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select language where role = 'rhea' order by notes limit 1583 col : year | film | role | language | notes row 1 : 2004 | kyun! ho gaya na | diya's sister | hindi | none row 2 : 2007 | lakshmi kalyanam | lakshmi | telugu | none row 3 : 2007 | chandamama | mahalakshmi | telugu | none row 4 : 2008 | pourudu | samyukhta | telugu | none row 5 : 2008 | pazhani | deepti | tamil | none row 6 : 2008 | aatadista | sunnanda | telugu | none row 7 : 2008 | saroja | pooja | tamil | cameo appearance row 8 : 2008 | bommalattam | anitha | tamil | none row 9 : 2009 | modhi vilayadu | easwari lakshmiram | tamil | none row 10 : 2009 | magadheera | yuvarani mithravindha devi indira (indu) | telugu | dual role nominated- filmfare award for best actress - telugu row 11 : 2009 | ganesh just ganesh | divya | telugu | none row 12 : 2009 | arya 2 | geethanjali | telugu | none row 13 : 2010 | om shanti | meghana | telugu | none row 14 : 2010 | darling | nandini | telugu | nominated- filmfare award for best actress - telugu row 15 : 2010 | naan mahaan alla | priya sudharsan | tamil | none row 16 : 2010 | brindaavanam | bhoomi | telugu | cinemaa award for best actress (telugu) row 17 : 2011 | mr. perfect | priya | telugu | nominated- filmfare award for best actress - telugu row 18 : 2011 | veera | chitti | telugu | none row 19 : 2011 | singham | kavya bhosle | hindi | nominated- filmfare award for best female debut row 20 : 2011 | dhada | rhea | telugu | none row 21 : 2012 | businessman | chitra | telugu | none row 22 : 2012 | maattrraan | anjali | tamil | none row 23 : 2012 | thuppakki | nisha | tamil | cinemaa award for best actress (tamil) row 24 : 2012 | sarocharu | sandhya | telugu | none row 25 : 2013 | naayak | madhu | telugu | none row 26 : 2013 | special 26 | priya chauhan | hindi | none row 27 : 2013 | baadshah | janaki | telugu | none row 28 : 2013 | all in all azhagu raja | chitra devi priya | tamil | none row 29 : 2014 | jilla | shanthi | tamil | none row 30 : 2014 | yevadu | deepthi | telugu | special appearance row 31 : 2014 | govindudu andarivadele | none | telugu | filming row 32 : 2014 | 'untitled balaji mohan project | none | tamil | pre-production | col : language row 1 : telugu | select language where role = 'rhea' order by notes limit 1583 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & film & role & language & notes \\
\midrule
0 & 2004 & kyun! ho gaya na & diya's sister & hindi & none \\
1 & 2007 & lakshmi kalyanam & lakshmi & telugu & none \\
2 & 2007 & chandamama & mahalakshmi & telugu & none \\
3 & 2008 & pourudu & samyukhta & telugu & none \\
4 & 2008 & pazhani & deepti & tamil & none \\
5 & 2008 & aatadista & sunnanda & telugu & none \\
6 & 2008 & saroja & pooja & tamil & cameo appearance \\
7 & 2008 & bommalattam & anitha & tamil & none \\
8 & 2009 & modhi vilayadu & easwari lakshmiram & tamil & none \\
9 & 2009 & magadheera & yuvarani mithravindha devi indira (indu) & telugu & dual role nominated- filmfare award for best actress - telugu \\
10 & 2009 & ganesh just ganesh & divya & telugu & none \\
11 & 2009 & arya 2 & geethanjali & telugu & none \\
12 & 2010 & om shanti & meghana & telugu & none \\
13 & 2010 & darling & nandini & telugu & nominated- filmfare award for best actress - telugu \\
14 & 2010 & naan mahaan alla & priya sudharsan & tamil & none \\
15 & 2010 & brindaavanam & bhoomi & telugu & cinemaa award for best actress (telugu) \\
16 & 2011 & mr. perfect & priya & telugu & nominated- filmfare award for best actress - telugu \\
17 & 2011 & veera & chitti & telugu & none \\
18 & 2011 & singham & kavya bhosle & hindi & nominated- filmfare award for best female debut \\
19 & 2011 & dhada & rhea & telugu & none \\
20 & 2012 & businessman & chitra & telugu & none \\
21 & 2012 & maattrraan & anjali & tamil & none \\
22 & 2012 & thuppakki & nisha & tamil & cinemaa award for best actress (tamil) \\
23 & 2012 & sarocharu & sandhya & telugu & none \\
24 & 2013 & naayak & madhu & telugu & none \\
25 & 2013 & special 26 & priya chauhan & hindi & none \\
26 & 2013 & baadshah & janaki & telugu & none \\
27 & 2013 & all in all azhagu raja & chitra devi priya & tamil & none \\
28 & 2014 & jilla & shanthi & tamil & none \\
29 & 2014 & yevadu & deepthi & telugu & special appearance \\
30 & 2014 & govindudu andarivadele & none & telugu & filming \\
31 & 2014 & 'untitled balaji mohan project & none & tamil & pre-production \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& language \\
\midrule
0 & telugu \\
\bottomrule
\end{tabular}
| select language where role = 'rhea' order by notes limit 1583 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>film</th>
<th>role</th>
<th>language</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004</td>
<td>kyun! ho gaya na</td>
<td>diya's sister</td>
<td>hindi</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2007</td>
<td>lakshmi kalyanam</td>
<td>lakshmi</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2007</td>
<td>chandamama</td>
<td>mahalakshmi</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2008</td>
<td>pourudu</td>
<td>samyukhta</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2008</td>
<td>pazhani</td>
<td>deepti</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>aatadista</td>
<td>sunnanda</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2008</td>
<td>saroja</td>
<td>pooja</td>
<td>tamil</td>
<td>cameo appearance</td>
</tr>
<tr>
<th>7</th>
<td>2008</td>
<td>bommalattam</td>
<td>anitha</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2009</td>
<td>modhi vilayadu</td>
<td>easwari lakshmiram</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>2009</td>
<td>magadheera</td>
<td>yuvarani mithravindha devi indira (indu)</td>
<td>telugu</td>
<td>dual role nominated- filmfare award for best actress - telugu</td>
</tr>
<tr>
<th>10</th>
<td>2009</td>
<td>ganesh just ganesh</td>
<td>divya</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>2009</td>
<td>arya 2</td>
<td>geethanjali</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>2010</td>
<td>om shanti</td>
<td>meghana</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>2010</td>
<td>darling</td>
<td>nandini</td>
<td>telugu</td>
<td>nominated- filmfare award for best actress - telugu</td>
</tr>
<tr>
<th>14</th>
<td>2010</td>
<td>naan mahaan alla</td>
<td>priya sudharsan</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>2010</td>
<td>brindaavanam</td>
<td>bhoomi</td>
<td>telugu</td>
<td>cinemaa award for best actress (telugu)</td>
</tr>
<tr>
<th>16</th>
<td>2011</td>
<td>mr. perfect</td>
<td>priya</td>
<td>telugu</td>
<td>nominated- filmfare award for best actress - telugu</td>
</tr>
<tr>
<th>17</th>
<td>2011</td>
<td>veera</td>
<td>chitti</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>2011</td>
<td>singham</td>
<td>kavya bhosle</td>
<td>hindi</td>
<td>nominated- filmfare award for best female debut</td>
</tr>
<tr>
<th>19</th>
<td>2011</td>
<td>dhada</td>
<td>rhea</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>2012</td>
<td>businessman</td>
<td>chitra</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>2012</td>
<td>maattrraan</td>
<td>anjali</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>2012</td>
<td>thuppakki</td>
<td>nisha</td>
<td>tamil</td>
<td>cinemaa award for best actress (tamil)</td>
</tr>
<tr>
<th>23</th>
<td>2012</td>
<td>sarocharu</td>
<td>sandhya</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>2013</td>
<td>naayak</td>
<td>madhu</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>2013</td>
<td>special 26</td>
<td>priya chauhan</td>
<td>hindi</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>2013</td>
<td>baadshah</td>
<td>janaki</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>2013</td>
<td>all in all azhagu raja</td>
<td>chitra devi priya</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>2014</td>
<td>jilla</td>
<td>shanthi</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>2014</td>
<td>yevadu</td>
<td>deepthi</td>
<td>telugu</td>
<td>special appearance</td>
</tr>
<tr>
<th>30</th>
<td>2014</td>
<td>govindudu andarivadele</td>
<td>none</td>
<td>telugu</td>
<td>filming</td>
</tr>
<tr>
<th>31</th>
<td>2014</td>
<td>'untitled balaji mohan project</td>
<td>none</td>
<td>tamil</td>
<td>pre-production</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>language</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>telugu</td>
</tr>
</tbody>
</table> | select language where role = 'rhea' order by notes limit 1583 <table_name> : table | | year | film | role | language | notes |
|---:|-------:|:-------------------------------|:-----------------------------------------|:-----------|:--------------------------------------------------------------|
| 0 | 2004 | kyun! ho gaya na | diya's sister | hindi | none |
| 1 | 2007 | lakshmi kalyanam | lakshmi | telugu | none |
| 2 | 2007 | chandamama | mahalakshmi | telugu | none |
| 3 | 2008 | pourudu | samyukhta | telugu | none |
| 4 | 2008 | pazhani | deepti | tamil | none |
| 5 | 2008 | aatadista | sunnanda | telugu | none |
| 6 | 2008 | saroja | pooja | tamil | cameo appearance |
| 7 | 2008 | bommalattam | anitha | tamil | none |
| 8 | 2009 | modhi vilayadu | easwari lakshmiram | tamil | none |
| 9 | 2009 | magadheera | yuvarani mithravindha devi indira (indu) | telugu | dual role nominated- filmfare award for best actress - telugu |
| 10 | 2009 | ganesh just ganesh | divya | telugu | none |
| 11 | 2009 | arya 2 | geethanjali | telugu | none |
| 12 | 2010 | om shanti | meghana | telugu | none |
| 13 | 2010 | darling | nandini | telugu | nominated- filmfare award for best actress - telugu |
| 14 | 2010 | naan mahaan alla | priya sudharsan | tamil | none |
| 15 | 2010 | brindaavanam | bhoomi | telugu | cinemaa award for best actress (telugu) |
| 16 | 2011 | mr. perfect | priya | telugu | nominated- filmfare award for best actress - telugu |
| 17 | 2011 | veera | chitti | telugu | none |
| 18 | 2011 | singham | kavya bhosle | hindi | nominated- filmfare award for best female debut |
| 19 | 2011 | dhada | rhea | telugu | none |
| 20 | 2012 | businessman | chitra | telugu | none |
| 21 | 2012 | maattrraan | anjali | tamil | none |
| 22 | 2012 | thuppakki | nisha | tamil | cinemaa award for best actress (tamil) |
| 23 | 2012 | sarocharu | sandhya | telugu | none |
| 24 | 2013 | naayak | madhu | telugu | none |
| 25 | 2013 | special 26 | priya chauhan | hindi | none |
| 26 | 2013 | baadshah | janaki | telugu | none |
| 27 | 2013 | all in all azhagu raja | chitra devi priya | tamil | none |
| 28 | 2014 | jilla | shanthi | tamil | none |
| 29 | 2014 | yevadu | deepthi | telugu | special appearance |
| 30 | 2014 | govindudu andarivadele | none | telugu | filming |
| 31 | 2014 | 'untitled balaji mohan project | none | tamil | pre-production | | | | language |
|---:|:-----------|
| 0 | telugu | | [
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select count ( * ) where language = 1472 col : year | film | role | language row 1 : 2004 | 7g rainbow colony | kadhir | tamil row 2 : 2005 | sukran | ravi shankar | tamil row 3 : 2005 | ponniyin selvan | venu | tamil row 4 : 2006 | kedi | raghu | tamil row 5 : 2008 | brahmanandam drama company | ravi | telugu row 6 : 2008 | netru indru naalai | vetri | tamil row 7 : 2008 | ninna nedu repu | vijay | telugu row 8 : 2009 | kadhalna summa illai | vetrivel | tamil row 9 : 2011 | aaranya kaandam | sappai | tamil | col : count ( "*" ) row 1 : 0 | select count ( * ) where language = 1472 <table_name> : table \begin{tabular}{lllll}
\toprule
& year & film & role & language \\
\midrule
0 & 2004 & 7g rainbow colony & kadhir & tamil \\
1 & 2005 & sukran & ravi shankar & tamil \\
2 & 2005 & ponniyin selvan & venu & tamil \\
3 & 2006 & kedi & raghu & tamil \\
4 & 2008 & brahmanandam drama company & ravi & telugu \\
5 & 2008 & netru indru naalai & vetri & tamil \\
6 & 2008 & ninna nedu repu & vijay & telugu \\
7 & 2009 & kadhalna summa illai & vetrivel & tamil \\
8 & 2011 & aaranya kaandam & sappai & tamil \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where language = 1472 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>film</th>
<th>role</th>
<th>language</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004</td>
<td>7g rainbow colony</td>
<td>kadhir</td>
<td>tamil</td>
</tr>
<tr>
<th>1</th>
<td>2005</td>
<td>sukran</td>
<td>ravi shankar</td>
<td>tamil</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>ponniyin selvan</td>
<td>venu</td>
<td>tamil</td>
</tr>
<tr>
<th>3</th>
<td>2006</td>
<td>kedi</td>
<td>raghu</td>
<td>tamil</td>
</tr>
<tr>
<th>4</th>
<td>2008</td>
<td>brahmanandam drama company</td>
<td>ravi</td>
<td>telugu</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>netru indru naalai</td>
<td>vetri</td>
<td>tamil</td>
</tr>
<tr>
<th>6</th>
<td>2008</td>
<td>ninna nedu repu</td>
<td>vijay</td>
<td>telugu</td>
</tr>
<tr>
<th>7</th>
<td>2009</td>
<td>kadhalna summa illai</td>
<td>vetrivel</td>
<td>tamil</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>aaranya kaandam</td>
<td>sappai</td>
<td>tamil</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where language = 1472 <table_name> : table | | year | film | role | language |
|---:|-------:|:---------------------------|:-------------|:-----------|
| 0 | 2004 | 7g rainbow colony | kadhir | tamil |
| 1 | 2005 | sukran | ravi shankar | tamil |
| 2 | 2005 | ponniyin selvan | venu | tamil |
| 3 | 2006 | kedi | raghu | tamil |
| 4 | 2008 | brahmanandam drama company | ravi | telugu |
| 5 | 2008 | netru indru naalai | vetri | tamil |
| 6 | 2008 | ninna nedu repu | vijay | telugu |
| 7 | 2009 | kadhalna summa illai | vetrivel | tamil |
| 8 | 2011 | aaranya kaandam | sappai | tamil | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( * ) where principal county = 'mariposa county' col : name of place | number of counties | principal county | lower zip code row 1 : yager junction | 1 | humboldt county | none row 2 : yale | 1 | riverside county | 92544 row 3 : yankee hill | 1 | butte county | 95965 row 4 : yankee hill | 1 | tuolumne county | none row 5 : yankee jims | 1 | placer county | 95713 row 6 : yarmouth | 1 | san joaquin county | none row 7 : yellowjacket | 1 | tehama county | none row 8 : yerba buena island | 1 | san francisco county | none row 9 : yermo | 1 | san bernardino county | 92398 row 10 : yettem | 1 | tulare county | 93670 row 11 : ygnacio valley | 1 | contra costa county | 94598 row 12 : yokohl | 1 | tulare county | none row 13 : yolano | 1 | solano county | 95620 row 14 : yolo | 1 | yolo county | 95697 row 15 : yontocket | 1 | del norte county | none row 16 : yorba | 1 | los angeles county | 91767 row 17 : yorba linda | 1 | orange county | 92686 row 18 : york | 1 | los angeles county | 90050 row 19 : yorkville | 1 | mendocino county | 95494 row 20 : yosemite forks | 1 | madera county | none row 21 : yosemite junction | 1 | tuolumne county | 95389 row 22 : yosemite lakes | 1 | madera county | none row 23 : yosemite lakes park | 1 | madera county | none row 24 : yosemite lodge | 1 | mariposa county | 95389 row 25 : yosemite national park | 3 | madera county | 95389 row 26 : yosemite national park | 3 | mariposa county | 95389 row 27 : yosemite national park | 3 | tuolumne county | 95389 row 28 : yosemite national park | 1 | mariposa county | 95389 row 29 : yosemite valley | 1 | mariposa county | none row 30 : yosemite village | 1 | mariposa county | none row 31 : you bet | 1 | nevada county | none row 32 : youngstown | 1 | san joaquin county | none row 33 : yountville | 1 | napa county | 94599 row 34 : yreka | 1 | siskiyou county | 96097 row 35 : yreka city | 1 | siskiyou county | 96097 row 36 : yuba city | 1 | sutter county | 95991 row 37 : yuba city farm labor center | 1 | sutter county | 95991 row 38 : south yuba city | 1 | sutter county | 95991 row 39 : yuba pass | 1 | nevada county | none row 40 : yuba-sutter area | 2 | sutter county yuba county | none row 41 : yucaipa | 1 | san bernardino county | 92399 row 42 : yucca grove | 1 | san bernardino county | none row 43 : yucca inn | 1 | san bernardino county | none row 44 : yucca valley | 1 | san bernardino county | 92284 row 45 : yurok indian reservation | 2 | del norte county | 95546 row 46 : yurok indian reservation | 2 | humboldt county | 95546 | col : count ( "*" ) row 1 : 5 | select count ( * ) where principal county = 'mariposa county' <table_name> : table \begin{tabular}{lllll}
\toprule
& name of place & number of counties & principal county & lower zip code \\
\midrule
0 & yager junction & 1 & humboldt county & none \\
1 & yale & 1 & riverside county & 92544 \\
2 & yankee hill & 1 & butte county & 95965 \\
3 & yankee hill & 1 & tuolumne county & none \\
4 & yankee jims & 1 & placer county & 95713 \\
5 & yarmouth & 1 & san joaquin county & none \\
6 & yellowjacket & 1 & tehama county & none \\
7 & yerba buena island & 1 & san francisco county & none \\
8 & yermo & 1 & san bernardino county & 92398 \\
9 & yettem & 1 & tulare county & 93670 \\
10 & ygnacio valley & 1 & contra costa county & 94598 \\
11 & yokohl & 1 & tulare county & none \\
12 & yolano & 1 & solano county & 95620 \\
13 & yolo & 1 & yolo county & 95697 \\
14 & yontocket & 1 & del norte county & none \\
15 & yorba & 1 & los angeles county & 91767 \\
16 & yorba linda & 1 & orange county & 92686 \\
17 & york & 1 & los angeles county & 90050 \\
18 & yorkville & 1 & mendocino county & 95494 \\
19 & yosemite forks & 1 & madera county & none \\
20 & yosemite junction & 1 & tuolumne county & 95389 \\
21 & yosemite lakes & 1 & madera county & none \\
22 & yosemite lakes park & 1 & madera county & none \\
23 & yosemite lodge & 1 & mariposa county & 95389 \\
24 & yosemite national park & 3 & madera county & 95389 \\
25 & yosemite national park & 3 & mariposa county & 95389 \\
26 & yosemite national park & 3 & tuolumne county & 95389 \\
27 & yosemite national park & 1 & mariposa county & 95389 \\
28 & yosemite valley & 1 & mariposa county & none \\
29 & yosemite village & 1 & mariposa county & none \\
30 & you bet & 1 & nevada county & none \\
31 & youngstown & 1 & san joaquin county & none \\
32 & yountville & 1 & napa county & 94599 \\
33 & yreka & 1 & siskiyou county & 96097 \\
34 & yreka city & 1 & siskiyou county & 96097 \\
35 & yuba city & 1 & sutter county & 95991 \\
36 & yuba city farm labor center & 1 & sutter county & 95991 \\
37 & south yuba city & 1 & sutter county & 95991 \\
38 & yuba pass & 1 & nevada county & none \\
39 & yuba-sutter area & 2 & sutter county yuba county & none \\
40 & yucaipa & 1 & san bernardino county & 92399 \\
41 & yucca grove & 1 & san bernardino county & none \\
42 & yucca inn & 1 & san bernardino county & none \\
43 & yucca valley & 1 & san bernardino county & 92284 \\
44 & yurok indian reservation & 2 & del norte county & 95546 \\
45 & yurok indian reservation & 2 & humboldt county & 95546 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( * ) where principal county = 'mariposa county' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name of place</th>
<th>number of counties</th>
<th>principal county</th>
<th>lower zip code</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>yager junction</td>
<td>1</td>
<td>humboldt county</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>yale</td>
<td>1</td>
<td>riverside county</td>
<td>92544</td>
</tr>
<tr>
<th>2</th>
<td>yankee hill</td>
<td>1</td>
<td>butte county</td>
<td>95965</td>
</tr>
<tr>
<th>3</th>
<td>yankee hill</td>
<td>1</td>
<td>tuolumne county</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>yankee jims</td>
<td>1</td>
<td>placer county</td>
<td>95713</td>
</tr>
<tr>
<th>5</th>
<td>yarmouth</td>
<td>1</td>
<td>san joaquin county</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>yellowjacket</td>
<td>1</td>
<td>tehama county</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>yerba buena island</td>
<td>1</td>
<td>san francisco county</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>yermo</td>
<td>1</td>
<td>san bernardino county</td>
<td>92398</td>
</tr>
<tr>
<th>9</th>
<td>yettem</td>
<td>1</td>
<td>tulare county</td>
<td>93670</td>
</tr>
<tr>
<th>10</th>
<td>ygnacio valley</td>
<td>1</td>
<td>contra costa county</td>
<td>94598</td>
</tr>
<tr>
<th>11</th>
<td>yokohl</td>
<td>1</td>
<td>tulare county</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>yolano</td>
<td>1</td>
<td>solano county</td>
<td>95620</td>
</tr>
<tr>
<th>13</th>
<td>yolo</td>
<td>1</td>
<td>yolo county</td>
<td>95697</td>
</tr>
<tr>
<th>14</th>
<td>yontocket</td>
<td>1</td>
<td>del norte county</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>yorba</td>
<td>1</td>
<td>los angeles county</td>
<td>91767</td>
</tr>
<tr>
<th>16</th>
<td>yorba linda</td>
<td>1</td>
<td>orange county</td>
<td>92686</td>
</tr>
<tr>
<th>17</th>
<td>york</td>
<td>1</td>
<td>los angeles county</td>
<td>90050</td>
</tr>
<tr>
<th>18</th>
<td>yorkville</td>
<td>1</td>
<td>mendocino county</td>
<td>95494</td>
</tr>
<tr>
<th>19</th>
<td>yosemite forks</td>
<td>1</td>
<td>madera county</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>yosemite junction</td>
<td>1</td>
<td>tuolumne county</td>
<td>95389</td>
</tr>
<tr>
<th>21</th>
<td>yosemite lakes</td>
<td>1</td>
<td>madera county</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>yosemite lakes park</td>
<td>1</td>
<td>madera county</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>yosemite lodge</td>
<td>1</td>
<td>mariposa county</td>
<td>95389</td>
</tr>
<tr>
<th>24</th>
<td>yosemite national park</td>
<td>3</td>
<td>madera county</td>
<td>95389</td>
</tr>
<tr>
<th>25</th>
<td>yosemite national park</td>
<td>3</td>
<td>mariposa county</td>
<td>95389</td>
</tr>
<tr>
<th>26</th>
<td>yosemite national park</td>
<td>3</td>
<td>tuolumne county</td>
<td>95389</td>
</tr>
<tr>
<th>27</th>
<td>yosemite national park</td>
<td>1</td>
<td>mariposa county</td>
<td>95389</td>
</tr>
<tr>
<th>28</th>
<td>yosemite valley</td>
<td>1</td>
<td>mariposa county</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>yosemite village</td>
<td>1</td>
<td>mariposa county</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>you bet</td>
<td>1</td>
<td>nevada county</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>youngstown</td>
<td>1</td>
<td>san joaquin county</td>
<td>none</td>
</tr>
<tr>
<th>32</th>
<td>yountville</td>
<td>1</td>
<td>napa county</td>
<td>94599</td>
</tr>
<tr>
<th>33</th>
<td>yreka</td>
<td>1</td>
<td>siskiyou county</td>
<td>96097</td>
</tr>
<tr>
<th>34</th>
<td>yreka city</td>
<td>1</td>
<td>siskiyou county</td>
<td>96097</td>
</tr>
<tr>
<th>35</th>
<td>yuba city</td>
<td>1</td>
<td>sutter county</td>
<td>95991</td>
</tr>
<tr>
<th>36</th>
<td>yuba city farm labor center</td>
<td>1</td>
<td>sutter county</td>
<td>95991</td>
</tr>
<tr>
<th>37</th>
<td>south yuba city</td>
<td>1</td>
<td>sutter county</td>
<td>95991</td>
</tr>
<tr>
<th>38</th>
<td>yuba pass</td>
<td>1</td>
<td>nevada county</td>
<td>none</td>
</tr>
<tr>
<th>39</th>
<td>yuba-sutter area</td>
<td>2</td>
<td>sutter county yuba county</td>
<td>none</td>
</tr>
<tr>
<th>40</th>
<td>yucaipa</td>
<td>1</td>
<td>san bernardino county</td>
<td>92399</td>
</tr>
<tr>
<th>41</th>
<td>yucca grove</td>
<td>1</td>
<td>san bernardino county</td>
<td>none</td>
</tr>
<tr>
<th>42</th>
<td>yucca inn</td>
<td>1</td>
<td>san bernardino county</td>
<td>none</td>
</tr>
<tr>
<th>43</th>
<td>yucca valley</td>
<td>1</td>
<td>san bernardino county</td>
<td>92284</td>
</tr>
<tr>
<th>44</th>
<td>yurok indian reservation</td>
<td>2</td>
<td>del norte county</td>
<td>95546</td>
</tr>
<tr>
<th>45</th>
<td>yurok indian reservation</td>
<td>2</td>
<td>humboldt county</td>
<td>95546</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
</tr>
</tbody>
</table> | select count ( * ) where principal county = 'mariposa county' <table_name> : table | | name of place | number of counties | principal county | lower zip code |
|---:|:----------------------------|---------------------:|:--------------------------|:-----------------|
| 0 | yager junction | 1 | humboldt county | none |
| 1 | yale | 1 | riverside county | 92544 |
| 2 | yankee hill | 1 | butte county | 95965 |
| 3 | yankee hill | 1 | tuolumne county | none |
| 4 | yankee jims | 1 | placer county | 95713 |
| 5 | yarmouth | 1 | san joaquin county | none |
| 6 | yellowjacket | 1 | tehama county | none |
| 7 | yerba buena island | 1 | san francisco county | none |
| 8 | yermo | 1 | san bernardino county | 92398 |
| 9 | yettem | 1 | tulare county | 93670 |
| 10 | ygnacio valley | 1 | contra costa county | 94598 |
| 11 | yokohl | 1 | tulare county | none |
| 12 | yolano | 1 | solano county | 95620 |
| 13 | yolo | 1 | yolo county | 95697 |
| 14 | yontocket | 1 | del norte county | none |
| 15 | yorba | 1 | los angeles county | 91767 |
| 16 | yorba linda | 1 | orange county | 92686 |
| 17 | york | 1 | los angeles county | 90050 |
| 18 | yorkville | 1 | mendocino county | 95494 |
| 19 | yosemite forks | 1 | madera county | none |
| 20 | yosemite junction | 1 | tuolumne county | 95389 |
| 21 | yosemite lakes | 1 | madera county | none |
| 22 | yosemite lakes park | 1 | madera county | none |
| 23 | yosemite lodge | 1 | mariposa county | 95389 |
| 24 | yosemite national park | 3 | madera county | 95389 |
| 25 | yosemite national park | 3 | mariposa county | 95389 |
| 26 | yosemite national park | 3 | tuolumne county | 95389 |
| 27 | yosemite national park | 1 | mariposa county | 95389 |
| 28 | yosemite valley | 1 | mariposa county | none |
| 29 | yosemite village | 1 | mariposa county | none |
| 30 | you bet | 1 | nevada county | none |
| 31 | youngstown | 1 | san joaquin county | none |
| 32 | yountville | 1 | napa county | 94599 |
| 33 | yreka | 1 | siskiyou county | 96097 |
| 34 | yreka city | 1 | siskiyou county | 96097 |
| 35 | yuba city | 1 | sutter county | 95991 |
| 36 | yuba city farm labor center | 1 | sutter county | 95991 |
| 37 | south yuba city | 1 | sutter county | 95991 |
| 38 | yuba pass | 1 | nevada county | none |
| 39 | yuba-sutter area | 2 | sutter county yuba county | none |
| 40 | yucaipa | 1 | san bernardino county | 92399 |
| 41 | yucca grove | 1 | san bernardino county | none |
| 42 | yucca inn | 1 | san bernardino county | none |
| 43 | yucca valley | 1 | san bernardino county | 92284 |
| 44 | yurok indian reservation | 2 | del norte county | 95546 |
| 45 | yurok indian reservation | 2 | humboldt county | 95546 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 5 | | [
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select max ( location ) where school = 'grosvenor high school' col : school | location | outright titles | shared titles | runners-up | total finals | last title | last final row 1 : methodist college belfast | belfast | 35 | 2 | 25 | 62 | 2014 | 2014 row 2 : royal belfast academical institution | belfast | 29 | 4 | 21 | 54 | 2007 | 2013 row 3 : campbell college | belfast | 23 | 4 | 12 | 39 | 2011 | 2011 row 4 : coleraine academical institution | coleraine | 9 | 0 | 24 | 33 | 1992 | 1998 row 5 : the royal school, armagh | armagh | 9 | 0 | 3 | 12 | 2004 | 2004 row 6 : portora royal school | enniskillen | 6 | 1 | 5 | 12 | 1942 | 1942 row 7 : bangor grammar school | bangor | 5 | 0 | 4 | 9 | 1988 | 1995 row 8 : ballymena academy | ballymena | 3 | 0 | 6 | 9 | 2010 | 2010 row 9 : rainey endowed school | magherafelt | 2 | 1 | 2 | 5 | 1982 | 1982 row 10 : foyle college | londonderry | 2 | 0 | 4 | 6 | 1915 | 1915 row 11 : belfast royal academy | belfast | 1 | 3 | 5 | 9 | 1997 | 2010 row 12 : regent house grammar school | newtownards | 1 | 1 | 2 | 4 | 1996 | 2008 row 13 : royal school dungannon | dungannon | 1 | 0 | 4 | 5 | 1907 | 1975 row 14 : annadale grammar school (now wellington college) | belfast | 1 | 0 | 1 | 2 | 1958 | 1978 row 15 : ballyclare high school | ballyclare | 1 | 0 | 1 | 2 | 1973 | 2012 row 16 : belfast boys' model school | belfast | 1 | 0 | 0 | 1 | 1971 | 1971 row 17 : grosvenor high school | belfast | 1 | 0 | 0 | 1 | 1983 | 1983 row 18 : wallace high school | lisburn | 0 | 0 | 4 | 4 | none | 2007 row 19 : derry academy | derry | 0 | 0 | 2 | 2 | none | 1896 row 20 : dalriada school | ballymoney | 0 | 0 | 1 | 1 | none | 1993 row 21 : galway grammar school | galway | 0 | 0 | 1 | 1 | none | 1887 row 22 : lurgan college | lurgan | 0 | 0 | 1 | 1 | none | 1934 row 23 : omagh academy | omagh | 0 | 0 | 1 | 1 | none | 1985 row 24 : sullivan upper school | holywood | 0 | 0 | 1 | 1 | none | 2014 | col : max ( "location" ) row 1 : belfast | select max ( location ) where school = 'grosvenor high school' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& school & location & outright titles & shared titles & runners-up & total finals & last title & last final \\
\midrule
0 & methodist college belfast & belfast & 35 & 2 & 25 & 62 & 2014 & 2014 \\
1 & royal belfast academical institution & belfast & 29 & 4 & 21 & 54 & 2007 & 2013 \\
2 & campbell college & belfast & 23 & 4 & 12 & 39 & 2011 & 2011 \\
3 & coleraine academical institution & coleraine & 9 & 0 & 24 & 33 & 1992 & 1998 \\
4 & the royal school, armagh & armagh & 9 & 0 & 3 & 12 & 2004 & 2004 \\
5 & portora royal school & enniskillen & 6 & 1 & 5 & 12 & 1942 & 1942 \\
6 & bangor grammar school & bangor & 5 & 0 & 4 & 9 & 1988 & 1995 \\
7 & ballymena academy & ballymena & 3 & 0 & 6 & 9 & 2010 & 2010 \\
8 & rainey endowed school & magherafelt & 2 & 1 & 2 & 5 & 1982 & 1982 \\
9 & foyle college & londonderry & 2 & 0 & 4 & 6 & 1915 & 1915 \\
10 & belfast royal academy & belfast & 1 & 3 & 5 & 9 & 1997 & 2010 \\
11 & regent house grammar school & newtownards & 1 & 1 & 2 & 4 & 1996 & 2008 \\
12 & royal school dungannon & dungannon & 1 & 0 & 4 & 5 & 1907 & 1975 \\
13 & annadale grammar school (now wellington college) & belfast & 1 & 0 & 1 & 2 & 1958 & 1978 \\
14 & ballyclare high school & ballyclare & 1 & 0 & 1 & 2 & 1973 & 2012 \\
15 & belfast boys' model school & belfast & 1 & 0 & 0 & 1 & 1971 & 1971 \\
16 & grosvenor high school & belfast & 1 & 0 & 0 & 1 & 1983 & 1983 \\
17 & wallace high school & lisburn & 0 & 0 & 4 & 4 & none & 2007 \\
18 & derry academy & derry & 0 & 0 & 2 & 2 & none & 1896 \\
19 & dalriada school & ballymoney & 0 & 0 & 1 & 1 & none & 1993 \\
20 & galway grammar school & galway & 0 & 0 & 1 & 1 & none & 1887 \\
21 & lurgan college & lurgan & 0 & 0 & 1 & 1 & none & 1934 \\
22 & omagh academy & omagh & 0 & 0 & 1 & 1 & none & 1985 \\
23 & sullivan upper school & holywood & 0 & 0 & 1 & 1 & none & 2014 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& max ( "location" ) \\
\midrule
0 & belfast \\
\bottomrule
\end{tabular}
| select max ( location ) where school = 'grosvenor high school' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>school</th>
<th>location</th>
<th>outright titles</th>
<th>shared titles</th>
<th>runners-up</th>
<th>total finals</th>
<th>last title</th>
<th>last final</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>methodist college belfast</td>
<td>belfast</td>
<td>35</td>
<td>2</td>
<td>25</td>
<td>62</td>
<td>2014</td>
<td>2014</td>
</tr>
<tr>
<th>1</th>
<td>royal belfast academical institution</td>
<td>belfast</td>
<td>29</td>
<td>4</td>
<td>21</td>
<td>54</td>
<td>2007</td>
<td>2013</td>
</tr>
<tr>
<th>2</th>
<td>campbell college</td>
<td>belfast</td>
<td>23</td>
<td>4</td>
<td>12</td>
<td>39</td>
<td>2011</td>
<td>2011</td>
</tr>
<tr>
<th>3</th>
<td>coleraine academical institution</td>
<td>coleraine</td>
<td>9</td>
<td>0</td>
<td>24</td>
<td>33</td>
<td>1992</td>
<td>1998</td>
</tr>
<tr>
<th>4</th>
<td>the royal school, armagh</td>
<td>armagh</td>
<td>9</td>
<td>0</td>
<td>3</td>
<td>12</td>
<td>2004</td>
<td>2004</td>
</tr>
<tr>
<th>5</th>
<td>portora royal school</td>
<td>enniskillen</td>
<td>6</td>
<td>1</td>
<td>5</td>
<td>12</td>
<td>1942</td>
<td>1942</td>
</tr>
<tr>
<th>6</th>
<td>bangor grammar school</td>
<td>bangor</td>
<td>5</td>
<td>0</td>
<td>4</td>
<td>9</td>
<td>1988</td>
<td>1995</td>
</tr>
<tr>
<th>7</th>
<td>ballymena academy</td>
<td>ballymena</td>
<td>3</td>
<td>0</td>
<td>6</td>
<td>9</td>
<td>2010</td>
<td>2010</td>
</tr>
<tr>
<th>8</th>
<td>rainey endowed school</td>
<td>magherafelt</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>5</td>
<td>1982</td>
<td>1982</td>
</tr>
<tr>
<th>9</th>
<td>foyle college</td>
<td>londonderry</td>
<td>2</td>
<td>0</td>
<td>4</td>
<td>6</td>
<td>1915</td>
<td>1915</td>
</tr>
<tr>
<th>10</th>
<td>belfast royal academy</td>
<td>belfast</td>
<td>1</td>
<td>3</td>
<td>5</td>
<td>9</td>
<td>1997</td>
<td>2010</td>
</tr>
<tr>
<th>11</th>
<td>regent house grammar school</td>
<td>newtownards</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>4</td>
<td>1996</td>
<td>2008</td>
</tr>
<tr>
<th>12</th>
<td>royal school dungannon</td>
<td>dungannon</td>
<td>1</td>
<td>0</td>
<td>4</td>
<td>5</td>
<td>1907</td>
<td>1975</td>
</tr>
<tr>
<th>13</th>
<td>annadale grammar school (now wellington college)</td>
<td>belfast</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
<td>1958</td>
<td>1978</td>
</tr>
<tr>
<th>14</th>
<td>ballyclare high school</td>
<td>ballyclare</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
<td>1973</td>
<td>2012</td>
</tr>
<tr>
<th>15</th>
<td>belfast boys' model school</td>
<td>belfast</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1971</td>
<td>1971</td>
</tr>
<tr>
<th>16</th>
<td>grosvenor high school</td>
<td>belfast</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1983</td>
<td>1983</td>
</tr>
<tr>
<th>17</th>
<td>wallace high school</td>
<td>lisburn</td>
<td>0</td>
<td>0</td>
<td>4</td>
<td>4</td>
<td>none</td>
<td>2007</td>
</tr>
<tr>
<th>18</th>
<td>derry academy</td>
<td>derry</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
<td>none</td>
<td>1896</td>
</tr>
<tr>
<th>19</th>
<td>dalriada school</td>
<td>ballymoney</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>1993</td>
</tr>
<tr>
<th>20</th>
<td>galway grammar school</td>
<td>galway</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>1887</td>
</tr>
<tr>
<th>21</th>
<td>lurgan college</td>
<td>lurgan</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>1934</td>
</tr>
<tr>
<th>22</th>
<td>omagh academy</td>
<td>omagh</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>1985</td>
</tr>
<tr>
<th>23</th>
<td>sullivan upper school</td>
<td>holywood</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>2014</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>max ( "location" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>belfast</td>
</tr>
</tbody>
</table> | select max ( location ) where school = 'grosvenor high school' <table_name> : table | | school | location | outright titles | shared titles | runners-up | total finals | last title | last final |
|---:|:-------------------------------------------------|:------------|------------------:|----------------:|-------------:|---------------:|:-------------|-------------:|
| 0 | methodist college belfast | belfast | 35 | 2 | 25 | 62 | 2014 | 2014 |
| 1 | royal belfast academical institution | belfast | 29 | 4 | 21 | 54 | 2007 | 2013 |
| 2 | campbell college | belfast | 23 | 4 | 12 | 39 | 2011 | 2011 |
| 3 | coleraine academical institution | coleraine | 9 | 0 | 24 | 33 | 1992 | 1998 |
| 4 | the royal school, armagh | armagh | 9 | 0 | 3 | 12 | 2004 | 2004 |
| 5 | portora royal school | enniskillen | 6 | 1 | 5 | 12 | 1942 | 1942 |
| 6 | bangor grammar school | bangor | 5 | 0 | 4 | 9 | 1988 | 1995 |
| 7 | ballymena academy | ballymena | 3 | 0 | 6 | 9 | 2010 | 2010 |
| 8 | rainey endowed school | magherafelt | 2 | 1 | 2 | 5 | 1982 | 1982 |
| 9 | foyle college | londonderry | 2 | 0 | 4 | 6 | 1915 | 1915 |
| 10 | belfast royal academy | belfast | 1 | 3 | 5 | 9 | 1997 | 2010 |
| 11 | regent house grammar school | newtownards | 1 | 1 | 2 | 4 | 1996 | 2008 |
| 12 | royal school dungannon | dungannon | 1 | 0 | 4 | 5 | 1907 | 1975 |
| 13 | annadale grammar school (now wellington college) | belfast | 1 | 0 | 1 | 2 | 1958 | 1978 |
| 14 | ballyclare high school | ballyclare | 1 | 0 | 1 | 2 | 1973 | 2012 |
| 15 | belfast boys' model school | belfast | 1 | 0 | 0 | 1 | 1971 | 1971 |
| 16 | grosvenor high school | belfast | 1 | 0 | 0 | 1 | 1983 | 1983 |
| 17 | wallace high school | lisburn | 0 | 0 | 4 | 4 | none | 2007 |
| 18 | derry academy | derry | 0 | 0 | 2 | 2 | none | 1896 |
| 19 | dalriada school | ballymoney | 0 | 0 | 1 | 1 | none | 1993 |
| 20 | galway grammar school | galway | 0 | 0 | 1 | 1 | none | 1887 |
| 21 | lurgan college | lurgan | 0 | 0 | 1 | 1 | none | 1934 |
| 22 | omagh academy | omagh | 0 | 0 | 1 | 1 | none | 1985 |
| 23 | sullivan upper school | holywood | 0 | 0 | 1 | 1 | none | 2014 | | | | max ( "location" ) |
|---:|:---------------------|
| 0 | belfast | | [
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select count ( nationality ) where time = 0 col : rank | name | nationality | time row 1 : none | joanne malar | canada | 4:43.64 row 2 : none | alison fealey | united states | 4:48.31 row 3 : none | jenny kurth | united states | 4:57.24 row 4 : 4 | sonia fonseca | puerto rico | 5:03.15 row 5 : 5 | fabiola molina | brazil | 5:03.43 row 6 : 6 | isabel rojas | colombia | 5:11.58 row 7 : 7 | carolyn adel | suriname | 5:13.24 row 8 : 8 | edith arraspide | argentina | 5:13.95 | col : count ( "nationality" ) row 1 : 0 | select count ( nationality ) where time = 0 <table_name> : table \begin{tabular}{lllll}
\toprule
& rank & name & nationality & time \\
\midrule
0 & none & joanne malar & canada & 4:43.64 \\
1 & none & alison fealey & united states & 4:48.31 \\
2 & none & jenny kurth & united states & 4:57.24 \\
3 & 4 & sonia fonseca & puerto rico & 5:03.15 \\
4 & 5 & fabiola molina & brazil & 5:03.43 \\
5 & 6 & isabel rojas & colombia & 5:11.58 \\
6 & 7 & carolyn adel & suriname & 5:13.24 \\
7 & 8 & edith arraspide & argentina & 5:13.95 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "nationality" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( nationality ) where time = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>nationality</th>
<th>time</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>joanne malar</td>
<td>canada</td>
<td>4:43.64</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>alison fealey</td>
<td>united states</td>
<td>4:48.31</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>jenny kurth</td>
<td>united states</td>
<td>4:57.24</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>sonia fonseca</td>
<td>puerto rico</td>
<td>5:03.15</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>fabiola molina</td>
<td>brazil</td>
<td>5:03.43</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>isabel rojas</td>
<td>colombia</td>
<td>5:11.58</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>carolyn adel</td>
<td>suriname</td>
<td>5:13.24</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>edith arraspide</td>
<td>argentina</td>
<td>5:13.95</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "nationality" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( nationality ) where time = 0 <table_name> : table | | rank | name | nationality | time |
|---:|:-------|:----------------|:--------------|:--------|
| 0 | none | joanne malar | canada | 4:43.64 |
| 1 | none | alison fealey | united states | 4:48.31 |
| 2 | none | jenny kurth | united states | 4:57.24 |
| 3 | 4 | sonia fonseca | puerto rico | 5:03.15 |
| 4 | 5 | fabiola molina | brazil | 5:03.43 |
| 5 | 6 | isabel rojas | colombia | 5:11.58 |
| 6 | 7 | carolyn adel | suriname | 5:13.24 |
| 7 | 8 | edith arraspide | argentina | 5:13.95 | | | | count ( "nationality" ) |
|---:|--------------------------:|
| 0 | 0 | | [
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select name where rank = 6 col : rank | name | nationality | time row 1 : none | sule utura | ethiopia | 15:38.70 row 2 : none | emebet anteneh mengistu | ethiopia | 15:40.13 row 3 : none | pauline korikwiang | kenya | 15:40.93 row 4 : 4 | hyvin jepkemoi | kenya | 15:42.64 row 5 : 5 | esther ndiema | kenya | 15:43.48 row 6 : 6 | goytetom gebresilasse | ethiopia | 15:49.90 row 7 : 7 | angeline myiramsabimana | rwanda | 16:24.04 row 8 : 8 | mekdes weldu | eritrea | 16:42.69 row 9 : 9 | thandiwe nyathy | zimbabwe | 17:13.00 | col : name row 1 : goytetom gebresilasse | select name where rank = 6 <table_name> : table \begin{tabular}{lllll}
\toprule
& rank & name & nationality & time \\
\midrule
0 & none & sule utura & ethiopia & 15:38.70 \\
1 & none & emebet anteneh mengistu & ethiopia & 15:40.13 \\
2 & none & pauline korikwiang & kenya & 15:40.93 \\
3 & 4 & hyvin jepkemoi & kenya & 15:42.64 \\
4 & 5 & esther ndiema & kenya & 15:43.48 \\
5 & 6 & goytetom gebresilasse & ethiopia & 15:49.90 \\
6 & 7 & angeline myiramsabimana & rwanda & 16:24.04 \\
7 & 8 & mekdes weldu & eritrea & 16:42.69 \\
8 & 9 & thandiwe nyathy & zimbabwe & 17:13.00 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& name \\
\midrule
0 & goytetom gebresilasse \\
\bottomrule
\end{tabular}
| select name where rank = 6 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>nationality</th>
<th>time</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>sule utura</td>
<td>ethiopia</td>
<td>15:38.70</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>emebet anteneh mengistu</td>
<td>ethiopia</td>
<td>15:40.13</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>pauline korikwiang</td>
<td>kenya</td>
<td>15:40.93</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>hyvin jepkemoi</td>
<td>kenya</td>
<td>15:42.64</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>esther ndiema</td>
<td>kenya</td>
<td>15:43.48</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>goytetom gebresilasse</td>
<td>ethiopia</td>
<td>15:49.90</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>angeline myiramsabimana</td>
<td>rwanda</td>
<td>16:24.04</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>mekdes weldu</td>
<td>eritrea</td>
<td>16:42.69</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>thandiwe nyathy</td>
<td>zimbabwe</td>
<td>17:13.00</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>goytetom gebresilasse</td>
</tr>
</tbody>
</table> | select name where rank = 6 <table_name> : table | | rank | name | nationality | time |
|---:|:-------|:------------------------|:--------------|:---------|
| 0 | none | sule utura | ethiopia | 15:38.70 |
| 1 | none | emebet anteneh mengistu | ethiopia | 15:40.13 |
| 2 | none | pauline korikwiang | kenya | 15:40.93 |
| 3 | 4 | hyvin jepkemoi | kenya | 15:42.64 |
| 4 | 5 | esther ndiema | kenya | 15:43.48 |
| 5 | 6 | goytetom gebresilasse | ethiopia | 15:49.90 |
| 6 | 7 | angeline myiramsabimana | rwanda | 16:24.04 |
| 7 | 8 | mekdes weldu | eritrea | 16:42.69 |
| 8 | 9 | thandiwe nyathy | zimbabwe | 17:13.00 | | | | name |
|---:|:----------------------|
| 0 | goytetom gebresilasse | | [
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select count ( * ) where league apps > 1462 col : name | nation | position | league apps | league goals | fa cup apps | fa cup goals | total apps | total goals row 1 : ned barkas | england | df | 4 | 0 | 0 | 0 | 4 | 0 row 2 : harry brough | england | df | 9 | 0 | 0 | 0 | 9 | 0 row 3 : george brown | england | fw | 6 | 4 | 0 | 0 | 6 | 4 row 4 : jack byers | england | mf | 5 | 1 | 0 | 0 | 5 | 1 row 5 : harry cawthorne | england | df | 5 | 0 | 0 | 0 | 5 | 0 row 6 : ted davis | england | gk | 27 | 0 | 7 | 0 | 34 | 0 row 7 : ernie islip | england | fw | 34 | 11 | 9 | 4 | 43 | 15 row 8 : billy johnston | england | fw | 21 | 2 | 2 | 0 | 23 | 2 row 9 : robert jones | england | mf | 2 | 1 | 0 | 0 | 2 | 1 row 10 : frank mann | england | fw | 40 | 5 | 8 | 4 | 48 | 9 row 11 : len marlow | england | fw | 1 | 0 | 0 | 0 | 1 | 0 row 12 : colin mckay | scotland | df | 14 | 2 | 0 | 0 | 14 | 2 row 13 : sandy mutch | scotland | gk | 15 | 0 | 2 | 0 | 17 | 0 row 14 : stan pearson | england | mf | 1 | 0 | 1 | 0 | 2 | 0 row 15 : george richardson | england | mf | 14 | 1 | 8 | 1 | 22 | 2 row 16 : charlie slade | england | df | 25 | 0 | 9 | 0 | 34 | 0 row 17 : billy e. smith | england | fw | 1 | 0 | 0 | 0 | 1 | 0 row 18 : billy h. smith | england | mf | 40 | 8 | 9 | 4 | 49 | 12 row 19 : clem stephenson | england | fw | 39 | 9 | 9 | 6 | 48 | 15 row 20 : jack swann | england | fw | 9 | 3 | 0 | 0 | 9 | 3 row 21 : sam wadsworth | england | df | 39 | 1 | 9 | 0 | 48 | 1 row 22 : billy watson | england | df | 36 | 0 | 9 | 1 | 45 | 1 row 23 : tom wilson | england | df | 39 | 1 | 9 | 0 | 48 | 1 row 24 : james wood | england | df | 36 | 0 | 9 | 0 | 45 | 0 | col : count ( "*" ) row 1 : 19 | select count ( * ) where league apps > 1462 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& name & nation & position & league apps & league goals & fa cup apps & fa cup goals & total apps & total goals \\
\midrule
0 & ned barkas & england & df & 4 & 0 & 0 & 0 & 4 & 0 \\
1 & harry brough & england & df & 9 & 0 & 0 & 0 & 9 & 0 \\
2 & george brown & england & fw & 6 & 4 & 0 & 0 & 6 & 4 \\
3 & jack byers & england & mf & 5 & 1 & 0 & 0 & 5 & 1 \\
4 & harry cawthorne & england & df & 5 & 0 & 0 & 0 & 5 & 0 \\
5 & ted davis & england & gk & 27 & 0 & 7 & 0 & 34 & 0 \\
6 & ernie islip & england & fw & 34 & 11 & 9 & 4 & 43 & 15 \\
7 & billy johnston & england & fw & 21 & 2 & 2 & 0 & 23 & 2 \\
8 & robert jones & england & mf & 2 & 1 & 0 & 0 & 2 & 1 \\
9 & frank mann & england & fw & 40 & 5 & 8 & 4 & 48 & 9 \\
10 & len marlow & england & fw & 1 & 0 & 0 & 0 & 1 & 0 \\
11 & colin mckay & scotland & df & 14 & 2 & 0 & 0 & 14 & 2 \\
12 & sandy mutch & scotland & gk & 15 & 0 & 2 & 0 & 17 & 0 \\
13 & stan pearson & england & mf & 1 & 0 & 1 & 0 & 2 & 0 \\
14 & george richardson & england & mf & 14 & 1 & 8 & 1 & 22 & 2 \\
15 & charlie slade & england & df & 25 & 0 & 9 & 0 & 34 & 0 \\
16 & billy e. smith & england & fw & 1 & 0 & 0 & 0 & 1 & 0 \\
17 & billy h. smith & england & mf & 40 & 8 & 9 & 4 & 49 & 12 \\
18 & clem stephenson & england & fw & 39 & 9 & 9 & 6 & 48 & 15 \\
19 & jack swann & england & fw & 9 & 3 & 0 & 0 & 9 & 3 \\
20 & sam wadsworth & england & df & 39 & 1 & 9 & 0 & 48 & 1 \\
21 & billy watson & england & df & 36 & 0 & 9 & 1 & 45 & 1 \\
22 & tom wilson & england & df & 39 & 1 & 9 & 0 & 48 & 1 \\
23 & james wood & england & df & 36 & 0 & 9 & 0 & 45 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 19 \\
\bottomrule
\end{tabular}
| select count ( * ) where league apps > 1462 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>nation</th>
<th>position</th>
<th>league apps</th>
<th>league goals</th>
<th>fa cup apps</th>
<th>fa cup goals</th>
<th>total apps</th>
<th>total goals</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>ned barkas</td>
<td>england</td>
<td>df</td>
<td>4</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>4</td>
<td>0</td>
</tr>
<tr>
<th>1</th>
<td>harry brough</td>
<td>england</td>
<td>df</td>
<td>9</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>9</td>
<td>0</td>
</tr>
<tr>
<th>2</th>
<td>george brown</td>
<td>england</td>
<td>fw</td>
<td>6</td>
<td>4</td>
<td>0</td>
<td>0</td>
<td>6</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>jack byers</td>
<td>england</td>
<td>mf</td>
<td>5</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>5</td>
<td>1</td>
</tr>
<tr>
<th>4</th>
<td>harry cawthorne</td>
<td>england</td>
<td>df</td>
<td>5</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>5</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>ted davis</td>
<td>england</td>
<td>gk</td>
<td>27</td>
<td>0</td>
<td>7</td>
<td>0</td>
<td>34</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>ernie islip</td>
<td>england</td>
<td>fw</td>
<td>34</td>
<td>11</td>
<td>9</td>
<td>4</td>
<td>43</td>
<td>15</td>
</tr>
<tr>
<th>7</th>
<td>billy johnston</td>
<td>england</td>
<td>fw</td>
<td>21</td>
<td>2</td>
<td>2</td>
<td>0</td>
<td>23</td>
<td>2</td>
</tr>
<tr>
<th>8</th>
<td>robert jones</td>
<td>england</td>
<td>mf</td>
<td>2</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>frank mann</td>
<td>england</td>
<td>fw</td>
<td>40</td>
<td>5</td>
<td>8</td>
<td>4</td>
<td>48</td>
<td>9</td>
</tr>
<tr>
<th>10</th>
<td>len marlow</td>
<td>england</td>
<td>fw</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0</td>
</tr>
<tr>
<th>11</th>
<td>colin mckay</td>
<td>scotland</td>
<td>df</td>
<td>14</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>14</td>
<td>2</td>
</tr>
<tr>
<th>12</th>
<td>sandy mutch</td>
<td>scotland</td>
<td>gk</td>
<td>15</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>17</td>
<td>0</td>
</tr>
<tr>
<th>13</th>
<td>stan pearson</td>
<td>england</td>
<td>mf</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>2</td>
<td>0</td>
</tr>
<tr>
<th>14</th>
<td>george richardson</td>
<td>england</td>
<td>mf</td>
<td>14</td>
<td>1</td>
<td>8</td>
<td>1</td>
<td>22</td>
<td>2</td>
</tr>
<tr>
<th>15</th>
<td>charlie slade</td>
<td>england</td>
<td>df</td>
<td>25</td>
<td>0</td>
<td>9</td>
<td>0</td>
<td>34</td>
<td>0</td>
</tr>
<tr>
<th>16</th>
<td>billy e. smith</td>
<td>england</td>
<td>fw</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0</td>
</tr>
<tr>
<th>17</th>
<td>billy h. smith</td>
<td>england</td>
<td>mf</td>
<td>40</td>
<td>8</td>
<td>9</td>
<td>4</td>
<td>49</td>
<td>12</td>
</tr>
<tr>
<th>18</th>
<td>clem stephenson</td>
<td>england</td>
<td>fw</td>
<td>39</td>
<td>9</td>
<td>9</td>
<td>6</td>
<td>48</td>
<td>15</td>
</tr>
<tr>
<th>19</th>
<td>jack swann</td>
<td>england</td>
<td>fw</td>
<td>9</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>9</td>
<td>3</td>
</tr>
<tr>
<th>20</th>
<td>sam wadsworth</td>
<td>england</td>
<td>df</td>
<td>39</td>
<td>1</td>
<td>9</td>
<td>0</td>
<td>48</td>
<td>1</td>
</tr>
<tr>
<th>21</th>
<td>billy watson</td>
<td>england</td>
<td>df</td>
<td>36</td>
<td>0</td>
<td>9</td>
<td>1</td>
<td>45</td>
<td>1</td>
</tr>
<tr>
<th>22</th>
<td>tom wilson</td>
<td>england</td>
<td>df</td>
<td>39</td>
<td>1</td>
<td>9</td>
<td>0</td>
<td>48</td>
<td>1</td>
</tr>
<tr>
<th>23</th>
<td>james wood</td>
<td>england</td>
<td>df</td>
<td>36</td>
<td>0</td>
<td>9</td>
<td>0</td>
<td>45</td>
<td>0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>19</td>
</tr>
</tbody>
</table> | select count ( * ) where league apps > 1462 <table_name> : table | | name | nation | position | league apps | league goals | fa cup apps | fa cup goals | total apps | total goals |
|---:|:------------------|:---------|:-----------|--------------:|---------------:|--------------:|---------------:|-------------:|--------------:|
| 0 | ned barkas | england | df | 4 | 0 | 0 | 0 | 4 | 0 |
| 1 | harry brough | england | df | 9 | 0 | 0 | 0 | 9 | 0 |
| 2 | george brown | england | fw | 6 | 4 | 0 | 0 | 6 | 4 |
| 3 | jack byers | england | mf | 5 | 1 | 0 | 0 | 5 | 1 |
| 4 | harry cawthorne | england | df | 5 | 0 | 0 | 0 | 5 | 0 |
| 5 | ted davis | england | gk | 27 | 0 | 7 | 0 | 34 | 0 |
| 6 | ernie islip | england | fw | 34 | 11 | 9 | 4 | 43 | 15 |
| 7 | billy johnston | england | fw | 21 | 2 | 2 | 0 | 23 | 2 |
| 8 | robert jones | england | mf | 2 | 1 | 0 | 0 | 2 | 1 |
| 9 | frank mann | england | fw | 40 | 5 | 8 | 4 | 48 | 9 |
| 10 | len marlow | england | fw | 1 | 0 | 0 | 0 | 1 | 0 |
| 11 | colin mckay | scotland | df | 14 | 2 | 0 | 0 | 14 | 2 |
| 12 | sandy mutch | scotland | gk | 15 | 0 | 2 | 0 | 17 | 0 |
| 13 | stan pearson | england | mf | 1 | 0 | 1 | 0 | 2 | 0 |
| 14 | george richardson | england | mf | 14 | 1 | 8 | 1 | 22 | 2 |
| 15 | charlie slade | england | df | 25 | 0 | 9 | 0 | 34 | 0 |
| 16 | billy e. smith | england | fw | 1 | 0 | 0 | 0 | 1 | 0 |
| 17 | billy h. smith | england | mf | 40 | 8 | 9 | 4 | 49 | 12 |
| 18 | clem stephenson | england | fw | 39 | 9 | 9 | 6 | 48 | 15 |
| 19 | jack swann | england | fw | 9 | 3 | 0 | 0 | 9 | 3 |
| 20 | sam wadsworth | england | df | 39 | 1 | 9 | 0 | 48 | 1 |
| 21 | billy watson | england | df | 36 | 0 | 9 | 1 | 45 | 1 |
| 22 | tom wilson | england | df | 39 | 1 | 9 | 0 | 48 | 1 |
| 23 | james wood | england | df | 36 | 0 | 9 | 0 | 45 | 0 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 19 | | [
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select english where dutch = 'ja' col : afrikaans | ipa | dutch | english | german row 1 : hallo! hoe gaan dit? | [ɦaləu ɦu xaˑn dət] | hallo! hoe gaat het (met je/jou/u)? also used: hallo! hoe is het? | hello! how is it going? (hello! how are you?) | hallo! wie geht's? (hallo! wie geht's dir/ihnen?) row 2 : baie goed, dankie | [bajə xuˑt daŋki] | heel goed, dank je | very well, thank you | sehr gut, danke row 3 : praat jy afrikaans? | [prɑˑt jəi afrikɑˑs] | spreek/praat je/jij afrikaans? | do you speak afrikaans? | sprichst du afrikaans? row 4 : praat jy engels? | [prɑˑt jəi ɛŋəls] | spreek/praat je/jij engels? | do you speak english? | sprichst du englisch? row 5 : ja | [jɑˑ] | ja | yes | ja row 6 : nee | [neˑə] | nee | no | nein row 7 : 'n bietjie | [ə biki] | een beetje | a bit | ein bisschen row 8 : wat is jou naam? | [vat əs jəu nɑˑm] | hoe heet je? / wat is jouw naam? | what is your name? | wie heißt du? / wie ist dein name? row 9 : die kinders praat afrikaans | [di kənərs prɑˑt afrikɑˑns] | de kinderen spreken/praten afrikaans | the children speak afrikaans | die kinder sprechen afrikaans row 10 : ek is lief vir jou. less common: ek het jou lief | [æk əs lif vɯr jəʊ] | ik hou van je/jou. common in southern dutch: ik heb je/jou/u lief | i love you | ich liebe dich. also: ich habe dich lieb. (colloquial; virtually no romantic connotation) | col : english row 1 : yes | select english where dutch = 'ja' <table_name> : table \begin{tabular}{llllll}
\toprule
& afrikaans & ipa & dutch & english & german \\
\midrule
0 & hallo! hoe gaan dit? & [ɦaləu ɦu xaˑn dət] & hallo! hoe gaat het (met je/jou/u)? also used: hallo! hoe is het? & hello! how is it going? (hello! how are you?) & hallo! wie geht's? (hallo! wie geht's dir/ihnen?) \\
1 & baie goed, dankie & [bajə xuˑt daŋki] & heel goed, dank je & very well, thank you & sehr gut, danke \\
2 & praat jy afrikaans? & [prɑˑt jəi afrikɑˑs] & spreek/praat je/jij afrikaans? & do you speak afrikaans? & sprichst du afrikaans? \\
3 & praat jy engels? & [prɑˑt jəi ɛŋəls] & spreek/praat je/jij engels? & do you speak english? & sprichst du englisch? \\
4 & ja & [jɑˑ] & ja & yes & ja \\
5 & nee & [neˑə] & nee & no & nein \\
6 & 'n bietjie & [ə biki] & een beetje & a bit & ein bisschen \\
7 & wat is jou naam? & [vat əs jəu nɑˑm] & hoe heet je? / wat is jouw naam? & what is your name? & wie heißt du? / wie ist dein name? \\
8 & die kinders praat afrikaans & [di kənərs prɑˑt afrikɑˑns] & de kinderen spreken/praten afrikaans & the children speak afrikaans & die kinder sprechen afrikaans \\
9 & ek is lief vir jou. less common: ek het jou lief & [æk əs lif vɯr jəʊ] & ik hou van je/jou. common in southern dutch: ik heb je/jou/u lief & i love you & ich liebe dich. also: ich habe dich lieb. (colloquial; virtually no romantic connotation) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& english \\
\midrule
0 & yes \\
\bottomrule
\end{tabular}
| select english where dutch = 'ja' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>afrikaans</th>
<th>ipa</th>
<th>dutch</th>
<th>english</th>
<th>german</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>hallo! hoe gaan dit?</td>
<td>[ɦaləu ɦu xaˑn dət]</td>
<td>hallo! hoe gaat het (met je/jou/u)? also used: hallo! hoe is het?</td>
<td>hello! how is it going? (hello! how are you?)</td>
<td>hallo! wie geht's? (hallo! wie geht's dir/ihnen?)</td>
</tr>
<tr>
<th>1</th>
<td>baie goed, dankie</td>
<td>[bajə xuˑt daŋki]</td>
<td>heel goed, dank je</td>
<td>very well, thank you</td>
<td>sehr gut, danke</td>
</tr>
<tr>
<th>2</th>
<td>praat jy afrikaans?</td>
<td>[prɑˑt jəi afrikɑˑs]</td>
<td>spreek/praat je/jij afrikaans?</td>
<td>do you speak afrikaans?</td>
<td>sprichst du afrikaans?</td>
</tr>
<tr>
<th>3</th>
<td>praat jy engels?</td>
<td>[prɑˑt jəi ɛŋəls]</td>
<td>spreek/praat je/jij engels?</td>
<td>do you speak english?</td>
<td>sprichst du englisch?</td>
</tr>
<tr>
<th>4</th>
<td>ja</td>
<td>[jɑˑ]</td>
<td>ja</td>
<td>yes</td>
<td>ja</td>
</tr>
<tr>
<th>5</th>
<td>nee</td>
<td>[neˑə]</td>
<td>nee</td>
<td>no</td>
<td>nein</td>
</tr>
<tr>
<th>6</th>
<td>'n bietjie</td>
<td>[ə biki]</td>
<td>een beetje</td>
<td>a bit</td>
<td>ein bisschen</td>
</tr>
<tr>
<th>7</th>
<td>wat is jou naam?</td>
<td>[vat əs jəu nɑˑm]</td>
<td>hoe heet je? / wat is jouw naam?</td>
<td>what is your name?</td>
<td>wie heißt du? / wie ist dein name?</td>
</tr>
<tr>
<th>8</th>
<td>die kinders praat afrikaans</td>
<td>[di kənərs prɑˑt afrikɑˑns]</td>
<td>de kinderen spreken/praten afrikaans</td>
<td>the children speak afrikaans</td>
<td>die kinder sprechen afrikaans</td>
</tr>
<tr>
<th>9</th>
<td>ek is lief vir jou. less common: ek het jou lief</td>
<td>[æk əs lif vɯr jəʊ]</td>
<td>ik hou van je/jou. common in southern dutch: ik heb je/jou/u lief</td>
<td>i love you</td>
<td>ich liebe dich. also: ich habe dich lieb. (colloquial; virtually no romantic connotation)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>english</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>yes</td>
</tr>
</tbody>
</table> | select english where dutch = 'ja' <table_name> : table | | afrikaans | ipa | dutch | english | german |
|---:|:-------------------------------------------------|:----------------------------|:------------------------------------------------------------------|:----------------------------------------------|:------------------------------------------------------------------------------------------|
| 0 | hallo! hoe gaan dit? | [ɦaləu ɦu xaˑn dət] | hallo! hoe gaat het (met je/jou/u)? also used: hallo! hoe is het? | hello! how is it going? (hello! how are you?) | hallo! wie geht's? (hallo! wie geht's dir/ihnen?) |
| 1 | baie goed, dankie | [bajə xuˑt daŋki] | heel goed, dank je | very well, thank you | sehr gut, danke |
| 2 | praat jy afrikaans? | [prɑˑt jəi afrikɑˑs] | spreek/praat je/jij afrikaans? | do you speak afrikaans? | sprichst du afrikaans? |
| 3 | praat jy engels? | [prɑˑt jəi ɛŋəls] | spreek/praat je/jij engels? | do you speak english? | sprichst du englisch? |
| 4 | ja | [jɑˑ] | ja | yes | ja |
| 5 | nee | [neˑə] | nee | no | nein |
| 6 | 'n bietjie | [ə biki] | een beetje | a bit | ein bisschen |
| 7 | wat is jou naam? | [vat əs jəu nɑˑm] | hoe heet je? / wat is jouw naam? | what is your name? | wie heißt du? / wie ist dein name? |
| 8 | die kinders praat afrikaans | [di kənərs prɑˑt afrikɑˑns] | de kinderen spreken/praten afrikaans | the children speak afrikaans | die kinder sprechen afrikaans |
| 9 | ek is lief vir jou. less common: ek het jou lief | [æk əs lif vɯr jəʊ] | ik hou van je/jou. common in southern dutch: ik heb je/jou/u lief | i love you | ich liebe dich. also: ich habe dich lieb. (colloquial; virtually no romantic connotation) | | | | english |
|---:|:----------|
| 0 | yes | | [
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select count ( service ) where comparison with 2011/12 (£million) > 0 col : service | 2012/13 total cost (£million) | comparison with 2011/12 (£million) row 1 : bbc radio 1 | 54.2 | + 3.6 row 2 : bbc radio 1xtra | 11.8 | + 0.7 row 3 : bbc radio 2 | 62.1 | + 1.6 row 4 : bbc radio 3 | 54.3 | + 1.8 row 5 : bbc radio 4 | 122.1 | + 6.2 row 6 : bbc radio 4 extra | 7.2 | - 1 row 7 : bbc radio 5 live | 76.0 | + 6.7 row 8 : bbc radio 5 live sports extra | 5.6 | + 0.3 row 9 : bbc radio 6 music | 11.5 | - 0.2 row 10 : bbc asian network | 13.0 | 0 row 11 : bbc local radio | 152.5 | + 6 row 12 : bbc radio scotland | 32.7 | + 0.6 row 13 : bbc radio nan gaidheal | 6.3 | + 0.3 row 14 : bbc radio wales | 18.8 | + 1.1 row 15 : bbc radio cymru | 17.6 | + 1.7 row 16 : bbc radio ulster and bbc radio foyle | 23.8 | 0 | col : count ( "service" ) row 1 : 0 | select count ( service ) where comparison with 2011/12 (£million) > 0 <table_name> : table \begin{tabular}{llll}
\toprule
& service & 2012/13 total cost (£million) & comparison with 2011/12 (£million) \\
\midrule
0 & bbc radio 1 & 54.2 & + 3.6 \\
1 & bbc radio 1xtra & 11.8 & + 0.7 \\
2 & bbc radio 2 & 62.1 & + 1.6 \\
3 & bbc radio 3 & 54.3 & + 1.8 \\
4 & bbc radio 4 & 122.1 & + 6.2 \\
5 & bbc radio 4 extra & 7.2 & - 1 \\
6 & bbc radio 5 live & 76.0 & + 6.7 \\
7 & bbc radio 5 live sports extra & 5.6 & + 0.3 \\
8 & bbc radio 6 music & 11.5 & - 0.2 \\
9 & bbc asian network & 13.0 & 0 \\
10 & bbc local radio & 152.5 & + 6 \\
11 & bbc radio scotland & 32.7 & + 0.6 \\
12 & bbc radio nan gaidheal & 6.3 & + 0.3 \\
13 & bbc radio wales & 18.8 & + 1.1 \\
14 & bbc radio cymru & 17.6 & + 1.7 \\
15 & bbc radio ulster and bbc radio foyle & 23.8 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "service" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( service ) where comparison with 2011/12 (£million) > 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>service</th>
<th>2012/13 total cost (£million)</th>
<th>comparison with 2011/12 (£million)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>bbc radio 1</td>
<td>54.2</td>
<td>+ 3.6</td>
</tr>
<tr>
<th>1</th>
<td>bbc radio 1xtra</td>
<td>11.8</td>
<td>+ 0.7</td>
</tr>
<tr>
<th>2</th>
<td>bbc radio 2</td>
<td>62.1</td>
<td>+ 1.6</td>
</tr>
<tr>
<th>3</th>
<td>bbc radio 3</td>
<td>54.3</td>
<td>+ 1.8</td>
</tr>
<tr>
<th>4</th>
<td>bbc radio 4</td>
<td>122.1</td>
<td>+ 6.2</td>
</tr>
<tr>
<th>5</th>
<td>bbc radio 4 extra</td>
<td>7.2</td>
<td>- 1</td>
</tr>
<tr>
<th>6</th>
<td>bbc radio 5 live</td>
<td>76.0</td>
<td>+ 6.7</td>
</tr>
<tr>
<th>7</th>
<td>bbc radio 5 live sports extra</td>
<td>5.6</td>
<td>+ 0.3</td>
</tr>
<tr>
<th>8</th>
<td>bbc radio 6 music</td>
<td>11.5</td>
<td>- 0.2</td>
</tr>
<tr>
<th>9</th>
<td>bbc asian network</td>
<td>13.0</td>
<td>0</td>
</tr>
<tr>
<th>10</th>
<td>bbc local radio</td>
<td>152.5</td>
<td>+ 6</td>
</tr>
<tr>
<th>11</th>
<td>bbc radio scotland</td>
<td>32.7</td>
<td>+ 0.6</td>
</tr>
<tr>
<th>12</th>
<td>bbc radio nan gaidheal</td>
<td>6.3</td>
<td>+ 0.3</td>
</tr>
<tr>
<th>13</th>
<td>bbc radio wales</td>
<td>18.8</td>
<td>+ 1.1</td>
</tr>
<tr>
<th>14</th>
<td>bbc radio cymru</td>
<td>17.6</td>
<td>+ 1.7</td>
</tr>
<tr>
<th>15</th>
<td>bbc radio ulster and bbc radio foyle</td>
<td>23.8</td>
<td>0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "service" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( service ) where comparison with 2011/12 (£million) > 0 <table_name> : table | | service | 2012/13 total cost (£million) | comparison with 2011/12 (£million) |
|---:|:-------------------------------------|--------------------------------:|:-------------------------------------|
| 0 | bbc radio 1 | 54.2 | + 3.6 |
| 1 | bbc radio 1xtra | 11.8 | + 0.7 |
| 2 | bbc radio 2 | 62.1 | + 1.6 |
| 3 | bbc radio 3 | 54.3 | + 1.8 |
| 4 | bbc radio 4 | 122.1 | + 6.2 |
| 5 | bbc radio 4 extra | 7.2 | - 1 |
| 6 | bbc radio 5 live | 76 | + 6.7 |
| 7 | bbc radio 5 live sports extra | 5.6 | + 0.3 |
| 8 | bbc radio 6 music | 11.5 | - 0.2 |
| 9 | bbc asian network | 13 | 0 |
| 10 | bbc local radio | 152.5 | + 6 |
| 11 | bbc radio scotland | 32.7 | + 0.6 |
| 12 | bbc radio nan gaidheal | 6.3 | + 0.3 |
| 13 | bbc radio wales | 18.8 | + 1.1 |
| 14 | bbc radio cymru | 17.6 | + 1.7 |
| 15 | bbc radio ulster and bbc radio foyle | 23.8 | 0 | | | | count ( "service" ) |
|---:|----------------------:|
| 0 | 0 | | [
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select count ( bank ) where foundation = 425 col : bank | foundation | # of branches as of 30 september 2012 | total assets (million tl) as of 30 september 2012 row 1 : turkiye is bankası | 1924 | 1294 | 210535 row 2 : ziraat bankası | 1863 | 1510 | 207871 row 3 : garanti bank | 1946 | 947 | 154550 row 4 : akbank | 1948 | 963 | 150241 row 5 : yapı ve kredi bankası | 1944 | 949 | 160309 row 6 : halk bankası | 1938 | 807 | 116372 row 7 : vakıfbank | 1954 | 741 | 135578 row 8 : finansbank | 1987 | 530 | 49902 row 9 : turk ekonomi bankası | 1927 | 510 | 42505 row 10 : denizbank | 1997 | 624 | 40457 row 11 : hsbc bank | 1990 | 331 | 25797 row 12 : ing bank | 1984 | 320 | 23184 row 13 : turk eximbank | 1987 | 2 | 14724 row 14 : sekerbank | 1953 | 272 | 14656 row 15 : iller bankası | 1933 | 19 | 12309 row 16 : turkiye sınai kalkınma bankası | 1950 | 4 | 9929 row 17 : alternatif bank | 1992 | 63 | 7904 row 18 : citibank | 1980 | 37 | 7884 row 19 : anadolubank | 1996 | 88 | 7218 row 20 : burgan bank | 1992 | 60 | 4275 row 21 : imkb takas ve saklama bankası | 1995 | 1 | 3587 row 22 : tekstilbank | 1986 | 44 | 3502 row 23 : deutsche bank | 1988 | 1 | 3426 row 24 : fibabanka | 1984 | 27 | 3120 row 25 : aktif yatırım bankası | 1999 | 7 | 2997 row 26 : the royal bank of scotland | 1921 | 3 | 2750 row 27 : turkiye kalkınma bankası | 1975 | 1 | 2651 row 28 : turkland bank | 1991 | 27 | 2649 row 29 : arap turk bankası | 1977 | 7 | 2147 row 30 : merrill lynch | 1992 | 1 | 1898 row 31 : bankpozitif | 1999 | 1 | 1788 row 32 : societe generale | 1989 | 16 | 1457 row 33 : turkish bank | 1982 | 20 | 837 row 34 : jpmorgan chase | 1984 | 1 | 830 row 35 : birlesik fon bankası | 1958 | 1 | 801 row 36 : bank mellat | 1982 | 3 | 729 row 37 : portigon | 1985 | 1 | 279 row 38 : nurol yatırım bankası | 1999 | 2 | 227 row 39 : diler yatırım bankası | 1998 | 1 | 108 row 40 : gsd yatırım bankası | 1998 | 1 | 108 row 41 : habib bank limited | 1983 | 1 | 80 row 42 : credit agricole | 1990 | 1 | 72 row 43 : adabank | 1985 | 1 | 51 row 44 : taib yatırım bank | 1987 | 1 | 18 | col : count ( "bank" ) row 1 : 0 | select count ( bank ) where foundation = 425 <table_name> : table \begin{tabular}{lllll}
\toprule
& bank & foundation & # of branches as of 30 september 2012 & total assets (million tl) as of 30 september 2012 \\
\midrule
0 & turkiye is bankası & 1924 & 1294 & 210535 \\
1 & ziraat bankası & 1863 & 1510 & 207871 \\
2 & garanti bank & 1946 & 947 & 154550 \\
3 & akbank & 1948 & 963 & 150241 \\
4 & yapı ve kredi bankası & 1944 & 949 & 160309 \\
5 & halk bankası & 1938 & 807 & 116372 \\
6 & vakıfbank & 1954 & 741 & 135578 \\
7 & finansbank & 1987 & 530 & 49902 \\
8 & turk ekonomi bankası & 1927 & 510 & 42505 \\
9 & denizbank & 1997 & 624 & 40457 \\
10 & hsbc bank & 1990 & 331 & 25797 \\
11 & ing bank & 1984 & 320 & 23184 \\
12 & turk eximbank & 1987 & 2 & 14724 \\
13 & sekerbank & 1953 & 272 & 14656 \\
14 & iller bankası & 1933 & 19 & 12309 \\
15 & turkiye sınai kalkınma bankası & 1950 & 4 & 9929 \\
16 & alternatif bank & 1992 & 63 & 7904 \\
17 & citibank & 1980 & 37 & 7884 \\
18 & anadolubank & 1996 & 88 & 7218 \\
19 & burgan bank & 1992 & 60 & 4275 \\
20 & imkb takas ve saklama bankası & 1995 & 1 & 3587 \\
21 & tekstilbank & 1986 & 44 & 3502 \\
22 & deutsche bank & 1988 & 1 & 3426 \\
23 & fibabanka & 1984 & 27 & 3120 \\
24 & aktif yatırım bankası & 1999 & 7 & 2997 \\
25 & the royal bank of scotland & 1921 & 3 & 2750 \\
26 & turkiye kalkınma bankası & 1975 & 1 & 2651 \\
27 & turkland bank & 1991 & 27 & 2649 \\
28 & arap turk bankası & 1977 & 7 & 2147 \\
29 & merrill lynch & 1992 & 1 & 1898 \\
30 & bankpozitif & 1999 & 1 & 1788 \\
31 & societe generale & 1989 & 16 & 1457 \\
32 & turkish bank & 1982 & 20 & 837 \\
33 & jpmorgan chase & 1984 & 1 & 830 \\
34 & birlesik fon bankası & 1958 & 1 & 801 \\
35 & bank mellat & 1982 & 3 & 729 \\
36 & portigon & 1985 & 1 & 279 \\
37 & nurol yatırım bankası & 1999 & 2 & 227 \\
38 & diler yatırım bankası & 1998 & 1 & 108 \\
39 & gsd yatırım bankası & 1998 & 1 & 108 \\
40 & habib bank limited & 1983 & 1 & 80 \\
41 & credit agricole & 1990 & 1 & 72 \\
42 & adabank & 1985 & 1 & 51 \\
43 & taib yatırım bank & 1987 & 1 & 18 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "bank" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( bank ) where foundation = 425 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>bank</th>
<th>foundation</th>
<th># of branches as of 30 september 2012</th>
<th>total assets (million tl) as of 30 september 2012</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>turkiye is bankası</td>
<td>1924</td>
<td>1294</td>
<td>210535</td>
</tr>
<tr>
<th>1</th>
<td>ziraat bankası</td>
<td>1863</td>
<td>1510</td>
<td>207871</td>
</tr>
<tr>
<th>2</th>
<td>garanti bank</td>
<td>1946</td>
<td>947</td>
<td>154550</td>
</tr>
<tr>
<th>3</th>
<td>akbank</td>
<td>1948</td>
<td>963</td>
<td>150241</td>
</tr>
<tr>
<th>4</th>
<td>yapı ve kredi bankası</td>
<td>1944</td>
<td>949</td>
<td>160309</td>
</tr>
<tr>
<th>5</th>
<td>halk bankası</td>
<td>1938</td>
<td>807</td>
<td>116372</td>
</tr>
<tr>
<th>6</th>
<td>vakıfbank</td>
<td>1954</td>
<td>741</td>
<td>135578</td>
</tr>
<tr>
<th>7</th>
<td>finansbank</td>
<td>1987</td>
<td>530</td>
<td>49902</td>
</tr>
<tr>
<th>8</th>
<td>turk ekonomi bankası</td>
<td>1927</td>
<td>510</td>
<td>42505</td>
</tr>
<tr>
<th>9</th>
<td>denizbank</td>
<td>1997</td>
<td>624</td>
<td>40457</td>
</tr>
<tr>
<th>10</th>
<td>hsbc bank</td>
<td>1990</td>
<td>331</td>
<td>25797</td>
</tr>
<tr>
<th>11</th>
<td>ing bank</td>
<td>1984</td>
<td>320</td>
<td>23184</td>
</tr>
<tr>
<th>12</th>
<td>turk eximbank</td>
<td>1987</td>
<td>2</td>
<td>14724</td>
</tr>
<tr>
<th>13</th>
<td>sekerbank</td>
<td>1953</td>
<td>272</td>
<td>14656</td>
</tr>
<tr>
<th>14</th>
<td>iller bankası</td>
<td>1933</td>
<td>19</td>
<td>12309</td>
</tr>
<tr>
<th>15</th>
<td>turkiye sınai kalkınma bankası</td>
<td>1950</td>
<td>4</td>
<td>9929</td>
</tr>
<tr>
<th>16</th>
<td>alternatif bank</td>
<td>1992</td>
<td>63</td>
<td>7904</td>
</tr>
<tr>
<th>17</th>
<td>citibank</td>
<td>1980</td>
<td>37</td>
<td>7884</td>
</tr>
<tr>
<th>18</th>
<td>anadolubank</td>
<td>1996</td>
<td>88</td>
<td>7218</td>
</tr>
<tr>
<th>19</th>
<td>burgan bank</td>
<td>1992</td>
<td>60</td>
<td>4275</td>
</tr>
<tr>
<th>20</th>
<td>imkb takas ve saklama bankası</td>
<td>1995</td>
<td>1</td>
<td>3587</td>
</tr>
<tr>
<th>21</th>
<td>tekstilbank</td>
<td>1986</td>
<td>44</td>
<td>3502</td>
</tr>
<tr>
<th>22</th>
<td>deutsche bank</td>
<td>1988</td>
<td>1</td>
<td>3426</td>
</tr>
<tr>
<th>23</th>
<td>fibabanka</td>
<td>1984</td>
<td>27</td>
<td>3120</td>
</tr>
<tr>
<th>24</th>
<td>aktif yatırım bankası</td>
<td>1999</td>
<td>7</td>
<td>2997</td>
</tr>
<tr>
<th>25</th>
<td>the royal bank of scotland</td>
<td>1921</td>
<td>3</td>
<td>2750</td>
</tr>
<tr>
<th>26</th>
<td>turkiye kalkınma bankası</td>
<td>1975</td>
<td>1</td>
<td>2651</td>
</tr>
<tr>
<th>27</th>
<td>turkland bank</td>
<td>1991</td>
<td>27</td>
<td>2649</td>
</tr>
<tr>
<th>28</th>
<td>arap turk bankası</td>
<td>1977</td>
<td>7</td>
<td>2147</td>
</tr>
<tr>
<th>29</th>
<td>merrill lynch</td>
<td>1992</td>
<td>1</td>
<td>1898</td>
</tr>
<tr>
<th>30</th>
<td>bankpozitif</td>
<td>1999</td>
<td>1</td>
<td>1788</td>
</tr>
<tr>
<th>31</th>
<td>societe generale</td>
<td>1989</td>
<td>16</td>
<td>1457</td>
</tr>
<tr>
<th>32</th>
<td>turkish bank</td>
<td>1982</td>
<td>20</td>
<td>837</td>
</tr>
<tr>
<th>33</th>
<td>jpmorgan chase</td>
<td>1984</td>
<td>1</td>
<td>830</td>
</tr>
<tr>
<th>34</th>
<td>birlesik fon bankası</td>
<td>1958</td>
<td>1</td>
<td>801</td>
</tr>
<tr>
<th>35</th>
<td>bank mellat</td>
<td>1982</td>
<td>3</td>
<td>729</td>
</tr>
<tr>
<th>36</th>
<td>portigon</td>
<td>1985</td>
<td>1</td>
<td>279</td>
</tr>
<tr>
<th>37</th>
<td>nurol yatırım bankası</td>
<td>1999</td>
<td>2</td>
<td>227</td>
</tr>
<tr>
<th>38</th>
<td>diler yatırım bankası</td>
<td>1998</td>
<td>1</td>
<td>108</td>
</tr>
<tr>
<th>39</th>
<td>gsd yatırım bankası</td>
<td>1998</td>
<td>1</td>
<td>108</td>
</tr>
<tr>
<th>40</th>
<td>habib bank limited</td>
<td>1983</td>
<td>1</td>
<td>80</td>
</tr>
<tr>
<th>41</th>
<td>credit agricole</td>
<td>1990</td>
<td>1</td>
<td>72</td>
</tr>
<tr>
<th>42</th>
<td>adabank</td>
<td>1985</td>
<td>1</td>
<td>51</td>
</tr>
<tr>
<th>43</th>
<td>taib yatırım bank</td>
<td>1987</td>
<td>1</td>
<td>18</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "bank" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( bank ) where foundation = 425 <table_name> : table | | bank | foundation | # of branches as of 30 september 2012 | total assets (million tl) as of 30 september 2012 |
|---:|:-------------------------------|-------------:|----------------------------------------:|----------------------------------------------------:|
| 0 | turkiye is bankası | 1924 | 1294 | 210535 |
| 1 | ziraat bankası | 1863 | 1510 | 207871 |
| 2 | garanti bank | 1946 | 947 | 154550 |
| 3 | akbank | 1948 | 963 | 150241 |
| 4 | yapı ve kredi bankası | 1944 | 949 | 160309 |
| 5 | halk bankası | 1938 | 807 | 116372 |
| 6 | vakıfbank | 1954 | 741 | 135578 |
| 7 | finansbank | 1987 | 530 | 49902 |
| 8 | turk ekonomi bankası | 1927 | 510 | 42505 |
| 9 | denizbank | 1997 | 624 | 40457 |
| 10 | hsbc bank | 1990 | 331 | 25797 |
| 11 | ing bank | 1984 | 320 | 23184 |
| 12 | turk eximbank | 1987 | 2 | 14724 |
| 13 | sekerbank | 1953 | 272 | 14656 |
| 14 | iller bankası | 1933 | 19 | 12309 |
| 15 | turkiye sınai kalkınma bankası | 1950 | 4 | 9929 |
| 16 | alternatif bank | 1992 | 63 | 7904 |
| 17 | citibank | 1980 | 37 | 7884 |
| 18 | anadolubank | 1996 | 88 | 7218 |
| 19 | burgan bank | 1992 | 60 | 4275 |
| 20 | imkb takas ve saklama bankası | 1995 | 1 | 3587 |
| 21 | tekstilbank | 1986 | 44 | 3502 |
| 22 | deutsche bank | 1988 | 1 | 3426 |
| 23 | fibabanka | 1984 | 27 | 3120 |
| 24 | aktif yatırım bankası | 1999 | 7 | 2997 |
| 25 | the royal bank of scotland | 1921 | 3 | 2750 |
| 26 | turkiye kalkınma bankası | 1975 | 1 | 2651 |
| 27 | turkland bank | 1991 | 27 | 2649 |
| 28 | arap turk bankası | 1977 | 7 | 2147 |
| 29 | merrill lynch | 1992 | 1 | 1898 |
| 30 | bankpozitif | 1999 | 1 | 1788 |
| 31 | societe generale | 1989 | 16 | 1457 |
| 32 | turkish bank | 1982 | 20 | 837 |
| 33 | jpmorgan chase | 1984 | 1 | 830 |
| 34 | birlesik fon bankası | 1958 | 1 | 801 |
| 35 | bank mellat | 1982 | 3 | 729 |
| 36 | portigon | 1985 | 1 | 279 |
| 37 | nurol yatırım bankası | 1999 | 2 | 227 |
| 38 | diler yatırım bankası | 1998 | 1 | 108 |
| 39 | gsd yatırım bankası | 1998 | 1 | 108 |
| 40 | habib bank limited | 1983 | 1 | 80 |
| 41 | credit agricole | 1990 | 1 | 72 |
| 42 | adabank | 1985 | 1 | 51 |
| 43 | taib yatırım bank | 1987 | 1 | 18 | | | | count ( "bank" ) |
|---:|-------------------:|
| 0 | 0 | | [
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select rank where rank = '#1' col : season | episodes | time slot (est) | original airing season premiere | original airing season finale | original airing tv season | rank | viewers (in millions) row 1 : 1 | 23 | friday 9pm/8c (october 6, 2000 - january 12, 2001) thursday 9pm/8c (february 1, 2001 - may 17, 2001) | october 6, 2000 | may 17, 2001 | 2000-2001 | #10 | 17.8 row 2 : 2 | 23 | thursday 9pm/8c | september 27, 2001 | may 16, 2002 | 2001-2002 | #2 | 23.69 row 3 : 3 | 23 | thursday 9pm/8c | september 26, 2002 | may 15, 2003 | 2002-2003 | #1 | 26.2 row 4 : 4 | 23 | thursday 9pm/8c | september 25, 2003 | may 20, 2004 | 2003-2004 | #2 | 25.27 row 5 : 5 | 25 | thursday 9pm/8c | september 23, 2004 | may 19, 2005 | 2004-2005 | #2 | 26.26 row 6 : 6 | 24 | thursday 9pm/8c | september 22, 2005 | may 18, 2006 | 2005-2006 | #3 | 24.86 row 7 : 7 | 24 | thursday 9pm/8c | september 21, 2006 | may 17, 2007 | 2006-2007 | #4 | 20.34 row 8 : 8 | 17 | thursday 9pm/8c | september 27, 2007 | may 15, 2008 | 2007-2008 | #9 | 16.62 row 9 : 9 | 24 | thursday 9pm/8c | october 9, 2008 | may 14, 2009 | 2008-2009 | #4 | 18.52 row 10 : 10 | 23 | thursday 9pm/8c | september 24, 2009 | may 20, 2010 | 2009-2010 | #12 | 14.92 row 11 : 11 | 22 | thursday 9pm/8c | september 23, 2010 | may 12, 2011 | 2010-2011 | #12 | 13.52 row 12 : 12 | 22 | wednesday 10pm/9c | september 21, 2011 | may 9, 2012 | 2011-2012 | #21 | 12.49 row 13 : 13 | 22 | wednesday 10pm/9c | september 26, 2012 | may 15, 2013 | 2012-2013 | #25 | 11.63 | col : rank row 1 : #1 | select rank where rank = '#1' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& season & episodes & time slot (est) & original airing season premiere & original airing season finale & original airing tv season & rank & viewers (in millions) \\
\midrule
0 & 1 & 23 & friday 9pm/8c (october 6, 2000 - january 12, 2001) thursday 9pm/8c (february 1, 2001 - may 17, 2001) & october 6, 2000 & may 17, 2001 & 2000-2001 & #10 & 17.8 \\
1 & 2 & 23 & thursday 9pm/8c & september 27, 2001 & may 16, 2002 & 2001-2002 & #2 & 23.69 \\
2 & 3 & 23 & thursday 9pm/8c & september 26, 2002 & may 15, 2003 & 2002-2003 & #1 & 26.2 \\
3 & 4 & 23 & thursday 9pm/8c & september 25, 2003 & may 20, 2004 & 2003-2004 & #2 & 25.27 \\
4 & 5 & 25 & thursday 9pm/8c & september 23, 2004 & may 19, 2005 & 2004-2005 & #2 & 26.26 \\
5 & 6 & 24 & thursday 9pm/8c & september 22, 2005 & may 18, 2006 & 2005-2006 & #3 & 24.86 \\
6 & 7 & 24 & thursday 9pm/8c & september 21, 2006 & may 17, 2007 & 2006-2007 & #4 & 20.34 \\
7 & 8 & 17 & thursday 9pm/8c & september 27, 2007 & may 15, 2008 & 2007-2008 & #9 & 16.62 \\
8 & 9 & 24 & thursday 9pm/8c & october 9, 2008 & may 14, 2009 & 2008-2009 & #4 & 18.52 \\
9 & 10 & 23 & thursday 9pm/8c & september 24, 2009 & may 20, 2010 & 2009-2010 & #12 & 14.92 \\
10 & 11 & 22 & thursday 9pm/8c & september 23, 2010 & may 12, 2011 & 2010-2011 & #12 & 13.52 \\
11 & 12 & 22 & wednesday 10pm/9c & september 21, 2011 & may 9, 2012 & 2011-2012 & #21 & 12.49 \\
12 & 13 & 22 & wednesday 10pm/9c & september 26, 2012 & may 15, 2013 & 2012-2013 & #25 & 11.63 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& rank \\
\midrule
0 & #1 \\
\bottomrule
\end{tabular}
| select rank where rank = '#1' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>episodes</th>
<th>time slot (est)</th>
<th>original airing season premiere</th>
<th>original airing season finale</th>
<th>original airing tv season</th>
<th>rank</th>
<th>viewers (in millions)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>23</td>
<td>friday 9pm/8c (october 6, 2000 - january 12, 2001) thursday 9pm/8c (february 1, 2001 - may 17, 2001)</td>
<td>october 6, 2000</td>
<td>may 17, 2001</td>
<td>2000-2001</td>
<td>#10</td>
<td>17.8</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>23</td>
<td>thursday 9pm/8c</td>
<td>september 27, 2001</td>
<td>may 16, 2002</td>
<td>2001-2002</td>
<td>#2</td>
<td>23.69</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>23</td>
<td>thursday 9pm/8c</td>
<td>september 26, 2002</td>
<td>may 15, 2003</td>
<td>2002-2003</td>
<td>#1</td>
<td>26.2</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>23</td>
<td>thursday 9pm/8c</td>
<td>september 25, 2003</td>
<td>may 20, 2004</td>
<td>2003-2004</td>
<td>#2</td>
<td>25.27</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>25</td>
<td>thursday 9pm/8c</td>
<td>september 23, 2004</td>
<td>may 19, 2005</td>
<td>2004-2005</td>
<td>#2</td>
<td>26.26</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>24</td>
<td>thursday 9pm/8c</td>
<td>september 22, 2005</td>
<td>may 18, 2006</td>
<td>2005-2006</td>
<td>#3</td>
<td>24.86</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>24</td>
<td>thursday 9pm/8c</td>
<td>september 21, 2006</td>
<td>may 17, 2007</td>
<td>2006-2007</td>
<td>#4</td>
<td>20.34</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>17</td>
<td>thursday 9pm/8c</td>
<td>september 27, 2007</td>
<td>may 15, 2008</td>
<td>2007-2008</td>
<td>#9</td>
<td>16.62</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>24</td>
<td>thursday 9pm/8c</td>
<td>october 9, 2008</td>
<td>may 14, 2009</td>
<td>2008-2009</td>
<td>#4</td>
<td>18.52</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>23</td>
<td>thursday 9pm/8c</td>
<td>september 24, 2009</td>
<td>may 20, 2010</td>
<td>2009-2010</td>
<td>#12</td>
<td>14.92</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>22</td>
<td>thursday 9pm/8c</td>
<td>september 23, 2010</td>
<td>may 12, 2011</td>
<td>2010-2011</td>
<td>#12</td>
<td>13.52</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>22</td>
<td>wednesday 10pm/9c</td>
<td>september 21, 2011</td>
<td>may 9, 2012</td>
<td>2011-2012</td>
<td>#21</td>
<td>12.49</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>22</td>
<td>wednesday 10pm/9c</td>
<td>september 26, 2012</td>
<td>may 15, 2013</td>
<td>2012-2013</td>
<td>#25</td>
<td>11.63</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>#1</td>
</tr>
</tbody>
</table> | select rank where rank = '#1' <table_name> : table | | season | episodes | time slot (est) | original airing season premiere | original airing season finale | original airing tv season | rank | viewers (in millions) |
|---:|---------:|-----------:|:-----------------------------------------------------------------------------------------------------|:----------------------------------|:--------------------------------|:----------------------------|:-------|------------------------:|
| 0 | 1 | 23 | friday 9pm/8c (october 6, 2000 - january 12, 2001) thursday 9pm/8c (february 1, 2001 - may 17, 2001) | october 6, 2000 | may 17, 2001 | 2000-2001 | #10 | 17.8 |
| 1 | 2 | 23 | thursday 9pm/8c | september 27, 2001 | may 16, 2002 | 2001-2002 | #2 | 23.69 |
| 2 | 3 | 23 | thursday 9pm/8c | september 26, 2002 | may 15, 2003 | 2002-2003 | #1 | 26.2 |
| 3 | 4 | 23 | thursday 9pm/8c | september 25, 2003 | may 20, 2004 | 2003-2004 | #2 | 25.27 |
| 4 | 5 | 25 | thursday 9pm/8c | september 23, 2004 | may 19, 2005 | 2004-2005 | #2 | 26.26 |
| 5 | 6 | 24 | thursday 9pm/8c | september 22, 2005 | may 18, 2006 | 2005-2006 | #3 | 24.86 |
| 6 | 7 | 24 | thursday 9pm/8c | september 21, 2006 | may 17, 2007 | 2006-2007 | #4 | 20.34 |
| 7 | 8 | 17 | thursday 9pm/8c | september 27, 2007 | may 15, 2008 | 2007-2008 | #9 | 16.62 |
| 8 | 9 | 24 | thursday 9pm/8c | october 9, 2008 | may 14, 2009 | 2008-2009 | #4 | 18.52 |
| 9 | 10 | 23 | thursday 9pm/8c | september 24, 2009 | may 20, 2010 | 2009-2010 | #12 | 14.92 |
| 10 | 11 | 22 | thursday 9pm/8c | september 23, 2010 | may 12, 2011 | 2010-2011 | #12 | 13.52 |
| 11 | 12 | 22 | wednesday 10pm/9c | september 21, 2011 | may 9, 2012 | 2011-2012 | #21 | 12.49 |
| 12 | 13 | 22 | wednesday 10pm/9c | september 26, 2012 | may 15, 2013 | 2012-2013 | #25 | 11.63 | | | | rank |
|---:|:-------|
| 0 | #1 | | [
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select women's division where state/territory men's division = 'new south wales' col : year | state/territory men's division | state/territory women's division | major centres division | community division | women's division row 1 : 2012 | queensland | new south wales | none | none | none row 2 : 2012 | new south wales | new south wales | darwin | brothers in arms | bush potatoes row 3 : 2011 | new south wales | new south wales | maranoa murris | gap angels | bush potatoes row 4 : 2010 | western australia | none | none | none | none row 5 : 2009 | queensland | none | alkupitja | tangentyere | new south wales row 6 : 2008 | queensland | none | katherine | cooktown | new south wales row 7 : 2007 | new south wales | none | alkupitja | cat tigers | cga cougars row 8 : 2006 | queensland | none | alice springs | melville island | darwin row 9 : 2005 | queensland | none | alice springs | alkupitja | darwin row 10 : 2004 | queensland | none | alice springs | normanton | tennant creek row 11 : 2003 | new south wales | none | darwin | none | none row 12 : 2002 | northern territory | none | darwin | none | none row 13 : 2001 | tasmania | none | none | none | none | col : women's division row 1 : bush potatoes row 2 : bush potatoes row 3 : cga cougars row 4 : none | select women's division where state/territory men's division = 'new south wales' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & state/territory men's division & state/territory women's division & major centres division & community division & women's division \\
\midrule
0 & 2012 & queensland & new south wales & none & none & none \\
1 & 2012 & new south wales & new south wales & darwin & brothers in arms & bush potatoes \\
2 & 2011 & new south wales & new south wales & maranoa murris & gap angels & bush potatoes \\
3 & 2010 & western australia & none & none & none & none \\
4 & 2009 & queensland & none & alkupitja & tangentyere & new south wales \\
5 & 2008 & queensland & none & katherine & cooktown & new south wales \\
6 & 2007 & new south wales & none & alkupitja & cat tigers & cga cougars \\
7 & 2006 & queensland & none & alice springs & melville island & darwin \\
8 & 2005 & queensland & none & alice springs & alkupitja & darwin \\
9 & 2004 & queensland & none & alice springs & normanton & tennant creek \\
10 & 2003 & new south wales & none & darwin & none & none \\
11 & 2002 & northern territory & none & darwin & none & none \\
12 & 2001 & tasmania & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& women's division \\
\midrule
0 & bush potatoes \\
1 & bush potatoes \\
2 & cga cougars \\
3 & none \\
\bottomrule
\end{tabular}
| select women's division where state/territory men's division = 'new south wales' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>state/territory men's division</th>
<th>state/territory women's division</th>
<th>major centres division</th>
<th>community division</th>
<th>women's division</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2012</td>
<td>queensland</td>
<td>new south wales</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2012</td>
<td>new south wales</td>
<td>new south wales</td>
<td>darwin</td>
<td>brothers in arms</td>
<td>bush potatoes</td>
</tr>
<tr>
<th>2</th>
<td>2011</td>
<td>new south wales</td>
<td>new south wales</td>
<td>maranoa murris</td>
<td>gap angels</td>
<td>bush potatoes</td>
</tr>
<tr>
<th>3</th>
<td>2010</td>
<td>western australia</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2009</td>
<td>queensland</td>
<td>none</td>
<td>alkupitja</td>
<td>tangentyere</td>
<td>new south wales</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>queensland</td>
<td>none</td>
<td>katherine</td>
<td>cooktown</td>
<td>new south wales</td>
</tr>
<tr>
<th>6</th>
<td>2007</td>
<td>new south wales</td>
<td>none</td>
<td>alkupitja</td>
<td>cat tigers</td>
<td>cga cougars</td>
</tr>
<tr>
<th>7</th>
<td>2006</td>
<td>queensland</td>
<td>none</td>
<td>alice springs</td>
<td>melville island</td>
<td>darwin</td>
</tr>
<tr>
<th>8</th>
<td>2005</td>
<td>queensland</td>
<td>none</td>
<td>alice springs</td>
<td>alkupitja</td>
<td>darwin</td>
</tr>
<tr>
<th>9</th>
<td>2004</td>
<td>queensland</td>
<td>none</td>
<td>alice springs</td>
<td>normanton</td>
<td>tennant creek</td>
</tr>
<tr>
<th>10</th>
<td>2003</td>
<td>new south wales</td>
<td>none</td>
<td>darwin</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>2002</td>
<td>northern territory</td>
<td>none</td>
<td>darwin</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>2001</td>
<td>tasmania</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>women's division</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>bush potatoes</td>
</tr>
<tr>
<th>1</th>
<td>bush potatoes</td>
</tr>
<tr>
<th>2</th>
<td>cga cougars</td>
</tr>
<tr>
<th>3</th>
<td>none</td>
</tr>
</tbody>
</table> | select women's division where state/territory men's division = 'new south wales' <table_name> : table | | year | state/territory men's division | state/territory women's division | major centres division | community division | women's division |
|---:|-------:|:---------------------------------|:-----------------------------------|:-------------------------|:---------------------|:-------------------|
| 0 | 2012 | queensland | new south wales | none | none | none |
| 1 | 2012 | new south wales | new south wales | darwin | brothers in arms | bush potatoes |
| 2 | 2011 | new south wales | new south wales | maranoa murris | gap angels | bush potatoes |
| 3 | 2010 | western australia | none | none | none | none |
| 4 | 2009 | queensland | none | alkupitja | tangentyere | new south wales |
| 5 | 2008 | queensland | none | katherine | cooktown | new south wales |
| 6 | 2007 | new south wales | none | alkupitja | cat tigers | cga cougars |
| 7 | 2006 | queensland | none | alice springs | melville island | darwin |
| 8 | 2005 | queensland | none | alice springs | alkupitja | darwin |
| 9 | 2004 | queensland | none | alice springs | normanton | tennant creek |
| 10 | 2003 | new south wales | none | darwin | none | none |
| 11 | 2002 | northern territory | none | darwin | none | none |
| 12 | 2001 | tasmania | none | none | none | none | | | | women's division |
|---:|:-------------------|
| 0 | bush potatoes |
| 1 | bush potatoes |
| 2 | cga cougars |
| 3 | none | | [
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select count ( win % ) where played > 1 col : against | played | won | drawn | lost | win % row 1 : andorra | 3 | 3 | 0 | 0 | 100% row 2 : argentina | 4 | 0 | 0 | 4 | 0% row 3 : australia | 1 | 0 | 0 | 1 | 0% row 4 : australia emerging | 1 | 0 | 1 | 0 | 0% row 5 : belgium | 14 | 12 | 1 | 1 | 85.71% row 6 : barbarians | 1 | 0 | 0 | 1 | 0% row 7 : canada | 1 | 0 | 0 | 1 | 0% row 8 : chile | 4 | 2 | 0 | 2 | 50% row 9 : croatia | 2 | 1 | 1 | 0 | 50% row 10 : denmark | 1 | 1 | 0 | 0 | 100% row 11 : england a | 7 | 0 | 0 | 7 | 0% row 12 : england counties | 1 | 0 | 0 | 1 | 0% row 13 : royal air force rugby team | 4 | 0 | 2 | 2 | 0% row 14 : fiji | 1 | 0 | 0 | 1 | 0% row 15 : france | 24 | 0 | 0 | 24 | 0% row 16 : france a | 2 | 0 | 0 | 2 | 0% row 17 : france u | 2 | 1 | 0 | 1 | 50% row 18 : french protectorate of morocco | 4 | 1 | 1 | 2 | 25% row 19 : georgia | 12 | 3 | 1 | 8 | 25% row 20 : germany | 7 | 6 | 0 | 1 | 85.71% row 21 : hungary | 1 | 1 | 0 | 0 | 100% row 22 : italy | 27 | 3 | 1 | 23 | 11.11% row 23 : japan | 3 | 0 | 0 | 3 | 0% row 24 : moldova | 1 | 1 | 0 | 0 | 100% row 25 : morocco | 17 | 10 | 1 | 6 | 58.82% row 26 : namibia | 2 | 2 | 0 | 0 | 100% row 27 : netherlands | 13 | 12 | 1 | 0 | 92.31% row 28 : new zealand services | 2 | 0 | 0 | 2 | 0% row 29 : poland | 16 | 10 | 0 | 6 | 62.50% row 30 : portugal | 33 | 21 | 2 | 10 | 63.63% row 31 : czech republic | 8 | 2 | 0 | 6 | 75% row 32 : czechoslovakia | 5 | 2 | 1 | 2 | 40% row 33 : romania | 29 | 2 | 0 | 27 | 6.90% row 34 : russia | 16 | 2 | 0 | 14 | 12.50% row 35 : scotland | 8 | 0 | 0 | 8 | 0% row 36 : slovenia | 1 | 1 | 0 | 0 | 100% row 37 : south africa | 1 | 0 | 0 | 1 | 0% row 38 : south africa "a" | 1 | 0 | 0 | 1 | 0% row 39 : soviet union | 7 | 0 | 0 | 7 | 0% row 40 : sweden | 2 | 2 | 0 | 0 | 100% row 41 : switzerland | 1 | 1 | 0 | 0 | 100% row 42 : tunisia | 6 | 1 | 0 | 5 | 83.33% row 43 : ukraine | 2 | 2 | 0 | 0 | 100% row 44 : uruguay | 7 | 3 | 0 | 4 | 42.86% row 45 : united states | 3 | 0 | 0 | 3 | 0% row 46 : wales | 1 | 0 | 0 | 1 | 0% row 47 : wales a | 3 | 0 | 0 | 3 | 0% row 48 : west germany | 12 | 7 | 1 | 4 | 33.33% row 49 : yugoslavia | 4 | 4 | 0 | 0 | 100% row 50 : zimbabwe | 7 | 5 | 0 | 2 | 71.43% row 51 : total | 336 | 126 | 14 | 197 | 37.50% | col : count ( "win %" ) row 1 : 37 | select count ( win % ) where played > 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& against & played & won & drawn & lost & win % \\
\midrule
0 & andorra & 3 & 3 & 0 & 0 & 100% \\
1 & argentina & 4 & 0 & 0 & 4 & 0% \\
2 & australia & 1 & 0 & 0 & 1 & 0% \\
3 & australia emerging & 1 & 0 & 1 & 0 & 0% \\
4 & belgium & 14 & 12 & 1 & 1 & 85.71% \\
5 & barbarians & 1 & 0 & 0 & 1 & 0% \\
6 & canada & 1 & 0 & 0 & 1 & 0% \\
7 & chile & 4 & 2 & 0 & 2 & 50% \\
8 & croatia & 2 & 1 & 1 & 0 & 50% \\
9 & denmark & 1 & 1 & 0 & 0 & 100% \\
10 & england a & 7 & 0 & 0 & 7 & 0% \\
11 & england counties & 1 & 0 & 0 & 1 & 0% \\
12 & royal air force rugby team & 4 & 0 & 2 & 2 & 0% \\
13 & fiji & 1 & 0 & 0 & 1 & 0% \\
14 & france & 24 & 0 & 0 & 24 & 0% \\
15 & france a & 2 & 0 & 0 & 2 & 0% \\
16 & france u & 2 & 1 & 0 & 1 & 50% \\
17 & french protectorate of morocco & 4 & 1 & 1 & 2 & 25% \\
18 & georgia & 12 & 3 & 1 & 8 & 25% \\
19 & germany & 7 & 6 & 0 & 1 & 85.71% \\
20 & hungary & 1 & 1 & 0 & 0 & 100% \\
21 & italy & 27 & 3 & 1 & 23 & 11.11% \\
22 & japan & 3 & 0 & 0 & 3 & 0% \\
23 & moldova & 1 & 1 & 0 & 0 & 100% \\
24 & morocco & 17 & 10 & 1 & 6 & 58.82% \\
25 & namibia & 2 & 2 & 0 & 0 & 100% \\
26 & netherlands & 13 & 12 & 1 & 0 & 92.31% \\
27 & new zealand services & 2 & 0 & 0 & 2 & 0% \\
28 & poland & 16 & 10 & 0 & 6 & 62.50% \\
29 & portugal & 33 & 21 & 2 & 10 & 63.63% \\
30 & czech republic & 8 & 2 & 0 & 6 & 75% \\
31 & czechoslovakia & 5 & 2 & 1 & 2 & 40% \\
32 & romania & 29 & 2 & 0 & 27 & 6.90% \\
33 & russia & 16 & 2 & 0 & 14 & 12.50% \\
34 & scotland & 8 & 0 & 0 & 8 & 0% \\
35 & slovenia & 1 & 1 & 0 & 0 & 100% \\
36 & south africa & 1 & 0 & 0 & 1 & 0% \\
37 & south africa "a" & 1 & 0 & 0 & 1 & 0% \\
38 & soviet union & 7 & 0 & 0 & 7 & 0% \\
39 & sweden & 2 & 2 & 0 & 0 & 100% \\
40 & switzerland & 1 & 1 & 0 & 0 & 100% \\
41 & tunisia & 6 & 1 & 0 & 5 & 83.33% \\
42 & ukraine & 2 & 2 & 0 & 0 & 100% \\
43 & uruguay & 7 & 3 & 0 & 4 & 42.86% \\
44 & united states & 3 & 0 & 0 & 3 & 0% \\
45 & wales & 1 & 0 & 0 & 1 & 0% \\
46 & wales a & 3 & 0 & 0 & 3 & 0% \\
47 & west germany & 12 & 7 & 1 & 4 & 33.33% \\
48 & yugoslavia & 4 & 4 & 0 & 0 & 100% \\
49 & zimbabwe & 7 & 5 & 0 & 2 & 71.43% \\
50 & total & 336 & 126 & 14 & 197 & 37.50% \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "win %" ) \\
\midrule
0 & 37 \\
\bottomrule
\end{tabular}
| select count ( win % ) where played > 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>against</th>
<th>played</th>
<th>won</th>
<th>drawn</th>
<th>lost</th>
<th>win %</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>andorra</td>
<td>3</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>1</th>
<td>argentina</td>
<td>4</td>
<td>0</td>
<td>0</td>
<td>4</td>
<td>0%</td>
</tr>
<tr>
<th>2</th>
<td>australia</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0%</td>
</tr>
<tr>
<th>3</th>
<td>australia emerging</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>0%</td>
</tr>
<tr>
<th>4</th>
<td>belgium</td>
<td>14</td>
<td>12</td>
<td>1</td>
<td>1</td>
<td>85.71%</td>
</tr>
<tr>
<th>5</th>
<td>barbarians</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0%</td>
</tr>
<tr>
<th>6</th>
<td>canada</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0%</td>
</tr>
<tr>
<th>7</th>
<td>chile</td>
<td>4</td>
<td>2</td>
<td>0</td>
<td>2</td>
<td>50%</td>
</tr>
<tr>
<th>8</th>
<td>croatia</td>
<td>2</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>50%</td>
</tr>
<tr>
<th>9</th>
<td>denmark</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>10</th>
<td>england a</td>
<td>7</td>
<td>0</td>
<td>0</td>
<td>7</td>
<td>0%</td>
</tr>
<tr>
<th>11</th>
<td>england counties</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0%</td>
</tr>
<tr>
<th>12</th>
<td>royal air force rugby team</td>
<td>4</td>
<td>0</td>
<td>2</td>
<td>2</td>
<td>0%</td>
</tr>
<tr>
<th>13</th>
<td>fiji</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0%</td>
</tr>
<tr>
<th>14</th>
<td>france</td>
<td>24</td>
<td>0</td>
<td>0</td>
<td>24</td>
<td>0%</td>
</tr>
<tr>
<th>15</th>
<td>france a</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>0%</td>
</tr>
<tr>
<th>16</th>
<td>france u</td>
<td>2</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>50%</td>
</tr>
<tr>
<th>17</th>
<td>french protectorate of morocco</td>
<td>4</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>25%</td>
</tr>
<tr>
<th>18</th>
<td>georgia</td>
<td>12</td>
<td>3</td>
<td>1</td>
<td>8</td>
<td>25%</td>
</tr>
<tr>
<th>19</th>
<td>germany</td>
<td>7</td>
<td>6</td>
<td>0</td>
<td>1</td>
<td>85.71%</td>
</tr>
<tr>
<th>20</th>
<td>hungary</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>21</th>
<td>italy</td>
<td>27</td>
<td>3</td>
<td>1</td>
<td>23</td>
<td>11.11%</td>
</tr>
<tr>
<th>22</th>
<td>japan</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>0%</td>
</tr>
<tr>
<th>23</th>
<td>moldova</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>24</th>
<td>morocco</td>
<td>17</td>
<td>10</td>
<td>1</td>
<td>6</td>
<td>58.82%</td>
</tr>
<tr>
<th>25</th>
<td>namibia</td>
<td>2</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>26</th>
<td>netherlands</td>
<td>13</td>
<td>12</td>
<td>1</td>
<td>0</td>
<td>92.31%</td>
</tr>
<tr>
<th>27</th>
<td>new zealand services</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>0%</td>
</tr>
<tr>
<th>28</th>
<td>poland</td>
<td>16</td>
<td>10</td>
<td>0</td>
<td>6</td>
<td>62.50%</td>
</tr>
<tr>
<th>29</th>
<td>portugal</td>
<td>33</td>
<td>21</td>
<td>2</td>
<td>10</td>
<td>63.63%</td>
</tr>
<tr>
<th>30</th>
<td>czech republic</td>
<td>8</td>
<td>2</td>
<td>0</td>
<td>6</td>
<td>75%</td>
</tr>
<tr>
<th>31</th>
<td>czechoslovakia</td>
<td>5</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>40%</td>
</tr>
<tr>
<th>32</th>
<td>romania</td>
<td>29</td>
<td>2</td>
<td>0</td>
<td>27</td>
<td>6.90%</td>
</tr>
<tr>
<th>33</th>
<td>russia</td>
<td>16</td>
<td>2</td>
<td>0</td>
<td>14</td>
<td>12.50%</td>
</tr>
<tr>
<th>34</th>
<td>scotland</td>
<td>8</td>
<td>0</td>
<td>0</td>
<td>8</td>
<td>0%</td>
</tr>
<tr>
<th>35</th>
<td>slovenia</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>36</th>
<td>south africa</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0%</td>
</tr>
<tr>
<th>37</th>
<td>south africa "a"</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0%</td>
</tr>
<tr>
<th>38</th>
<td>soviet union</td>
<td>7</td>
<td>0</td>
<td>0</td>
<td>7</td>
<td>0%</td>
</tr>
<tr>
<th>39</th>
<td>sweden</td>
<td>2</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>40</th>
<td>switzerland</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>41</th>
<td>tunisia</td>
<td>6</td>
<td>1</td>
<td>0</td>
<td>5</td>
<td>83.33%</td>
</tr>
<tr>
<th>42</th>
<td>ukraine</td>
<td>2</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>43</th>
<td>uruguay</td>
<td>7</td>
<td>3</td>
<td>0</td>
<td>4</td>
<td>42.86%</td>
</tr>
<tr>
<th>44</th>
<td>united states</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>0%</td>
</tr>
<tr>
<th>45</th>
<td>wales</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>0%</td>
</tr>
<tr>
<th>46</th>
<td>wales a</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>0%</td>
</tr>
<tr>
<th>47</th>
<td>west germany</td>
<td>12</td>
<td>7</td>
<td>1</td>
<td>4</td>
<td>33.33%</td>
</tr>
<tr>
<th>48</th>
<td>yugoslavia</td>
<td>4</td>
<td>4</td>
<td>0</td>
<td>0</td>
<td>100%</td>
</tr>
<tr>
<th>49</th>
<td>zimbabwe</td>
<td>7</td>
<td>5</td>
<td>0</td>
<td>2</td>
<td>71.43%</td>
</tr>
<tr>
<th>50</th>
<td>total</td>
<td>336</td>
<td>126</td>
<td>14</td>
<td>197</td>
<td>37.50%</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "win %" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>37</td>
</tr>
</tbody>
</table> | select count ( win % ) where played > 1 <table_name> : table | | against | played | won | drawn | lost | win % |
|---:|:-------------------------------|---------:|------:|--------:|-------:|:--------|
| 0 | andorra | 3 | 3 | 0 | 0 | 100% |
| 1 | argentina | 4 | 0 | 0 | 4 | 0% |
| 2 | australia | 1 | 0 | 0 | 1 | 0% |
| 3 | australia emerging | 1 | 0 | 1 | 0 | 0% |
| 4 | belgium | 14 | 12 | 1 | 1 | 85.71% |
| 5 | barbarians | 1 | 0 | 0 | 1 | 0% |
| 6 | canada | 1 | 0 | 0 | 1 | 0% |
| 7 | chile | 4 | 2 | 0 | 2 | 50% |
| 8 | croatia | 2 | 1 | 1 | 0 | 50% |
| 9 | denmark | 1 | 1 | 0 | 0 | 100% |
| 10 | england a | 7 | 0 | 0 | 7 | 0% |
| 11 | england counties | 1 | 0 | 0 | 1 | 0% |
| 12 | royal air force rugby team | 4 | 0 | 2 | 2 | 0% |
| 13 | fiji | 1 | 0 | 0 | 1 | 0% |
| 14 | france | 24 | 0 | 0 | 24 | 0% |
| 15 | france a | 2 | 0 | 0 | 2 | 0% |
| 16 | france u | 2 | 1 | 0 | 1 | 50% |
| 17 | french protectorate of morocco | 4 | 1 | 1 | 2 | 25% |
| 18 | georgia | 12 | 3 | 1 | 8 | 25% |
| 19 | germany | 7 | 6 | 0 | 1 | 85.71% |
| 20 | hungary | 1 | 1 | 0 | 0 | 100% |
| 21 | italy | 27 | 3 | 1 | 23 | 11.11% |
| 22 | japan | 3 | 0 | 0 | 3 | 0% |
| 23 | moldova | 1 | 1 | 0 | 0 | 100% |
| 24 | morocco | 17 | 10 | 1 | 6 | 58.82% |
| 25 | namibia | 2 | 2 | 0 | 0 | 100% |
| 26 | netherlands | 13 | 12 | 1 | 0 | 92.31% |
| 27 | new zealand services | 2 | 0 | 0 | 2 | 0% |
| 28 | poland | 16 | 10 | 0 | 6 | 62.50% |
| 29 | portugal | 33 | 21 | 2 | 10 | 63.63% |
| 30 | czech republic | 8 | 2 | 0 | 6 | 75% |
| 31 | czechoslovakia | 5 | 2 | 1 | 2 | 40% |
| 32 | romania | 29 | 2 | 0 | 27 | 6.90% |
| 33 | russia | 16 | 2 | 0 | 14 | 12.50% |
| 34 | scotland | 8 | 0 | 0 | 8 | 0% |
| 35 | slovenia | 1 | 1 | 0 | 0 | 100% |
| 36 | south africa | 1 | 0 | 0 | 1 | 0% |
| 37 | south africa "a" | 1 | 0 | 0 | 1 | 0% |
| 38 | soviet union | 7 | 0 | 0 | 7 | 0% |
| 39 | sweden | 2 | 2 | 0 | 0 | 100% |
| 40 | switzerland | 1 | 1 | 0 | 0 | 100% |
| 41 | tunisia | 6 | 1 | 0 | 5 | 83.33% |
| 42 | ukraine | 2 | 2 | 0 | 0 | 100% |
| 43 | uruguay | 7 | 3 | 0 | 4 | 42.86% |
| 44 | united states | 3 | 0 | 0 | 3 | 0% |
| 45 | wales | 1 | 0 | 0 | 1 | 0% |
| 46 | wales a | 3 | 0 | 0 | 3 | 0% |
| 47 | west germany | 12 | 7 | 1 | 4 | 33.33% |
| 48 | yugoslavia | 4 | 4 | 0 | 0 | 100% |
| 49 | zimbabwe | 7 | 5 | 0 | 2 | 71.43% |
| 50 | total | 336 | 126 | 14 | 197 | 37.50% | | | | count ( "win %" ) |
|---:|--------------------:|
| 0 | 37 | | [
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select runner-up years where club = 'sv ried' col : club | winners | runner-ups | winning years | runner-up years row 1 : fk austria wien | 6 | 2 | 1990, 1991, 1992, 1994, 2003, 2004 | 1986, 1994 row 2 : sk rapid wien | 4 | 1 | 1986, 1987, 1988, 2008 | 1995, 1996 row 3 : sk sturm graz | 3 | 2 | 1996, 1998, 1999 | 1997, 2002 row 4 : sv austria salzburg | 3 | 0 | 1994, 1995, 1997 | none row 5 : grazer ak | 2 | 1 | 2000, 2002 | 2004 row 6 : vfb admira wacker modling | 1 | 1 | 1989 | 1992 row 7 : fc karnten | 1 | 1 | 2001 | 2003 row 8 : fc swarovski tirol / fc tirol innsbruck | 0 | 6 | none | 1987, 1989, 1990, 1993, 2000, 2001 row 9 : kremser sc | 0 | 1 | none | 1988 row 10 : sv stockerau | 0 | 1 | none | 1991 row 11 : sv ried | 0 | 1 | none | 1998 row 12 : lask linz | 0 | 1 | none | 1999 row 13 : sv horn | 0 | 1 | none | 2008 | col : runner-up years row 1 : 1998 | select runner-up years where club = 'sv ried' <table_name> : table \begin{tabular}{llllll}
\toprule
& club & winners & runner-ups & winning years & runner-up years \\
\midrule
0 & fk austria wien & 6 & 2 & 1990, 1991, 1992, 1994, 2003, 2004 & 1986, 1994 \\
1 & sk rapid wien & 4 & 1 & 1986, 1987, 1988, 2008 & 1995, 1996 \\
2 & sk sturm graz & 3 & 2 & 1996, 1998, 1999 & 1997, 2002 \\
3 & sv austria salzburg & 3 & 0 & 1994, 1995, 1997 & none \\
4 & grazer ak & 2 & 1 & 2000, 2002 & 2004 \\
5 & vfb admira wacker modling & 1 & 1 & 1989 & 1992 \\
6 & fc karnten & 1 & 1 & 2001 & 2003 \\
7 & fc swarovski tirol / fc tirol innsbruck & 0 & 6 & none & 1987, 1989, 1990, 1993, 2000, 2001 \\
8 & kremser sc & 0 & 1 & none & 1988 \\
9 & sv stockerau & 0 & 1 & none & 1991 \\
10 & sv ried & 0 & 1 & none & 1998 \\
11 & lask linz & 0 & 1 & none & 1999 \\
12 & sv horn & 0 & 1 & none & 2008 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& runner-up years \\
\midrule
0 & 1998 \\
\bottomrule
\end{tabular}
| select runner-up years where club = 'sv ried' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>club</th>
<th>winners</th>
<th>runner-ups</th>
<th>winning years</th>
<th>runner-up years</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>fk austria wien</td>
<td>6</td>
<td>2</td>
<td>1990, 1991, 1992, 1994, 2003, 2004</td>
<td>1986, 1994</td>
</tr>
<tr>
<th>1</th>
<td>sk rapid wien</td>
<td>4</td>
<td>1</td>
<td>1986, 1987, 1988, 2008</td>
<td>1995, 1996</td>
</tr>
<tr>
<th>2</th>
<td>sk sturm graz</td>
<td>3</td>
<td>2</td>
<td>1996, 1998, 1999</td>
<td>1997, 2002</td>
</tr>
<tr>
<th>3</th>
<td>sv austria salzburg</td>
<td>3</td>
<td>0</td>
<td>1994, 1995, 1997</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>grazer ak</td>
<td>2</td>
<td>1</td>
<td>2000, 2002</td>
<td>2004</td>
</tr>
<tr>
<th>5</th>
<td>vfb admira wacker modling</td>
<td>1</td>
<td>1</td>
<td>1989</td>
<td>1992</td>
</tr>
<tr>
<th>6</th>
<td>fc karnten</td>
<td>1</td>
<td>1</td>
<td>2001</td>
<td>2003</td>
</tr>
<tr>
<th>7</th>
<td>fc swarovski tirol / fc tirol innsbruck</td>
<td>0</td>
<td>6</td>
<td>none</td>
<td>1987, 1989, 1990, 1993, 2000, 2001</td>
</tr>
<tr>
<th>8</th>
<td>kremser sc</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1988</td>
</tr>
<tr>
<th>9</th>
<td>sv stockerau</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1991</td>
</tr>
<tr>
<th>10</th>
<td>sv ried</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1998</td>
</tr>
<tr>
<th>11</th>
<td>lask linz</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>1999</td>
</tr>
<tr>
<th>12</th>
<td>sv horn</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>2008</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>runner-up years</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1998</td>
</tr>
</tbody>
</table> | select runner-up years where club = 'sv ried' <table_name> : table | | club | winners | runner-ups | winning years | runner-up years |
|---:|:----------------------------------------|----------:|-------------:|:-----------------------------------|:-----------------------------------|
| 0 | fk austria wien | 6 | 2 | 1990, 1991, 1992, 1994, 2003, 2004 | 1986, 1994 |
| 1 | sk rapid wien | 4 | 1 | 1986, 1987, 1988, 2008 | 1995, 1996 |
| 2 | sk sturm graz | 3 | 2 | 1996, 1998, 1999 | 1997, 2002 |
| 3 | sv austria salzburg | 3 | 0 | 1994, 1995, 1997 | none |
| 4 | grazer ak | 2 | 1 | 2000, 2002 | 2004 |
| 5 | vfb admira wacker modling | 1 | 1 | 1989 | 1992 |
| 6 | fc karnten | 1 | 1 | 2001 | 2003 |
| 7 | fc swarovski tirol / fc tirol innsbruck | 0 | 6 | none | 1987, 1989, 1990, 1993, 2000, 2001 |
| 8 | kremser sc | 0 | 1 | none | 1988 |
| 9 | sv stockerau | 0 | 1 | none | 1991 |
| 10 | sv ried | 0 | 1 | none | 1998 |
| 11 | lask linz | 0 | 1 | none | 1999 |
| 12 | sv horn | 0 | 1 | none | 2008 | | | | runner-up years |
|---:|------------------:|
| 0 | 1998 | | [
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select count ( * ) where company (country) = 1339 and 2008 arms sales (us$ m.) > 13020 col : 2011 rank | 2010 rank | 2009 rank | 2008 rank | 2007 rank | company (country) | 2011 arms sales (us$ m.) | 2010 arms sales (us$ m.) | 2009 arms sales (us$ m.) | 2008 arms sales (us$ m.) | 2007 arms sales (us$ m.) | arms sales as share of company's total sales (%), row 1 : 1 | 1 | 1 | 2 | 3 | lockheed martin | 36270 | 35730 | 33430 | 29880 | 29400 | 78 row 2 : 2 | 3 | 3 | 3 | 1 | boeing | 31830 | 31360 | 32300 | 29200 | 30480 | 46 row 3 : 3 | 2 | 2 | 1 | 2 | bae systems | 29150 | 32880 | 33250 | 32420 | 29860 | 95 row 4 : 4 | 5 | 5 | 5 | 5 | general dynamics | 23760 | 23940 | 25590 | 22780 | 21520 | 73 row 5 : 5 | 6 | 6 | 6 | 6 | raytheon | 22470 | 22980 | 21030 | 23080 | 19540 | 90 row 6 : 6 | 4 | 4 | 4 | 4 | northrop grumman | 21390 | 28150 | 27000 | 26090 | 24600 | 81 row 7 : 7 | 7 | 7 | 7 | 7 | airbus group | 16390 | 16360 | 17900 | 15930 | 13100 | 24 row 8 : 8 | 8 | 8 | 8 | 9 | finmeccanica | 14560 | 14410 | 13280 | 13020 | 9850 | 60 row 9 : 9 | 9 | 9 | 9 | 8 | l-3 communications | 12520 | 13070 | 13010 | 12160 | 11240 | 83 row 10 : 10 | 10 | 10 | 11 | 11 | united technologies corporation | 11640 | 11410 | 11110 | 9980 | 8760 | 20 row 11 : 11 | 11 | 11 | 10 | 10 | thales group | 9480 | 9950 | 10200 | 10760 | 9350 | 52 row 12 : 12 | 12 | 12 | 12 | 12 | saic | 7940 | 8230 | 8030 | 7350 | 6250 | 75 row 13 : 13 | none | none | none | none | huntington ingalls industries | 6380 | none | none | none | none | 97 row 14 : 14 | 15 | 14 | 15 | 15 | honeywell | 5280 | 5400 | 5380 | 5310 | 5020 | 14 row 15 : 15 | 16 | 16 | 25 | 14 | safran | 5240 | 4800 | 4740 | 3020 | 5230 | 32 row 16 : 16 | 14 | 13 | 14 | 13 | computer sciences corp | 4860 | 5940 | 6050 | 5710 | 5420 | 31 row 17 : 17 | 17 | 19 | 17 | 17 | rolls-royce | 4670 | 4330 | 4140 | 4720 | 4580 | 26 row 18 : 18 | 21 | none | none | none | united aircraft corporation | 4440 | 3440 | none | none | none | 80 row 19 : 19 | 13 | 27 | 37 | 45 | oshkosh corporation | 4370 | 7080 | 2770 | 2070 | 1570 | 58 row 20 : 20 | 18 | 18 | 22 | 20 | general electric | 4100 | 4300 | 4700 | 3650 | 3460 | 3 row 21 : 21 | 19 | 17 | 16 | 19 | itt corp | 4020 | 4000 | 4730 | 5170 | 3850 | 69 row 22 : 22 | 20 | 22 | 18 | 23 | almaz-antey | 3690 | 3950 | 3260 | 4340 | 2780 | 85 | col : count ( "*" ) row 1 : 0 | select count ( * ) where company (country) = 1339 and 2008 arms sales (us$ m.) > 13020 <table_name> : table \begin{tabular}{lllllllllllll}
\toprule
& 2011 rank & 2010 rank & 2009 rank & 2008 rank & 2007 rank & company (country) & 2011 arms sales (us$ m.) & 2010 arms sales (us$ m.) & 2009 arms sales (us$ m.) & 2008 arms sales (us$ m.) & 2007 arms sales (us$ m.) & arms sales as share of company's total sales (%), \\
\midrule
0 & 1 & 1 & 1 & 2 & 3 & lockheed martin & 36270 & 35730 & 33430 & 29880 & 29400 & 78 \\
1 & 2 & 3 & 3 & 3 & 1 & boeing & 31830 & 31360 & 32300 & 29200 & 30480 & 46 \\
2 & 3 & 2 & 2 & 1 & 2 & bae systems & 29150 & 32880 & 33250 & 32420 & 29860 & 95 \\
3 & 4 & 5 & 5 & 5 & 5 & general dynamics & 23760 & 23940 & 25590 & 22780 & 21520 & 73 \\
4 & 5 & 6 & 6 & 6 & 6 & raytheon & 22470 & 22980 & 21030 & 23080 & 19540 & 90 \\
5 & 6 & 4 & 4 & 4 & 4 & northrop grumman & 21390 & 28150 & 27000 & 26090 & 24600 & 81 \\
6 & 7 & 7 & 7 & 7 & 7 & airbus group & 16390 & 16360 & 17900 & 15930 & 13100 & 24 \\
7 & 8 & 8 & 8 & 8 & 9 & finmeccanica & 14560 & 14410 & 13280 & 13020 & 9850 & 60 \\
8 & 9 & 9 & 9 & 9 & 8 & l-3 communications & 12520 & 13070 & 13010 & 12160 & 11240 & 83 \\
9 & 10 & 10 & 10 & 11 & 11 & united technologies corporation & 11640 & 11410 & 11110 & 9980 & 8760 & 20 \\
10 & 11 & 11 & 11 & 10 & 10 & thales group & 9480 & 9950 & 10200 & 10760 & 9350 & 52 \\
11 & 12 & 12 & 12 & 12 & 12 & saic & 7940 & 8230 & 8030 & 7350 & 6250 & 75 \\
12 & 13 & none & none & none & none & huntington ingalls industries & 6380 & none & none & none & none & 97 \\
13 & 14 & 15 & 14 & 15 & 15 & honeywell & 5280 & 5400 & 5380 & 5310 & 5020 & 14 \\
14 & 15 & 16 & 16 & 25 & 14 & safran & 5240 & 4800 & 4740 & 3020 & 5230 & 32 \\
15 & 16 & 14 & 13 & 14 & 13 & computer sciences corp & 4860 & 5940 & 6050 & 5710 & 5420 & 31 \\
16 & 17 & 17 & 19 & 17 & 17 & rolls-royce & 4670 & 4330 & 4140 & 4720 & 4580 & 26 \\
17 & 18 & 21 & none & none & none & united aircraft corporation & 4440 & 3440 & none & none & none & 80 \\
18 & 19 & 13 & 27 & 37 & 45 & oshkosh corporation & 4370 & 7080 & 2770 & 2070 & 1570 & 58 \\
19 & 20 & 18 & 18 & 22 & 20 & general electric & 4100 & 4300 & 4700 & 3650 & 3460 & 3 \\
20 & 21 & 19 & 17 & 16 & 19 & itt corp & 4020 & 4000 & 4730 & 5170 & 3850 & 69 \\
21 & 22 & 20 & 22 & 18 & 23 & almaz-antey & 3690 & 3950 & 3260 & 4340 & 2780 & 85 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where company (country) = 1339 and 2008 arms sales (us$ m.) > 13020 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>2011 rank</th>
<th>2010 rank</th>
<th>2009 rank</th>
<th>2008 rank</th>
<th>2007 rank</th>
<th>company (country)</th>
<th>2011 arms sales (us$ m.)</th>
<th>2010 arms sales (us$ m.)</th>
<th>2009 arms sales (us$ m.)</th>
<th>2008 arms sales (us$ m.)</th>
<th>2007 arms sales (us$ m.)</th>
<th>arms sales as share of company's total sales (%),</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>3</td>
<td>lockheed martin</td>
<td>36270</td>
<td>35730</td>
<td>33430</td>
<td>29880</td>
<td>29400</td>
<td>78</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>3</td>
<td>3</td>
<td>3</td>
<td>1</td>
<td>boeing</td>
<td>31830</td>
<td>31360</td>
<td>32300</td>
<td>29200</td>
<td>30480</td>
<td>46</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>bae systems</td>
<td>29150</td>
<td>32880</td>
<td>33250</td>
<td>32420</td>
<td>29860</td>
<td>95</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>5</td>
<td>5</td>
<td>5</td>
<td>5</td>
<td>general dynamics</td>
<td>23760</td>
<td>23940</td>
<td>25590</td>
<td>22780</td>
<td>21520</td>
<td>73</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>6</td>
<td>6</td>
<td>6</td>
<td>6</td>
<td>raytheon</td>
<td>22470</td>
<td>22980</td>
<td>21030</td>
<td>23080</td>
<td>19540</td>
<td>90</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>4</td>
<td>4</td>
<td>4</td>
<td>4</td>
<td>northrop grumman</td>
<td>21390</td>
<td>28150</td>
<td>27000</td>
<td>26090</td>
<td>24600</td>
<td>81</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>7</td>
<td>7</td>
<td>7</td>
<td>7</td>
<td>airbus group</td>
<td>16390</td>
<td>16360</td>
<td>17900</td>
<td>15930</td>
<td>13100</td>
<td>24</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>8</td>
<td>8</td>
<td>8</td>
<td>9</td>
<td>finmeccanica</td>
<td>14560</td>
<td>14410</td>
<td>13280</td>
<td>13020</td>
<td>9850</td>
<td>60</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>9</td>
<td>9</td>
<td>9</td>
<td>8</td>
<td>l-3 communications</td>
<td>12520</td>
<td>13070</td>
<td>13010</td>
<td>12160</td>
<td>11240</td>
<td>83</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>10</td>
<td>10</td>
<td>11</td>
<td>11</td>
<td>united technologies corporation</td>
<td>11640</td>
<td>11410</td>
<td>11110</td>
<td>9980</td>
<td>8760</td>
<td>20</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>11</td>
<td>11</td>
<td>10</td>
<td>10</td>
<td>thales group</td>
<td>9480</td>
<td>9950</td>
<td>10200</td>
<td>10760</td>
<td>9350</td>
<td>52</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>12</td>
<td>12</td>
<td>12</td>
<td>12</td>
<td>saic</td>
<td>7940</td>
<td>8230</td>
<td>8030</td>
<td>7350</td>
<td>6250</td>
<td>75</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>huntington ingalls industries</td>
<td>6380</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>97</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>15</td>
<td>14</td>
<td>15</td>
<td>15</td>
<td>honeywell</td>
<td>5280</td>
<td>5400</td>
<td>5380</td>
<td>5310</td>
<td>5020</td>
<td>14</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>16</td>
<td>16</td>
<td>25</td>
<td>14</td>
<td>safran</td>
<td>5240</td>
<td>4800</td>
<td>4740</td>
<td>3020</td>
<td>5230</td>
<td>32</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>14</td>
<td>13</td>
<td>14</td>
<td>13</td>
<td>computer sciences corp</td>
<td>4860</td>
<td>5940</td>
<td>6050</td>
<td>5710</td>
<td>5420</td>
<td>31</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>17</td>
<td>19</td>
<td>17</td>
<td>17</td>
<td>rolls-royce</td>
<td>4670</td>
<td>4330</td>
<td>4140</td>
<td>4720</td>
<td>4580</td>
<td>26</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>21</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>united aircraft corporation</td>
<td>4440</td>
<td>3440</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>80</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>13</td>
<td>27</td>
<td>37</td>
<td>45</td>
<td>oshkosh corporation</td>
<td>4370</td>
<td>7080</td>
<td>2770</td>
<td>2070</td>
<td>1570</td>
<td>58</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>18</td>
<td>18</td>
<td>22</td>
<td>20</td>
<td>general electric</td>
<td>4100</td>
<td>4300</td>
<td>4700</td>
<td>3650</td>
<td>3460</td>
<td>3</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>19</td>
<td>17</td>
<td>16</td>
<td>19</td>
<td>itt corp</td>
<td>4020</td>
<td>4000</td>
<td>4730</td>
<td>5170</td>
<td>3850</td>
<td>69</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>20</td>
<td>22</td>
<td>18</td>
<td>23</td>
<td>almaz-antey</td>
<td>3690</td>
<td>3950</td>
<td>3260</td>
<td>4340</td>
<td>2780</td>
<td>85</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where company (country) = 1339 and 2008 arms sales (us$ m.) > 13020 <table_name> : table | | 2011 rank | 2010 rank | 2009 rank | 2008 rank | 2007 rank | company (country) | 2011 arms sales (us$ m.) | 2010 arms sales (us$ m.) | 2009 arms sales (us$ m.) | 2008 arms sales (us$ m.) | 2007 arms sales (us$ m.) | arms sales as share of company's total sales (%), |
|---:|------------:|:------------|:------------|:------------|:------------|:--------------------------------|---------------------------:|:---------------------------|:---------------------------|:---------------------------|:---------------------------|----------------------------------------------------:|
| 0 | 1 | 1 | 1 | 2 | 3 | lockheed martin | 36270 | 35730 | 33430 | 29880 | 29400 | 78 |
| 1 | 2 | 3 | 3 | 3 | 1 | boeing | 31830 | 31360 | 32300 | 29200 | 30480 | 46 |
| 2 | 3 | 2 | 2 | 1 | 2 | bae systems | 29150 | 32880 | 33250 | 32420 | 29860 | 95 |
| 3 | 4 | 5 | 5 | 5 | 5 | general dynamics | 23760 | 23940 | 25590 | 22780 | 21520 | 73 |
| 4 | 5 | 6 | 6 | 6 | 6 | raytheon | 22470 | 22980 | 21030 | 23080 | 19540 | 90 |
| 5 | 6 | 4 | 4 | 4 | 4 | northrop grumman | 21390 | 28150 | 27000 | 26090 | 24600 | 81 |
| 6 | 7 | 7 | 7 | 7 | 7 | airbus group | 16390 | 16360 | 17900 | 15930 | 13100 | 24 |
| 7 | 8 | 8 | 8 | 8 | 9 | finmeccanica | 14560 | 14410 | 13280 | 13020 | 9850 | 60 |
| 8 | 9 | 9 | 9 | 9 | 8 | l-3 communications | 12520 | 13070 | 13010 | 12160 | 11240 | 83 |
| 9 | 10 | 10 | 10 | 11 | 11 | united technologies corporation | 11640 | 11410 | 11110 | 9980 | 8760 | 20 |
| 10 | 11 | 11 | 11 | 10 | 10 | thales group | 9480 | 9950 | 10200 | 10760 | 9350 | 52 |
| 11 | 12 | 12 | 12 | 12 | 12 | saic | 7940 | 8230 | 8030 | 7350 | 6250 | 75 |
| 12 | 13 | none | none | none | none | huntington ingalls industries | 6380 | none | none | none | none | 97 |
| 13 | 14 | 15 | 14 | 15 | 15 | honeywell | 5280 | 5400 | 5380 | 5310 | 5020 | 14 |
| 14 | 15 | 16 | 16 | 25 | 14 | safran | 5240 | 4800 | 4740 | 3020 | 5230 | 32 |
| 15 | 16 | 14 | 13 | 14 | 13 | computer sciences corp | 4860 | 5940 | 6050 | 5710 | 5420 | 31 |
| 16 | 17 | 17 | 19 | 17 | 17 | rolls-royce | 4670 | 4330 | 4140 | 4720 | 4580 | 26 |
| 17 | 18 | 21 | none | none | none | united aircraft corporation | 4440 | 3440 | none | none | none | 80 |
| 18 | 19 | 13 | 27 | 37 | 45 | oshkosh corporation | 4370 | 7080 | 2770 | 2070 | 1570 | 58 |
| 19 | 20 | 18 | 18 | 22 | 20 | general electric | 4100 | 4300 | 4700 | 3650 | 3460 | 3 |
| 20 | 21 | 19 | 17 | 16 | 19 | itt corp | 4020 | 4000 | 4730 | 5170 | 3850 | 69 |
| 21 | 22 | 20 | 22 | 18 | 23 | almaz-antey | 3690 | 3950 | 3260 | 4340 | 2780 | 85 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( * ) where peak hours only = 4 col : route | destinations | via | frequency (minutes) | peak hours only | former row 1 : 1 | montreal street st. lawrence college | downtown | 30 | none | cataraqui town centre-woods row 2 : 2 | kingston centre division street | st. lawrence college downtown | 30 | none | none row 3 : 3 | kingston centre downtown | queen mary road st. lawrence college king street | 30 | none | none row 4 : 4 | princess street | cataraqui town centre downtown | 30 | none | none row 5 : 6 | cataraqui town centre st. lawrence college | gardiners town centre | 30 | none | downtown row 6 : 7 | dalton/division midland/gardiners | cataraqui town centre train station bus terminal | 30 | none | none row 7 : 9 | downtown cataraqui town centre | brock st. / barrie st. gardiners town centre | 20 | none | none row 8 : 10 | amherstview cataraqui town centre | collins bay road | 30 | none | kingston centre row 9 : 11 | kingston centre cataraqui town centre | bath road gardiners town centre | 30 | none | (formerly route 71) row 10 : 12 | kingston centre highway 15 | downtown cfb kingston (off-peak only) | 30 | none | none row 11 : 12a | cfb kingston downtown | none | 30 | x | none row 12 : 18 | train station bus terminal | downtown queen's university st. lawrence college | none | none | student circuit row 13 : 19 | montreal street queen's university | downtown | 30 | x | none row 14 : 14 | train station cataraqui town centre / midland avenue | waterloo-davis multiplex | 30 | none | (formerly route a) row 15 : 15 | reddendale cataraqui town centre - woods | gardiners town centre | 30 | none | (formerly route b) row 16 : 16 | train station bus terminal | kingston centre | 30 | none | (formerly route c) | col : count ( "*" ) row 1 : 0 | select count ( * ) where peak hours only = 4 <table_name> : table \begin{tabular}{lllllll}
\toprule
& route & destinations & via & frequency (minutes) & peak hours only & former \\
\midrule
0 & 1 & montreal street st. lawrence college & downtown & 30 & none & cataraqui town centre-woods \\
1 & 2 & kingston centre division street & st. lawrence college downtown & 30 & none & none \\
2 & 3 & kingston centre downtown & queen mary road st. lawrence college king street & 30 & none & none \\
3 & 4 & princess street & cataraqui town centre downtown & 30 & none & none \\
4 & 6 & cataraqui town centre st. lawrence college & gardiners town centre & 30 & none & downtown \\
5 & 7 & dalton/division midland/gardiners & cataraqui town centre train station bus terminal & 30 & none & none \\
6 & 9 & downtown cataraqui town centre & brock st. / barrie st. gardiners town centre & 20 & none & none \\
7 & 10 & amherstview cataraqui town centre & collins bay road & 30 & none & kingston centre \\
8 & 11 & kingston centre cataraqui town centre & bath road gardiners town centre & 30 & none & (formerly route 71) \\
9 & 12 & kingston centre highway 15 & downtown cfb kingston (off-peak only) & 30 & none & none \\
10 & 12a & cfb kingston downtown & none & 30 & x & none \\
11 & 18 & train station bus terminal & downtown queen's university st. lawrence college & none & none & student circuit \\
12 & 19 & montreal street queen's university & downtown & 30 & x & none \\
13 & 14 & train station cataraqui town centre / midland avenue & waterloo-davis multiplex & 30 & none & (formerly route a) \\
14 & 15 & reddendale cataraqui town centre - woods & gardiners town centre & 30 & none & (formerly route b) \\
15 & 16 & train station bus terminal & kingston centre & 30 & none & (formerly route c) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where peak hours only = 4 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>route</th>
<th>destinations</th>
<th>via</th>
<th>frequency (minutes)</th>
<th>peak hours only</th>
<th>former</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>montreal street st. lawrence college</td>
<td>downtown</td>
<td>30</td>
<td>none</td>
<td>cataraqui town centre-woods</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>kingston centre division street</td>
<td>st. lawrence college downtown</td>
<td>30</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>kingston centre downtown</td>
<td>queen mary road st. lawrence college king street</td>
<td>30</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>princess street</td>
<td>cataraqui town centre downtown</td>
<td>30</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>cataraqui town centre st. lawrence college</td>
<td>gardiners town centre</td>
<td>30</td>
<td>none</td>
<td>downtown</td>
</tr>
<tr>
<th>5</th>
<td>7</td>
<td>dalton/division midland/gardiners</td>
<td>cataraqui town centre train station bus terminal</td>
<td>30</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>9</td>
<td>downtown cataraqui town centre</td>
<td>brock st. / barrie st. gardiners town centre</td>
<td>20</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>10</td>
<td>amherstview cataraqui town centre</td>
<td>collins bay road</td>
<td>30</td>
<td>none</td>
<td>kingston centre</td>
</tr>
<tr>
<th>8</th>
<td>11</td>
<td>kingston centre cataraqui town centre</td>
<td>bath road gardiners town centre</td>
<td>30</td>
<td>none</td>
<td>(formerly route 71)</td>
</tr>
<tr>
<th>9</th>
<td>12</td>
<td>kingston centre highway 15</td>
<td>downtown cfb kingston (off-peak only)</td>
<td>30</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>12a</td>
<td>cfb kingston downtown</td>
<td>none</td>
<td>30</td>
<td>x</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>18</td>
<td>train station bus terminal</td>
<td>downtown queen's university st. lawrence college</td>
<td>none</td>
<td>none</td>
<td>student circuit</td>
</tr>
<tr>
<th>12</th>
<td>19</td>
<td>montreal street queen's university</td>
<td>downtown</td>
<td>30</td>
<td>x</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>train station cataraqui town centre / midland avenue</td>
<td>waterloo-davis multiplex</td>
<td>30</td>
<td>none</td>
<td>(formerly route a)</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>reddendale cataraqui town centre - woods</td>
<td>gardiners town centre</td>
<td>30</td>
<td>none</td>
<td>(formerly route b)</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>train station bus terminal</td>
<td>kingston centre</td>
<td>30</td>
<td>none</td>
<td>(formerly route c)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where peak hours only = 4 <table_name> : table | | route | destinations | via | frequency (minutes) | peak hours only | former |
|---:|:--------|:-----------------------------------------------------|:-------------------------------------------------|:----------------------|:------------------|:----------------------------|
| 0 | 1 | montreal street st. lawrence college | downtown | 30 | none | cataraqui town centre-woods |
| 1 | 2 | kingston centre division street | st. lawrence college downtown | 30 | none | none |
| 2 | 3 | kingston centre downtown | queen mary road st. lawrence college king street | 30 | none | none |
| 3 | 4 | princess street | cataraqui town centre downtown | 30 | none | none |
| 4 | 6 | cataraqui town centre st. lawrence college | gardiners town centre | 30 | none | downtown |
| 5 | 7 | dalton/division midland/gardiners | cataraqui town centre train station bus terminal | 30 | none | none |
| 6 | 9 | downtown cataraqui town centre | brock st. / barrie st. gardiners town centre | 20 | none | none |
| 7 | 10 | amherstview cataraqui town centre | collins bay road | 30 | none | kingston centre |
| 8 | 11 | kingston centre cataraqui town centre | bath road gardiners town centre | 30 | none | (formerly route 71) |
| 9 | 12 | kingston centre highway 15 | downtown cfb kingston (off-peak only) | 30 | none | none |
| 10 | 12a | cfb kingston downtown | none | 30 | x | none |
| 11 | 18 | train station bus terminal | downtown queen's university st. lawrence college | none | none | student circuit |
| 12 | 19 | montreal street queen's university | downtown | 30 | x | none |
| 13 | 14 | train station cataraqui town centre / midland avenue | waterloo-davis multiplex | 30 | none | (formerly route a) |
| 14 | 15 | reddendale cataraqui town centre - woods | gardiners town centre | 30 | none | (formerly route b) |
| 15 | 16 | train station bus terminal | kingston centre | 30 | none | (formerly route c) | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( opponent ) where bye = 0 col : week | date | opponent | result | record | game site | tv time | attendance | bye row 1 : 1 | september 1, 1996 | arizona cardinals | w 20-13 | 1-0 | rca dome | fox 1:00 pm | 48133 | 0 row 2 : 2 | september 8, 1996 | at new york jets | w 21-7 | 2-0 | the meadowlands | nbc 4:15 pm | 63534 | 0 row 3 : 3 | september 15, 1996 | at dallas cowboys | w 25-24 | 3-0 | texas stadium | nbc 4:15 pm | 63021 | 0 row 4 : 4 | september 23, 1996 | miami dolphins | w 10-6 | 4-0 | rca dome | abc 9:00 pm | 60891 | 0 row 5 : 5 | none | none | none | none | none | none | none | 1 row 6 : 6 | october 6, 1996 | at buffalo bills | l 13-16 | 4-1 | rich stadium | nbc 4:15 pm | 79401 | 0 row 7 : 7 | october 13, 1996 | baltimore ravens | w 26-21 | 5-1 | rca dome | tnt 8:15 pm | 56978 | 0 row 8 : 8 | october 20, 1996 | new england patriots | l 9-27 | 5-2 | rca dome | nbc 1:00 pm | 58725 | 0 row 9 : 9 | october 27, 1996 | at washington redskins | l 16-31 | 5-3 | rfk stadium | nbc 1:00 pm | 54254 | 0 row 10 : 10 | november 3, 1996 | san diego chargers | l 19-26 | 5-4 | rca dome | nbc 1:00 pm | 58484 | 0 row 11 : 11 | november 10, 1996 | at miami dolphins | l 13-37 | 5-5 | joe robbie stadium | nbc 1:00 pm | 66623 | 0 row 12 : 12 | november 17, 1996 | new york jets | w 34-29 | 6-5 | rca dome | nbc 1:00 pm | 48322 | 0 row 13 : 13 | november 24, 1996 | at new england patriots | l 13-27 | 6-6 | foxboro stadium | nbc 1:00 pm | 58226 | 0 row 14 : 14 | december 1, 1996 | buffalo bills | w 13-10 | 7-6 | rca dome | nbc 4:15 pm | 53804 | 0 row 15 : 15 | december 5, 1996 | philadelphia eagles | w 37-10 | 8-6 | rca dome | espn 8:15 pm | 52689 | 0 row 16 : 16 | december 15, 1996 | at kansas city chiefs | w 24-19 | 9-6 | arrowhead stadium | nbc 4:15 pm | 71136 | 0 row 17 : 17 | december 22, 1996 | at cincinnati bengals | l 24-31 | 9-7 | cinergy field | nbc 1:00 pm | 49389 | 0 | col : count ( "opponent" ) row 1 : 16 | select count ( opponent ) where bye = 0 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& week & date & opponent & result & record & game site & tv time & attendance & bye \\
\midrule
0 & 1 & september 1, 1996 & arizona cardinals & w 20-13 & 1-0 & rca dome & fox 1:00 pm & 48133 & 0 \\
1 & 2 & september 8, 1996 & at new york jets & w 21-7 & 2-0 & the meadowlands & nbc 4:15 pm & 63534 & 0 \\
2 & 3 & september 15, 1996 & at dallas cowboys & w 25-24 & 3-0 & texas stadium & nbc 4:15 pm & 63021 & 0 \\
3 & 4 & september 23, 1996 & miami dolphins & w 10-6 & 4-0 & rca dome & abc 9:00 pm & 60891 & 0 \\
4 & 5 & none & none & none & none & none & none & none & 1 \\
5 & 6 & october 6, 1996 & at buffalo bills & l 13-16 & 4-1 & rich stadium & nbc 4:15 pm & 79401 & 0 \\
6 & 7 & october 13, 1996 & baltimore ravens & w 26-21 & 5-1 & rca dome & tnt 8:15 pm & 56978 & 0 \\
7 & 8 & october 20, 1996 & new england patriots & l 9-27 & 5-2 & rca dome & nbc 1:00 pm & 58725 & 0 \\
8 & 9 & october 27, 1996 & at washington redskins & l 16-31 & 5-3 & rfk stadium & nbc 1:00 pm & 54254 & 0 \\
9 & 10 & november 3, 1996 & san diego chargers & l 19-26 & 5-4 & rca dome & nbc 1:00 pm & 58484 & 0 \\
10 & 11 & november 10, 1996 & at miami dolphins & l 13-37 & 5-5 & joe robbie stadium & nbc 1:00 pm & 66623 & 0 \\
11 & 12 & november 17, 1996 & new york jets & w 34-29 & 6-5 & rca dome & nbc 1:00 pm & 48322 & 0 \\
12 & 13 & november 24, 1996 & at new england patriots & l 13-27 & 6-6 & foxboro stadium & nbc 1:00 pm & 58226 & 0 \\
13 & 14 & december 1, 1996 & buffalo bills & w 13-10 & 7-6 & rca dome & nbc 4:15 pm & 53804 & 0 \\
14 & 15 & december 5, 1996 & philadelphia eagles & w 37-10 & 8-6 & rca dome & espn 8:15 pm & 52689 & 0 \\
15 & 16 & december 15, 1996 & at kansas city chiefs & w 24-19 & 9-6 & arrowhead stadium & nbc 4:15 pm & 71136 & 0 \\
16 & 17 & december 22, 1996 & at cincinnati bengals & l 24-31 & 9-7 & cinergy field & nbc 1:00 pm & 49389 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "opponent" ) \\
\midrule
0 & 16 \\
\bottomrule
\end{tabular}
| select count ( opponent ) where bye = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>date</th>
<th>opponent</th>
<th>result</th>
<th>record</th>
<th>game site</th>
<th>tv time</th>
<th>attendance</th>
<th>bye</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>september 1, 1996</td>
<td>arizona cardinals</td>
<td>w 20-13</td>
<td>1-0</td>
<td>rca dome</td>
<td>fox 1:00 pm</td>
<td>48133</td>
<td>0</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>september 8, 1996</td>
<td>at new york jets</td>
<td>w 21-7</td>
<td>2-0</td>
<td>the meadowlands</td>
<td>nbc 4:15 pm</td>
<td>63534</td>
<td>0</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>september 15, 1996</td>
<td>at dallas cowboys</td>
<td>w 25-24</td>
<td>3-0</td>
<td>texas stadium</td>
<td>nbc 4:15 pm</td>
<td>63021</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>september 23, 1996</td>
<td>miami dolphins</td>
<td>w 10-6</td>
<td>4-0</td>
<td>rca dome</td>
<td>abc 9:00 pm</td>
<td>60891</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>october 6, 1996</td>
<td>at buffalo bills</td>
<td>l 13-16</td>
<td>4-1</td>
<td>rich stadium</td>
<td>nbc 4:15 pm</td>
<td>79401</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>october 13, 1996</td>
<td>baltimore ravens</td>
<td>w 26-21</td>
<td>5-1</td>
<td>rca dome</td>
<td>tnt 8:15 pm</td>
<td>56978</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>october 20, 1996</td>
<td>new england patriots</td>
<td>l 9-27</td>
<td>5-2</td>
<td>rca dome</td>
<td>nbc 1:00 pm</td>
<td>58725</td>
<td>0</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>october 27, 1996</td>
<td>at washington redskins</td>
<td>l 16-31</td>
<td>5-3</td>
<td>rfk stadium</td>
<td>nbc 1:00 pm</td>
<td>54254</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>november 3, 1996</td>
<td>san diego chargers</td>
<td>l 19-26</td>
<td>5-4</td>
<td>rca dome</td>
<td>nbc 1:00 pm</td>
<td>58484</td>
<td>0</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>november 10, 1996</td>
<td>at miami dolphins</td>
<td>l 13-37</td>
<td>5-5</td>
<td>joe robbie stadium</td>
<td>nbc 1:00 pm</td>
<td>66623</td>
<td>0</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>november 17, 1996</td>
<td>new york jets</td>
<td>w 34-29</td>
<td>6-5</td>
<td>rca dome</td>
<td>nbc 1:00 pm</td>
<td>48322</td>
<td>0</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>november 24, 1996</td>
<td>at new england patriots</td>
<td>l 13-27</td>
<td>6-6</td>
<td>foxboro stadium</td>
<td>nbc 1:00 pm</td>
<td>58226</td>
<td>0</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>december 1, 1996</td>
<td>buffalo bills</td>
<td>w 13-10</td>
<td>7-6</td>
<td>rca dome</td>
<td>nbc 4:15 pm</td>
<td>53804</td>
<td>0</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>december 5, 1996</td>
<td>philadelphia eagles</td>
<td>w 37-10</td>
<td>8-6</td>
<td>rca dome</td>
<td>espn 8:15 pm</td>
<td>52689</td>
<td>0</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>december 15, 1996</td>
<td>at kansas city chiefs</td>
<td>w 24-19</td>
<td>9-6</td>
<td>arrowhead stadium</td>
<td>nbc 4:15 pm</td>
<td>71136</td>
<td>0</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>december 22, 1996</td>
<td>at cincinnati bengals</td>
<td>l 24-31</td>
<td>9-7</td>
<td>cinergy field</td>
<td>nbc 1:00 pm</td>
<td>49389</td>
<td>0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "opponent" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>16</td>
</tr>
</tbody>
</table> | select count ( opponent ) where bye = 0 <table_name> : table | | week | date | opponent | result | record | game site | tv time | attendance | bye |
|---:|-------:|:-------------------|:------------------------|:---------|:---------|:-------------------|:-------------|:-------------|------:|
| 0 | 1 | september 1, 1996 | arizona cardinals | w 20-13 | 1-0 | rca dome | fox 1:00 pm | 48133 | 0 |
| 1 | 2 | september 8, 1996 | at new york jets | w 21-7 | 2-0 | the meadowlands | nbc 4:15 pm | 63534 | 0 |
| 2 | 3 | september 15, 1996 | at dallas cowboys | w 25-24 | 3-0 | texas stadium | nbc 4:15 pm | 63021 | 0 |
| 3 | 4 | september 23, 1996 | miami dolphins | w 10-6 | 4-0 | rca dome | abc 9:00 pm | 60891 | 0 |
| 4 | 5 | none | none | none | none | none | none | none | 1 |
| 5 | 6 | october 6, 1996 | at buffalo bills | l 13-16 | 4-1 | rich stadium | nbc 4:15 pm | 79401 | 0 |
| 6 | 7 | october 13, 1996 | baltimore ravens | w 26-21 | 5-1 | rca dome | tnt 8:15 pm | 56978 | 0 |
| 7 | 8 | october 20, 1996 | new england patriots | l 9-27 | 5-2 | rca dome | nbc 1:00 pm | 58725 | 0 |
| 8 | 9 | october 27, 1996 | at washington redskins | l 16-31 | 5-3 | rfk stadium | nbc 1:00 pm | 54254 | 0 |
| 9 | 10 | november 3, 1996 | san diego chargers | l 19-26 | 5-4 | rca dome | nbc 1:00 pm | 58484 | 0 |
| 10 | 11 | november 10, 1996 | at miami dolphins | l 13-37 | 5-5 | joe robbie stadium | nbc 1:00 pm | 66623 | 0 |
| 11 | 12 | november 17, 1996 | new york jets | w 34-29 | 6-5 | rca dome | nbc 1:00 pm | 48322 | 0 |
| 12 | 13 | november 24, 1996 | at new england patriots | l 13-27 | 6-6 | foxboro stadium | nbc 1:00 pm | 58226 | 0 |
| 13 | 14 | december 1, 1996 | buffalo bills | w 13-10 | 7-6 | rca dome | nbc 4:15 pm | 53804 | 0 |
| 14 | 15 | december 5, 1996 | philadelphia eagles | w 37-10 | 8-6 | rca dome | espn 8:15 pm | 52689 | 0 |
| 15 | 16 | december 15, 1996 | at kansas city chiefs | w 24-19 | 9-6 | arrowhead stadium | nbc 4:15 pm | 71136 | 0 |
| 16 | 17 | december 22, 1996 | at cincinnati bengals | l 24-31 | 9-7 | cinergy field | nbc 1:00 pm | 49389 | 0 | | | | count ( "opponent" ) |
|---:|-----------------------:|
| 0 | 16 | | [
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select athletes where time < '3:43.42' order by time desc limit 1 col : rank | pair | country | athletes | time | deficit row 1 : none | 3 | netherlands | sven kramer koen verweij jan blokhuijsen | 3:41.43 | none row 2 : none | 4 | united states | shani davis brian hansen jonathan kuck | 3:43.42 | 1.99 row 3 : none | 2 | russia | ivan skobrev denis yuskov yevgeny lalenkov | 3:43.62 | 2.19 row 4 : 4 | 1 | canada | denny morrison mathieu giroux lucas makowsky | 3:44.38 | 2.95 row 5 : 5 | 1 | norway | sverre lunde pedersen havard bøkko kristian reistad fredriksen | 3:46.33 | 4.9 row 6 : 6 | 3 | germany | patrick beckert marco weber robert lehmann | 3:46.48 | 5.05 row 7 : 7 | 4 | south korea | lee seung-hoon joo hyong-jun ko byung-wook | 3:47.18 | 5.75 row 8 : 8 | 2 | poland | zbigniew brodka konrad niedzwiedzki jan szymanski | 3:47.72 | 6.29 | col : athletes row 1 : sven kramer koen verweij jan blokhuijsen | select athletes where time < '3:43.42' order by time desc limit 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & pair & country & athletes & time & deficit \\
\midrule
0 & none & 3 & netherlands & sven kramer koen verweij jan blokhuijsen & 3:41.43 & none \\
1 & none & 4 & united states & shani davis brian hansen jonathan kuck & 3:43.42 & 1.99 \\
2 & none & 2 & russia & ivan skobrev denis yuskov yevgeny lalenkov & 3:43.62 & 2.19 \\
3 & 4 & 1 & canada & denny morrison mathieu giroux lucas makowsky & 3:44.38 & 2.95 \\
4 & 5 & 1 & norway & sverre lunde pedersen havard bøkko kristian reistad fredriksen & 3:46.33 & 4.9 \\
5 & 6 & 3 & germany & patrick beckert marco weber robert lehmann & 3:46.48 & 5.05 \\
6 & 7 & 4 & south korea & lee seung-hoon joo hyong-jun ko byung-wook & 3:47.18 & 5.75 \\
7 & 8 & 2 & poland & zbigniew brodka konrad niedzwiedzki jan szymanski & 3:47.72 & 6.29 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& athletes \\
\midrule
0 & sven kramer koen verweij jan blokhuijsen \\
\bottomrule
\end{tabular}
| select athletes where time < '3:43.42' order by time desc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>pair</th>
<th>country</th>
<th>athletes</th>
<th>time</th>
<th>deficit</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>3</td>
<td>netherlands</td>
<td>sven kramer koen verweij jan blokhuijsen</td>
<td>3:41.43</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>4</td>
<td>united states</td>
<td>shani davis brian hansen jonathan kuck</td>
<td>3:43.42</td>
<td>1.99</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>2</td>
<td>russia</td>
<td>ivan skobrev denis yuskov yevgeny lalenkov</td>
<td>3:43.62</td>
<td>2.19</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1</td>
<td>canada</td>
<td>denny morrison mathieu giroux lucas makowsky</td>
<td>3:44.38</td>
<td>2.95</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1</td>
<td>norway</td>
<td>sverre lunde pedersen havard bøkko kristian reistad fredriksen</td>
<td>3:46.33</td>
<td>4.9</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>3</td>
<td>germany</td>
<td>patrick beckert marco weber robert lehmann</td>
<td>3:46.48</td>
<td>5.05</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>4</td>
<td>south korea</td>
<td>lee seung-hoon joo hyong-jun ko byung-wook</td>
<td>3:47.18</td>
<td>5.75</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2</td>
<td>poland</td>
<td>zbigniew brodka konrad niedzwiedzki jan szymanski</td>
<td>3:47.72</td>
<td>6.29</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>athletes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>sven kramer koen verweij jan blokhuijsen</td>
</tr>
</tbody>
</table> | select athletes where time < '3:43.42' order by time desc limit 1 <table_name> : table | | rank | pair | country | athletes | time | deficit |
|---:|:-------|-------:|:--------------|:---------------------------------------------------------------|:--------|:----------|
| 0 | none | 3 | netherlands | sven kramer koen verweij jan blokhuijsen | 3:41.43 | none |
| 1 | none | 4 | united states | shani davis brian hansen jonathan kuck | 3:43.42 | 1.99 |
| 2 | none | 2 | russia | ivan skobrev denis yuskov yevgeny lalenkov | 3:43.62 | 2.19 |
| 3 | 4 | 1 | canada | denny morrison mathieu giroux lucas makowsky | 3:44.38 | 2.95 |
| 4 | 5 | 1 | norway | sverre lunde pedersen havard bøkko kristian reistad fredriksen | 3:46.33 | 4.9 |
| 5 | 6 | 3 | germany | patrick beckert marco weber robert lehmann | 3:46.48 | 5.05 |
| 6 | 7 | 4 | south korea | lee seung-hoon joo hyong-jun ko byung-wook | 3:47.18 | 5.75 |
| 7 | 8 | 2 | poland | zbigniew brodka konrad niedzwiedzki jan szymanski | 3:47.72 | 6.29 | | | | athletes |
|---:|:-----------------------------------------|
| 0 | sven kramer koen verweij jan blokhuijsen | | [
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] |
select driver where difference = '2:48.9' col : pos. | driver | co-driver | car | time | difference | points row 1 : 1 | sebastien loeb | daniel elena | citroen c4 wrc | 3:59:18.9 | 0 | 10 row 2 : 2 | dani sordo | marc marti | citroen c4 wrc | 3:59;36.4 | 17.5 | 8 row 3 : 3 | mikko hirvonen | jarmo lehtinen | ford focus rs wrc 08 | 4:00:00.4 | 41.5 | 6 row 4 : 4 | petter solberg | phil mills | subaru impreza wrc 2008 | 4:02:07.8 | 2:48.9 | 5 row 5 : 5 | urmo aava | kuldar sikk | citroen c4 wrc | 4:02:49.6 | 3:30.7 | 4 row 6 : 6 | pg andersson | jonas andersson | suzuki sx4 wrc | 4:06:56.3 | 7:37.4 | 3 row 7 : 7 | toni gardemeister | tomi tuominen | suzuki sx4 wrc | 4:07:13.8 | 7:54.9 | 2 row 8 : 8 | federico villagra | jorge perez companc | ford focus rs wrc 07 | 4:07:53.9 | 8:35.0 | 1 row 9 : 1. (10.) | martin prokop | jan tomanek | mitsubishi lancer evo ix | 4:13:07.9 | 0 | 10 row 10 : 2. (11.) | patrik sandell | emil axelsson | mitsubishi lancer evo ix | 4:13:44.1 | 36.2 | 8 row 11 : 3. (12.) | martin rauam | silver kutt | mitsubishi lancer evo ix | 4:14:05.7 | 57.8 | 6 | col : driver row 1 : petter solberg | select driver where difference = '2:48.9' <table_name> : table \begin{tabular}{llllllll}
\toprule
& pos. & driver & co-driver & car & time & difference & points \\
\midrule
0 & 1 & sebastien loeb & daniel elena & citroen c4 wrc & 3:59:18.9 & 0 & 10 \\
1 & 2 & dani sordo & marc marti & citroen c4 wrc & 3:59;36.4 & 17.5 & 8 \\
2 & 3 & mikko hirvonen & jarmo lehtinen & ford focus rs wrc 08 & 4:00:00.4 & 41.5 & 6 \\
3 & 4 & petter solberg & phil mills & subaru impreza wrc 2008 & 4:02:07.8 & 2:48.9 & 5 \\
4 & 5 & urmo aava & kuldar sikk & citroen c4 wrc & 4:02:49.6 & 3:30.7 & 4 \\
5 & 6 & pg andersson & jonas andersson & suzuki sx4 wrc & 4:06:56.3 & 7:37.4 & 3 \\
6 & 7 & toni gardemeister & tomi tuominen & suzuki sx4 wrc & 4:07:13.8 & 7:54.9 & 2 \\
7 & 8 & federico villagra & jorge perez companc & ford focus rs wrc 07 & 4:07:53.9 & 8:35.0 & 1 \\
8 & 1. (10.) & martin prokop & jan tomanek & mitsubishi lancer evo ix & 4:13:07.9 & 0 & 10 \\
9 & 2. (11.) & patrik sandell & emil axelsson & mitsubishi lancer evo ix & 4:13:44.1 & 36.2 & 8 \\
10 & 3. (12.) & martin rauam & silver kutt & mitsubishi lancer evo ix & 4:14:05.7 & 57.8 & 6 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& driver \\
\midrule
0 & petter solberg \\
\bottomrule
\end{tabular}
| select driver where difference = '2:48.9' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos.</th>
<th>driver</th>
<th>co-driver</th>
<th>car</th>
<th>time</th>
<th>difference</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>sebastien loeb</td>
<td>daniel elena</td>
<td>citroen c4 wrc</td>
<td>3:59:18.9</td>
<td>0</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>dani sordo</td>
<td>marc marti</td>
<td>citroen c4 wrc</td>
<td>3:59;36.4</td>
<td>17.5</td>
<td>8</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>mikko hirvonen</td>
<td>jarmo lehtinen</td>
<td>ford focus rs wrc 08</td>
<td>4:00:00.4</td>
<td>41.5</td>
<td>6</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>petter solberg</td>
<td>phil mills</td>
<td>subaru impreza wrc 2008</td>
<td>4:02:07.8</td>
<td>2:48.9</td>
<td>5</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>urmo aava</td>
<td>kuldar sikk</td>
<td>citroen c4 wrc</td>
<td>4:02:49.6</td>
<td>3:30.7</td>
<td>4</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>pg andersson</td>
<td>jonas andersson</td>
<td>suzuki sx4 wrc</td>
<td>4:06:56.3</td>
<td>7:37.4</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>toni gardemeister</td>
<td>tomi tuominen</td>
<td>suzuki sx4 wrc</td>
<td>4:07:13.8</td>
<td>7:54.9</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>federico villagra</td>
<td>jorge perez companc</td>
<td>ford focus rs wrc 07</td>
<td>4:07:53.9</td>
<td>8:35.0</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>1. (10.)</td>
<td>martin prokop</td>
<td>jan tomanek</td>
<td>mitsubishi lancer evo ix</td>
<td>4:13:07.9</td>
<td>0</td>
<td>10</td>
</tr>
<tr>
<th>9</th>
<td>2. (11.)</td>
<td>patrik sandell</td>
<td>emil axelsson</td>
<td>mitsubishi lancer evo ix</td>
<td>4:13:44.1</td>
<td>36.2</td>
<td>8</td>
</tr>
<tr>
<th>10</th>
<td>3. (12.)</td>
<td>martin rauam</td>
<td>silver kutt</td>
<td>mitsubishi lancer evo ix</td>
<td>4:14:05.7</td>
<td>57.8</td>
<td>6</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>driver</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>petter solberg</td>
</tr>
</tbody>
</table> | select driver where difference = '2:48.9' <table_name> : table | | pos. | driver | co-driver | car | time | difference | points |
|---:|:---------|:------------------|:--------------------|:-------------------------|:----------|:-------------|---------:|
| 0 | 1 | sebastien loeb | daniel elena | citroen c4 wrc | 3:59:18.9 | 0 | 10 |
| 1 | 2 | dani sordo | marc marti | citroen c4 wrc | 3:59;36.4 | 17.5 | 8 |
| 2 | 3 | mikko hirvonen | jarmo lehtinen | ford focus rs wrc 08 | 4:00:00.4 | 41.5 | 6 |
| 3 | 4 | petter solberg | phil mills | subaru impreza wrc 2008 | 4:02:07.8 | 2:48.9 | 5 |
| 4 | 5 | urmo aava | kuldar sikk | citroen c4 wrc | 4:02:49.6 | 3:30.7 | 4 |
| 5 | 6 | pg andersson | jonas andersson | suzuki sx4 wrc | 4:06:56.3 | 7:37.4 | 3 |
| 6 | 7 | toni gardemeister | tomi tuominen | suzuki sx4 wrc | 4:07:13.8 | 7:54.9 | 2 |
| 7 | 8 | federico villagra | jorge perez companc | ford focus rs wrc 07 | 4:07:53.9 | 8:35.0 | 1 |
| 8 | 1. (10.) | martin prokop | jan tomanek | mitsubishi lancer evo ix | 4:13:07.9 | 0 | 10 |
| 9 | 2. (11.) | patrik sandell | emil axelsson | mitsubishi lancer evo ix | 4:13:44.1 | 36.2 | 8 |
| 10 | 3. (12.) | martin rauam | silver kutt | mitsubishi lancer evo ix | 4:14:05.7 | 57.8 | 6 | | | | driver |
|---:|:---------------|
| 0 | petter solberg | | [
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select count ( * ) where date = 'october 24' col : date | opponent | site | result row 1 : september 5 | alcorn state | independence stadium • shreveport. la | l 24-28 row 2 : september 12 | vs. central state | yankee stadium • new york, ny | l 21-37 row 3 : september 26 | bethune-cookman | eddie robinson stadium • grambling, la | w 21-14 row 4 : october 3 | vs. prairie view a&m | cotton bowl • dallas, tx | w 28-7 row 5 : october 10 | at tennessee state | dudley field • nashville, tn | w 51-9 row 6 : october 17 | mississippi valley state | eddie robinson stadium • grambling, la | w 45-14 row 7 : october 24 | at jackson state | mississippi veterans memorial stadium • jackson, ms | l 17-31 row 8 : october 31 | texas southern | eddie robinson stadium • grambling, la | w 30-9 row 9 : november 7 | at alabama state | cramton bowl • montgomery, al | l 7-17 row 10 : november 14 | south carolina state | eddie robinson stadium • grambling, la | l 13-15 row 11 : november 28 | vs. southern | louisiana superdome • new orleans, la (xiv bayou classic) | l 21-27 | col : count ( "*" ) row 1 : 1 | select count ( * ) where date = 'october 24' <table_name> : table \begin{tabular}{lllll}
\toprule
& date & opponent & site & result \\
\midrule
0 & september 5 & alcorn state & independence stadium • shreveport. la & l 24-28 \\
1 & september 12 & vs. central state & yankee stadium • new york, ny & l 21-37 \\
2 & september 26 & bethune-cookman & eddie robinson stadium • grambling, la & w 21-14 \\
3 & october 3 & vs. prairie view a&m & cotton bowl • dallas, tx & w 28-7 \\
4 & october 10 & at tennessee state & dudley field • nashville, tn & w 51-9 \\
5 & october 17 & mississippi valley state & eddie robinson stadium • grambling, la & w 45-14 \\
6 & october 24 & at jackson state & mississippi veterans memorial stadium • jackson, ms & l 17-31 \\
7 & october 31 & texas southern & eddie robinson stadium • grambling, la & w 30-9 \\
8 & november 7 & at alabama state & cramton bowl • montgomery, al & l 7-17 \\
9 & november 14 & south carolina state & eddie robinson stadium • grambling, la & l 13-15 \\
10 & november 28 & vs. southern & louisiana superdome • new orleans, la (xiv bayou classic) & l 21-27 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where date = 'october 24' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>opponent</th>
<th>site</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>september 5</td>
<td>alcorn state</td>
<td>independence stadium • shreveport. la</td>
<td>l 24-28</td>
</tr>
<tr>
<th>1</th>
<td>september 12</td>
<td>vs. central state</td>
<td>yankee stadium • new york, ny</td>
<td>l 21-37</td>
</tr>
<tr>
<th>2</th>
<td>september 26</td>
<td>bethune-cookman</td>
<td>eddie robinson stadium • grambling, la</td>
<td>w 21-14</td>
</tr>
<tr>
<th>3</th>
<td>october 3</td>
<td>vs. prairie view a&m</td>
<td>cotton bowl • dallas, tx</td>
<td>w 28-7</td>
</tr>
<tr>
<th>4</th>
<td>october 10</td>
<td>at tennessee state</td>
<td>dudley field • nashville, tn</td>
<td>w 51-9</td>
</tr>
<tr>
<th>5</th>
<td>october 17</td>
<td>mississippi valley state</td>
<td>eddie robinson stadium • grambling, la</td>
<td>w 45-14</td>
</tr>
<tr>
<th>6</th>
<td>october 24</td>
<td>at jackson state</td>
<td>mississippi veterans memorial stadium • jackson, ms</td>
<td>l 17-31</td>
</tr>
<tr>
<th>7</th>
<td>october 31</td>
<td>texas southern</td>
<td>eddie robinson stadium • grambling, la</td>
<td>w 30-9</td>
</tr>
<tr>
<th>8</th>
<td>november 7</td>
<td>at alabama state</td>
<td>cramton bowl • montgomery, al</td>
<td>l 7-17</td>
</tr>
<tr>
<th>9</th>
<td>november 14</td>
<td>south carolina state</td>
<td>eddie robinson stadium • grambling, la</td>
<td>l 13-15</td>
</tr>
<tr>
<th>10</th>
<td>november 28</td>
<td>vs. southern</td>
<td>louisiana superdome • new orleans, la (xiv bayou classic)</td>
<td>l 21-27</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where date = 'october 24' <table_name> : table | | date | opponent | site | result |
|---:|:-------------|:-------------------------|:----------------------------------------------------------|:---------|
| 0 | september 5 | alcorn state | independence stadium • shreveport. la | l 24-28 |
| 1 | september 12 | vs. central state | yankee stadium • new york, ny | l 21-37 |
| 2 | september 26 | bethune-cookman | eddie robinson stadium • grambling, la | w 21-14 |
| 3 | october 3 | vs. prairie view a&m | cotton bowl • dallas, tx | w 28-7 |
| 4 | october 10 | at tennessee state | dudley field • nashville, tn | w 51-9 |
| 5 | october 17 | mississippi valley state | eddie robinson stadium • grambling, la | w 45-14 |
| 6 | october 24 | at jackson state | mississippi veterans memorial stadium • jackson, ms | l 17-31 |
| 7 | october 31 | texas southern | eddie robinson stadium • grambling, la | w 30-9 |
| 8 | november 7 | at alabama state | cramton bowl • montgomery, al | l 7-17 |
| 9 | november 14 | south carolina state | eddie robinson stadium • grambling, la | l 13-15 |
| 10 | november 28 | vs. southern | louisiana superdome • new orleans, la (xiv bayou classic) | l 21-27 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select pick # where position = 'left wing' col : pick # | player | position | nationality | nhl team | college/junior/club team row 1 : 123 | paul ames | defence | united states | pittsburgh penguins | billerica high school (ushs-ma) row 2 : 124 | joe reekie | defence | canada | hartford whalers | north bay centennials (ohl) row 3 : 125 | greg evtushevski | right wing | canada | new jersey devils | kamloops blazers (whl) row 4 : 126 | bob pierson | left wing | canada | detroit red wings | london knights (ohl) row 5 : 127 | tim burgess | defence | canada | los angeles kings | oshawa generals (ohl) row 6 : 128 | cam plante | defence | canada | toronto maple leafs | brandon wheat kings (whl) row 7 : 129 | iain duncan | left wing | canada | winnipeg jets | north york rangers (ojhl) row 8 : 130 | terry maki | left wing | canada | vancouver canucks | brantford alexanders (ohl) row 9 : 131 | jeff hogg | goaltender | canada | calgary flames | oshawa generals (ohl) row 10 : 132 | craig mack | defence | united states | quebec nordiques | east grand forks high school (ushs-mn) row 11 : 133 | steve orth | centre | united states | new york rangers | st. cloud state university (wcha) row 12 : 134 | christian ruuttu | centre | finland | buffalo sabres | pori (finland) row 13 : 135 | dwaine hutton | centre | canada | washington capitals | kelowna wings (whl) row 14 : 136 | sean toomey | left wing | united states | minnesota north stars | cretin-derham hall high school (ushs-mn) row 15 : 137 | jim sprenger | defence | united states | new york islanders | cloquet high school (ushs-mn) row 16 : 138 | vladislav tretiak | goaltender | soviet union | montreal canadiens | moscow cska (ussr) row 17 : 139 | scott birnie | rignt wing | canada | chicago black hawks | cornwall royals (ohl) row 18 : 140 | dale derkatch | centre | canada | edmonton oilers | regina pats (whl) row 19 : 141 | bob mormina | right wing | canada | philadelphia flyers | longueuil chevaliers (qmjhl) row 20 : 142 | ian armstrong | defence | canada | boston bruins | peterborough petes (ohl) | col : pick # row 1 : 126 row 2 : 129 row 3 : 130 row 4 : 136 | select pick # where position = 'left wing' <table_name> : table \begin{tabular}{lllllll}
\toprule
& pick # & player & position & nationality & nhl team & college/junior/club team \\
\midrule
0 & 123 & paul ames & defence & united states & pittsburgh penguins & billerica high school (ushs-ma) \\
1 & 124 & joe reekie & defence & canada & hartford whalers & north bay centennials (ohl) \\
2 & 125 & greg evtushevski & right wing & canada & new jersey devils & kamloops blazers (whl) \\
3 & 126 & bob pierson & left wing & canada & detroit red wings & london knights (ohl) \\
4 & 127 & tim burgess & defence & canada & los angeles kings & oshawa generals (ohl) \\
5 & 128 & cam plante & defence & canada & toronto maple leafs & brandon wheat kings (whl) \\
6 & 129 & iain duncan & left wing & canada & winnipeg jets & north york rangers (ojhl) \\
7 & 130 & terry maki & left wing & canada & vancouver canucks & brantford alexanders (ohl) \\
8 & 131 & jeff hogg & goaltender & canada & calgary flames & oshawa generals (ohl) \\
9 & 132 & craig mack & defence & united states & quebec nordiques & east grand forks high school (ushs-mn) \\
10 & 133 & steve orth & centre & united states & new york rangers & st. cloud state university (wcha) \\
11 & 134 & christian ruuttu & centre & finland & buffalo sabres & pori (finland) \\
12 & 135 & dwaine hutton & centre & canada & washington capitals & kelowna wings (whl) \\
13 & 136 & sean toomey & left wing & united states & minnesota north stars & cretin-derham hall high school (ushs-mn) \\
14 & 137 & jim sprenger & defence & united states & new york islanders & cloquet high school (ushs-mn) \\
15 & 138 & vladislav tretiak & goaltender & soviet union & montreal canadiens & moscow cska (ussr) \\
16 & 139 & scott birnie & rignt wing & canada & chicago black hawks & cornwall royals (ohl) \\
17 & 140 & dale derkatch & centre & canada & edmonton oilers & regina pats (whl) \\
18 & 141 & bob mormina & right wing & canada & philadelphia flyers & longueuil chevaliers (qmjhl) \\
19 & 142 & ian armstrong & defence & canada & boston bruins & peterborough petes (ohl) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& pick # \\
\midrule
0 & 126 \\
1 & 129 \\
2 & 130 \\
3 & 136 \\
\bottomrule
\end{tabular}
| select pick # where position = 'left wing' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pick #</th>
<th>player</th>
<th>position</th>
<th>nationality</th>
<th>nhl team</th>
<th>college/junior/club team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>123</td>
<td>paul ames</td>
<td>defence</td>
<td>united states</td>
<td>pittsburgh penguins</td>
<td>billerica high school (ushs-ma)</td>
</tr>
<tr>
<th>1</th>
<td>124</td>
<td>joe reekie</td>
<td>defence</td>
<td>canada</td>
<td>hartford whalers</td>
<td>north bay centennials (ohl)</td>
</tr>
<tr>
<th>2</th>
<td>125</td>
<td>greg evtushevski</td>
<td>right wing</td>
<td>canada</td>
<td>new jersey devils</td>
<td>kamloops blazers (whl)</td>
</tr>
<tr>
<th>3</th>
<td>126</td>
<td>bob pierson</td>
<td>left wing</td>
<td>canada</td>
<td>detroit red wings</td>
<td>london knights (ohl)</td>
</tr>
<tr>
<th>4</th>
<td>127</td>
<td>tim burgess</td>
<td>defence</td>
<td>canada</td>
<td>los angeles kings</td>
<td>oshawa generals (ohl)</td>
</tr>
<tr>
<th>5</th>
<td>128</td>
<td>cam plante</td>
<td>defence</td>
<td>canada</td>
<td>toronto maple leafs</td>
<td>brandon wheat kings (whl)</td>
</tr>
<tr>
<th>6</th>
<td>129</td>
<td>iain duncan</td>
<td>left wing</td>
<td>canada</td>
<td>winnipeg jets</td>
<td>north york rangers (ojhl)</td>
</tr>
<tr>
<th>7</th>
<td>130</td>
<td>terry maki</td>
<td>left wing</td>
<td>canada</td>
<td>vancouver canucks</td>
<td>brantford alexanders (ohl)</td>
</tr>
<tr>
<th>8</th>
<td>131</td>
<td>jeff hogg</td>
<td>goaltender</td>
<td>canada</td>
<td>calgary flames</td>
<td>oshawa generals (ohl)</td>
</tr>
<tr>
<th>9</th>
<td>132</td>
<td>craig mack</td>
<td>defence</td>
<td>united states</td>
<td>quebec nordiques</td>
<td>east grand forks high school (ushs-mn)</td>
</tr>
<tr>
<th>10</th>
<td>133</td>
<td>steve orth</td>
<td>centre</td>
<td>united states</td>
<td>new york rangers</td>
<td>st. cloud state university (wcha)</td>
</tr>
<tr>
<th>11</th>
<td>134</td>
<td>christian ruuttu</td>
<td>centre</td>
<td>finland</td>
<td>buffalo sabres</td>
<td>pori (finland)</td>
</tr>
<tr>
<th>12</th>
<td>135</td>
<td>dwaine hutton</td>
<td>centre</td>
<td>canada</td>
<td>washington capitals</td>
<td>kelowna wings (whl)</td>
</tr>
<tr>
<th>13</th>
<td>136</td>
<td>sean toomey</td>
<td>left wing</td>
<td>united states</td>
<td>minnesota north stars</td>
<td>cretin-derham hall high school (ushs-mn)</td>
</tr>
<tr>
<th>14</th>
<td>137</td>
<td>jim sprenger</td>
<td>defence</td>
<td>united states</td>
<td>new york islanders</td>
<td>cloquet high school (ushs-mn)</td>
</tr>
<tr>
<th>15</th>
<td>138</td>
<td>vladislav tretiak</td>
<td>goaltender</td>
<td>soviet union</td>
<td>montreal canadiens</td>
<td>moscow cska (ussr)</td>
</tr>
<tr>
<th>16</th>
<td>139</td>
<td>scott birnie</td>
<td>rignt wing</td>
<td>canada</td>
<td>chicago black hawks</td>
<td>cornwall royals (ohl)</td>
</tr>
<tr>
<th>17</th>
<td>140</td>
<td>dale derkatch</td>
<td>centre</td>
<td>canada</td>
<td>edmonton oilers</td>
<td>regina pats (whl)</td>
</tr>
<tr>
<th>18</th>
<td>141</td>
<td>bob mormina</td>
<td>right wing</td>
<td>canada</td>
<td>philadelphia flyers</td>
<td>longueuil chevaliers (qmjhl)</td>
</tr>
<tr>
<th>19</th>
<td>142</td>
<td>ian armstrong</td>
<td>defence</td>
<td>canada</td>
<td>boston bruins</td>
<td>peterborough petes (ohl)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pick #</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>126</td>
</tr>
<tr>
<th>1</th>
<td>129</td>
</tr>
<tr>
<th>2</th>
<td>130</td>
</tr>
<tr>
<th>3</th>
<td>136</td>
</tr>
</tbody>
</table> | select pick # where position = 'left wing' <table_name> : table | | pick # | player | position | nationality | nhl team | college/junior/club team |
|---:|---------:|:------------------|:-----------|:--------------|:----------------------|:-----------------------------------------|
| 0 | 123 | paul ames | defence | united states | pittsburgh penguins | billerica high school (ushs-ma) |
| 1 | 124 | joe reekie | defence | canada | hartford whalers | north bay centennials (ohl) |
| 2 | 125 | greg evtushevski | right wing | canada | new jersey devils | kamloops blazers (whl) |
| 3 | 126 | bob pierson | left wing | canada | detroit red wings | london knights (ohl) |
| 4 | 127 | tim burgess | defence | canada | los angeles kings | oshawa generals (ohl) |
| 5 | 128 | cam plante | defence | canada | toronto maple leafs | brandon wheat kings (whl) |
| 6 | 129 | iain duncan | left wing | canada | winnipeg jets | north york rangers (ojhl) |
| 7 | 130 | terry maki | left wing | canada | vancouver canucks | brantford alexanders (ohl) |
| 8 | 131 | jeff hogg | goaltender | canada | calgary flames | oshawa generals (ohl) |
| 9 | 132 | craig mack | defence | united states | quebec nordiques | east grand forks high school (ushs-mn) |
| 10 | 133 | steve orth | centre | united states | new york rangers | st. cloud state university (wcha) |
| 11 | 134 | christian ruuttu | centre | finland | buffalo sabres | pori (finland) |
| 12 | 135 | dwaine hutton | centre | canada | washington capitals | kelowna wings (whl) |
| 13 | 136 | sean toomey | left wing | united states | minnesota north stars | cretin-derham hall high school (ushs-mn) |
| 14 | 137 | jim sprenger | defence | united states | new york islanders | cloquet high school (ushs-mn) |
| 15 | 138 | vladislav tretiak | goaltender | soviet union | montreal canadiens | moscow cska (ussr) |
| 16 | 139 | scott birnie | rignt wing | canada | chicago black hawks | cornwall royals (ohl) |
| 17 | 140 | dale derkatch | centre | canada | edmonton oilers | regina pats (whl) |
| 18 | 141 | bob mormina | right wing | canada | philadelphia flyers | longueuil chevaliers (qmjhl) |
| 19 | 142 | ian armstrong | defence | canada | boston bruins | peterborough petes (ohl) | | | | pick # |
|---:|---------:|
| 0 | 126 |
| 1 | 129 |
| 2 | 130 |
| 3 | 136 | | [
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select count ( manufacturer ) where pos = '+1:25.758' col : pos | rider | manufacturer | time/retired | points row 1 : 1 | loris capirossi | honda | 38:04.730 | 25 row 2 : 2 | valentino rossi | aprilia | 0.18 | 20 row 3 : 3 | jeremy mcwilliams | aprilia | 0.534 | 16 row 4 : 4 | tohru ukawa | honda | 0.537 | 13 row 5 : 5 | shinya nakano | yamaha | 0.742 | 11 row 6 : 6 | ralf waldmann | aprilia | 7.019 | 10 row 7 : 7 | franco battaini | aprilia | 20.889 | 9 row 8 : 8 | stefano perugini | honda | 20.891 | 8 row 9 : 9 | jason vincent | honda | 21.31 | 7 row 10 : 10 | anthony west | tsr-honda | 26.816 | 6 row 11 : 11 | alex hofmann | tsr-honda | 26.933 | 5 row 12 : 12 | sebastian porto | yamaha | 27.054 | 4 row 13 : 13 | tomomi manako | yamaha | 27.903 | 3 row 14 : 14 | masaki tokudome | tsr-honda | 33.161 | 2 row 15 : 15 | jarno janssen | tsr-honda | 56.248 | 1 row 16 : 16 | luca boscoscuro | tsr-honda | 56.432 | none row 17 : 17 | johann stigefelt | yamaha | +1:07.433 | none row 18 : 18 | julien allemand | tsr-honda | +1:16.347 | none row 19 : 19 | fonsi nieto | yamaha | +1:25.622 | none row 20 : 20 | lucas oliver bulto | yamaha | +1:25.758 | none row 21 : 21 | david garcia | yamaha | +1:33.867 | none row 22 : 22 | rudie markink | aprilia | +1:40.280 | none row 23 : 23 | arno visscher | aprilia | +1:40.635 | none row 24 : 24 | henk van de lagemaat | honda | +1 lap | none row 25 : ret | maurice bolwerk | tsr-honda | retirement | none row 26 : ret | andre romein | honda | retirement | none row 27 : ret | roberto rolfo | aprilia | retirement | none row 28 : ret | marcellino lucchi | aprilia | retirement | none | col : count ( "manufacturer" ) row 1 : 0 | select count ( manufacturer ) where pos = '+1:25.758' <table_name> : table \begin{tabular}{llllll}
\toprule
& pos & rider & manufacturer & time/retired & points \\
\midrule
0 & 1 & loris capirossi & honda & 38:04.730 & 25 \\
1 & 2 & valentino rossi & aprilia & 0.18 & 20 \\
2 & 3 & jeremy mcwilliams & aprilia & 0.534 & 16 \\
3 & 4 & tohru ukawa & honda & 0.537 & 13 \\
4 & 5 & shinya nakano & yamaha & 0.742 & 11 \\
5 & 6 & ralf waldmann & aprilia & 7.019 & 10 \\
6 & 7 & franco battaini & aprilia & 20.889 & 9 \\
7 & 8 & stefano perugini & honda & 20.891 & 8 \\
8 & 9 & jason vincent & honda & 21.31 & 7 \\
9 & 10 & anthony west & tsr-honda & 26.816 & 6 \\
10 & 11 & alex hofmann & tsr-honda & 26.933 & 5 \\
11 & 12 & sebastian porto & yamaha & 27.054 & 4 \\
12 & 13 & tomomi manako & yamaha & 27.903 & 3 \\
13 & 14 & masaki tokudome & tsr-honda & 33.161 & 2 \\
14 & 15 & jarno janssen & tsr-honda & 56.248 & 1 \\
15 & 16 & luca boscoscuro & tsr-honda & 56.432 & none \\
16 & 17 & johann stigefelt & yamaha & +1:07.433 & none \\
17 & 18 & julien allemand & tsr-honda & +1:16.347 & none \\
18 & 19 & fonsi nieto & yamaha & +1:25.622 & none \\
19 & 20 & lucas oliver bulto & yamaha & +1:25.758 & none \\
20 & 21 & david garcia & yamaha & +1:33.867 & none \\
21 & 22 & rudie markink & aprilia & +1:40.280 & none \\
22 & 23 & arno visscher & aprilia & +1:40.635 & none \\
23 & 24 & henk van de lagemaat & honda & +1 lap & none \\
24 & ret & maurice bolwerk & tsr-honda & retirement & none \\
25 & ret & andre romein & honda & retirement & none \\
26 & ret & roberto rolfo & aprilia & retirement & none \\
27 & ret & marcellino lucchi & aprilia & retirement & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "manufacturer" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( manufacturer ) where pos = '+1:25.758' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>rider</th>
<th>manufacturer</th>
<th>time/retired</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>loris capirossi</td>
<td>honda</td>
<td>38:04.730</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>valentino rossi</td>
<td>aprilia</td>
<td>0.18</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>jeremy mcwilliams</td>
<td>aprilia</td>
<td>0.534</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>tohru ukawa</td>
<td>honda</td>
<td>0.537</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>shinya nakano</td>
<td>yamaha</td>
<td>0.742</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>ralf waldmann</td>
<td>aprilia</td>
<td>7.019</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>franco battaini</td>
<td>aprilia</td>
<td>20.889</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>stefano perugini</td>
<td>honda</td>
<td>20.891</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>jason vincent</td>
<td>honda</td>
<td>21.31</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>anthony west</td>
<td>tsr-honda</td>
<td>26.816</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>alex hofmann</td>
<td>tsr-honda</td>
<td>26.933</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>sebastian porto</td>
<td>yamaha</td>
<td>27.054</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>tomomi manako</td>
<td>yamaha</td>
<td>27.903</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>masaki tokudome</td>
<td>tsr-honda</td>
<td>33.161</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>jarno janssen</td>
<td>tsr-honda</td>
<td>56.248</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>luca boscoscuro</td>
<td>tsr-honda</td>
<td>56.432</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>johann stigefelt</td>
<td>yamaha</td>
<td>+1:07.433</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>julien allemand</td>
<td>tsr-honda</td>
<td>+1:16.347</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>fonsi nieto</td>
<td>yamaha</td>
<td>+1:25.622</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>lucas oliver bulto</td>
<td>yamaha</td>
<td>+1:25.758</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>david garcia</td>
<td>yamaha</td>
<td>+1:33.867</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>rudie markink</td>
<td>aprilia</td>
<td>+1:40.280</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>arno visscher</td>
<td>aprilia</td>
<td>+1:40.635</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>henk van de lagemaat</td>
<td>honda</td>
<td>+1 lap</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>maurice bolwerk</td>
<td>tsr-honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>andre romein</td>
<td>honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>ret</td>
<td>roberto rolfo</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>ret</td>
<td>marcellino lucchi</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "manufacturer" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( manufacturer ) where pos = '+1:25.758' <table_name> : table | | pos | rider | manufacturer | time/retired | points |
|---:|:------|:---------------------|:---------------|:---------------|:---------|
| 0 | 1 | loris capirossi | honda | 38:04.730 | 25 |
| 1 | 2 | valentino rossi | aprilia | 0.18 | 20 |
| 2 | 3 | jeremy mcwilliams | aprilia | 0.534 | 16 |
| 3 | 4 | tohru ukawa | honda | 0.537 | 13 |
| 4 | 5 | shinya nakano | yamaha | 0.742 | 11 |
| 5 | 6 | ralf waldmann | aprilia | 7.019 | 10 |
| 6 | 7 | franco battaini | aprilia | 20.889 | 9 |
| 7 | 8 | stefano perugini | honda | 20.891 | 8 |
| 8 | 9 | jason vincent | honda | 21.31 | 7 |
| 9 | 10 | anthony west | tsr-honda | 26.816 | 6 |
| 10 | 11 | alex hofmann | tsr-honda | 26.933 | 5 |
| 11 | 12 | sebastian porto | yamaha | 27.054 | 4 |
| 12 | 13 | tomomi manako | yamaha | 27.903 | 3 |
| 13 | 14 | masaki tokudome | tsr-honda | 33.161 | 2 |
| 14 | 15 | jarno janssen | tsr-honda | 56.248 | 1 |
| 15 | 16 | luca boscoscuro | tsr-honda | 56.432 | none |
| 16 | 17 | johann stigefelt | yamaha | +1:07.433 | none |
| 17 | 18 | julien allemand | tsr-honda | +1:16.347 | none |
| 18 | 19 | fonsi nieto | yamaha | +1:25.622 | none |
| 19 | 20 | lucas oliver bulto | yamaha | +1:25.758 | none |
| 20 | 21 | david garcia | yamaha | +1:33.867 | none |
| 21 | 22 | rudie markink | aprilia | +1:40.280 | none |
| 22 | 23 | arno visscher | aprilia | +1:40.635 | none |
| 23 | 24 | henk van de lagemaat | honda | +1 lap | none |
| 24 | ret | maurice bolwerk | tsr-honda | retirement | none |
| 25 | ret | andre romein | honda | retirement | none |
| 26 | ret | roberto rolfo | aprilia | retirement | none |
| 27 | ret | marcellino lucchi | aprilia | retirement | none | | | | count ( "manufacturer" ) |
|---:|---------------------------:|
| 0 | 0 | | [
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select character where м > 'cyrillic small letter em' order by м limit 1 col : character | м -1 | м -2 | м -3 | м -4 row 1 : unicode name | cyrillic capital letter em | cyrillic capital letter em | cyrillic small letter em | cyrillic small letter em row 2 : encodings | decimal | hex | decimal | hex row 3 : unicode | 1052 | u+041c | 1084 | u+043c row 4 : utf-8 | 208 156 | d0 9c | 208 188 | d0 bc row 5 : numeric character reference | М | М | м | м row 6 : koi8-r and koi8-u | 237 | ed | 205 | cd row 7 : code page 855 | 211 | d3 | 210 | d2 row 8 : code page 866 | 140 | 8c | 172 | ac row 9 : windows-1251 | 204 | cc | 236 | ec row 10 : iso-8859-5 | 188 | bc | 220 | dc row 11 : macintosh cyrillic | 140 | 8c | 236 | ec | col : character row 1 : utf-8 | select character where м > 'cyrillic small letter em' order by м limit 1 <table_name> : table \begin{tabular}{llllll}
\toprule
& character & м -1 & м -2 & м -3 & м -4 \\
\midrule
0 & unicode name & cyrillic capital letter em & cyrillic capital letter em & cyrillic small letter em & cyrillic small letter em \\
1 & encodings & decimal & hex & decimal & hex \\
2 & unicode & 1052 & u+041c & 1084 & u+043c \\
3 & utf-8 & 208 156 & d0 9c & 208 188 & d0 bc \\
4 & numeric character reference & М & М & м & м \\
5 & koi8-r and koi8-u & 237 & ed & 205 & cd \\
6 & code page 855 & 211 & d3 & 210 & d2 \\
7 & code page 866 & 140 & 8c & 172 & ac \\
8 & windows-1251 & 204 & cc & 236 & ec \\
9 & iso-8859-5 & 188 & bc & 220 & dc \\
10 & macintosh cyrillic & 140 & 8c & 236 & ec \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& character \\
\midrule
0 & utf-8 \\
\bottomrule
\end{tabular}
| select character where м > 'cyrillic small letter em' order by м limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>character</th>
<th>м -1</th>
<th>м -2</th>
<th>м -3</th>
<th>м -4</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>unicode name</td>
<td>cyrillic capital letter em</td>
<td>cyrillic capital letter em</td>
<td>cyrillic small letter em</td>
<td>cyrillic small letter em</td>
</tr>
<tr>
<th>1</th>
<td>encodings</td>
<td>decimal</td>
<td>hex</td>
<td>decimal</td>
<td>hex</td>
</tr>
<tr>
<th>2</th>
<td>unicode</td>
<td>1052</td>
<td>u+041c</td>
<td>1084</td>
<td>u+043c</td>
</tr>
<tr>
<th>3</th>
<td>utf-8</td>
<td>208 156</td>
<td>d0 9c</td>
<td>208 188</td>
<td>d0 bc</td>
</tr>
<tr>
<th>4</th>
<td>numeric character reference</td>
<td>&#1052;</td>
<td>&#x41c;</td>
<td>&#1084;</td>
<td>&#x43c;</td>
</tr>
<tr>
<th>5</th>
<td>koi8-r and koi8-u</td>
<td>237</td>
<td>ed</td>
<td>205</td>
<td>cd</td>
</tr>
<tr>
<th>6</th>
<td>code page 855</td>
<td>211</td>
<td>d3</td>
<td>210</td>
<td>d2</td>
</tr>
<tr>
<th>7</th>
<td>code page 866</td>
<td>140</td>
<td>8c</td>
<td>172</td>
<td>ac</td>
</tr>
<tr>
<th>8</th>
<td>windows-1251</td>
<td>204</td>
<td>cc</td>
<td>236</td>
<td>ec</td>
</tr>
<tr>
<th>9</th>
<td>iso-8859-5</td>
<td>188</td>
<td>bc</td>
<td>220</td>
<td>dc</td>
</tr>
<tr>
<th>10</th>
<td>macintosh cyrillic</td>
<td>140</td>
<td>8c</td>
<td>236</td>
<td>ec</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>character</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>utf-8</td>
</tr>
</tbody>
</table> | select character where м > 'cyrillic small letter em' order by м limit 1 <table_name> : table | | character | м -1 | м -2 | м -3 | м -4 |
|---:|:----------------------------|:---------------------------|:---------------------------|:-------------------------|:-------------------------|
| 0 | unicode name | cyrillic capital letter em | cyrillic capital letter em | cyrillic small letter em | cyrillic small letter em |
| 1 | encodings | decimal | hex | decimal | hex |
| 2 | unicode | 1052 | u+041c | 1084 | u+043c |
| 3 | utf-8 | 208 156 | d0 9c | 208 188 | d0 bc |
| 4 | numeric character reference | М | М | м | м |
| 5 | koi8-r and koi8-u | 237 | ed | 205 | cd |
| 6 | code page 855 | 211 | d3 | 210 | d2 |
| 7 | code page 866 | 140 | 8c | 172 | ac |
| 8 | windows-1251 | 204 | cc | 236 | ec |
| 9 | iso-8859-5 | 188 | bc | 220 | dc |
| 10 | macintosh cyrillic | 140 | 8c | 236 | ec | | | | character |
|---:|:------------|
| 0 | utf-8 | | [
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select nation where nation = 'venezuela' order by nation asc limit 1 col : rank | nation | gold | silver | bronze | total row 1 : 1 | cuba | 4 | 3 | 2 | 9 row 2 : 2 | canada | 4 | 2 | 1 | 7 row 3 : 3 | united states | 2 | 0 | 2 | 4 row 4 : 4 | mexico | 1 | 1 | 0 | 2 row 5 : 5 | ecuador | 1 | 0 | 0 | 1 row 6 : 6 | argentina | 0 | 4 | 3 | 7 row 7 : 7 | brazil | 0 | 2 | 2 | 4 row 8 : 8 | chile | 0 | 0 | 1 | 1 row 9 : 8 | venezuela | 0 | 0 | 1 | 1 row 10 : total | total | 12 | 12 | 12 | 36 | col : nation row 1 : venezuela | select nation where nation = 'venezuela' order by nation asc limit 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & cuba & 4 & 3 & 2 & 9 \\
1 & 2 & canada & 4 & 2 & 1 & 7 \\
2 & 3 & united states & 2 & 0 & 2 & 4 \\
3 & 4 & mexico & 1 & 1 & 0 & 2 \\
4 & 5 & ecuador & 1 & 0 & 0 & 1 \\
5 & 6 & argentina & 0 & 4 & 3 & 7 \\
6 & 7 & brazil & 0 & 2 & 2 & 4 \\
7 & 8 & chile & 0 & 0 & 1 & 1 \\
8 & 8 & venezuela & 0 & 0 & 1 & 1 \\
9 & total & total & 12 & 12 & 12 & 36 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & venezuela \\
\bottomrule
\end{tabular}
| select nation where nation = 'venezuela' order by nation asc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>cuba</td>
<td>4</td>
<td>3</td>
<td>2</td>
<td>9</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>canada</td>
<td>4</td>
<td>2</td>
<td>1</td>
<td>7</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>united states</td>
<td>2</td>
<td>0</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>mexico</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>ecuador</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>argentina</td>
<td>0</td>
<td>4</td>
<td>3</td>
<td>7</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>brazil</td>
<td>0</td>
<td>2</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>chile</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>venezuela</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>total</td>
<td>total</td>
<td>12</td>
<td>12</td>
<td>12</td>
<td>36</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>venezuela</td>
</tr>
</tbody>
</table> | select nation where nation = 'venezuela' order by nation asc limit 1 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:--------------|-------:|---------:|---------:|--------:|
| 0 | 1 | cuba | 4 | 3 | 2 | 9 |
| 1 | 2 | canada | 4 | 2 | 1 | 7 |
| 2 | 3 | united states | 2 | 0 | 2 | 4 |
| 3 | 4 | mexico | 1 | 1 | 0 | 2 |
| 4 | 5 | ecuador | 1 | 0 | 0 | 1 |
| 5 | 6 | argentina | 0 | 4 | 3 | 7 |
| 6 | 7 | brazil | 0 | 2 | 2 | 4 |
| 7 | 8 | chile | 0 | 0 | 1 | 1 |
| 8 | 8 | venezuela | 0 | 0 | 1 | 1 |
| 9 | total | total | 12 | 12 | 12 | 36 | | | | nation |
|---:|:----------|
| 0 | venezuela | | [
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select count ( country ) where country = 'uk' col : name | year built | country | town | height | remarks row 1 : glacial aerial tramway kaprun iii | 1966 | austria | kaprun | 113.6 m | the tallest pylon is on the third section row 2 : mississippi aerial river transit | 1984 | usa | new orleans | 109 m | the tallest pylon on a gondola lift; on 87 m pile foundations; demolished 1994 row 3 : torre jaume i | 1931 | spain | barcelona | 107 m | intermediate stop of the harbour aerial tramway, also observation tower row 4 : gant hohtaelli aerial tramway | none | switzerland | zermatt | 94 m | one pylon row 5 : london emirates air line | early 2012 | uk | london | 88 m | north main tower. river thames aerial crossing between greenwich peninsular and royal docks row 6 : singapore cable car | 1972 | singapore | singapore | 88 m | pylon i row 7 : eibsee aerial tramway | 1962 | germany | garmisch-partenkirchen | 85 m | pylon ii row 8 : nizhny novgorod volga aerial tramway, tower 4 & 5 | 2012 | russia | nizhny novgorod | 82 m | none row 9 : mittersill goods aerial tramway | 1940s | austria | mittersill | 80 m | two pylons for a tramway that never went in service and was demolished in the 1950s. one of the pylons was built of timber, the other of steel row 10 : singapore cable car | 1972 | singapore | singapore | 80 m | pylon ii row 11 : 3s aerial tramway | 2004 | austria | kitzbuhel | 80 m | one pylon row 12 : torre sant sebastia | 1931 | spain | barcelona | 78 m | terminal of harbour aerial tramway row 13 : roosevelt island tramway | 1976 | usa | new york city | 76 m | central pylon of commuter tramway row 14 : wendelstein aerial tramway | 1970 | germany | bayerischzell-osterhofen | 75 m | none row 15 : vinpearl cable car | 2007 | vietnam | nha trang | 75 m | 7 pylons standing in the sea. total height from sea bed is 115 m row 16 : sandia peak tramway | 1965 | usa | albuquerque | 70.7 m | pylon 1, inclined at an angle of 18 degrees row 17 : eibsee aerial tramway | 1962 | germany | garmisch-partenkirchen | 65 m | pylon i | col : count ( "country" ) row 1 : 1 | select count ( country ) where country = 'uk' <table_name> : table \begin{tabular}{lllllll}
\toprule
& name & year built & country & town & height & remarks \\
\midrule
0 & glacial aerial tramway kaprun iii & 1966 & austria & kaprun & 113.6 m & the tallest pylon is on the third section \\
1 & mississippi aerial river transit & 1984 & usa & new orleans & 109 m & the tallest pylon on a gondola lift; on 87 m pile foundations; demolished 1994 \\
2 & torre jaume i & 1931 & spain & barcelona & 107 m & intermediate stop of the harbour aerial tramway, also observation tower \\
3 & gant hohtaelli aerial tramway & none & switzerland & zermatt & 94 m & one pylon \\
4 & london emirates air line & early 2012 & uk & london & 88 m & north main tower. river thames aerial crossing between greenwich peninsular and royal docks \\
5 & singapore cable car & 1972 & singapore & singapore & 88 m & pylon i \\
6 & eibsee aerial tramway & 1962 & germany & garmisch-partenkirchen & 85 m & pylon ii \\
7 & nizhny novgorod volga aerial tramway, tower 4 & 5 & 2012 & russia & nizhny novgorod & 82 m & none \\
8 & mittersill goods aerial tramway & 1940s & austria & mittersill & 80 m & two pylons for a tramway that never went in service and was demolished in the 1950s. one of the pylons was built of timber, the other of steel \\
9 & singapore cable car & 1972 & singapore & singapore & 80 m & pylon ii \\
10 & 3s aerial tramway & 2004 & austria & kitzbuhel & 80 m & one pylon \\
11 & torre sant sebastia & 1931 & spain & barcelona & 78 m & terminal of harbour aerial tramway \\
12 & roosevelt island tramway & 1976 & usa & new york city & 76 m & central pylon of commuter tramway \\
13 & wendelstein aerial tramway & 1970 & germany & bayerischzell-osterhofen & 75 m & none \\
14 & vinpearl cable car & 2007 & vietnam & nha trang & 75 m & 7 pylons standing in the sea. total height from sea bed is 115 m \\
15 & sandia peak tramway & 1965 & usa & albuquerque & 70.7 m & pylon 1, inclined at an angle of 18 degrees \\
16 & eibsee aerial tramway & 1962 & germany & garmisch-partenkirchen & 65 m & pylon i \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "country" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( country ) where country = 'uk' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>year built</th>
<th>country</th>
<th>town</th>
<th>height</th>
<th>remarks</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>glacial aerial tramway kaprun iii</td>
<td>1966</td>
<td>austria</td>
<td>kaprun</td>
<td>113.6 m</td>
<td>the tallest pylon is on the third section</td>
</tr>
<tr>
<th>1</th>
<td>mississippi aerial river transit</td>
<td>1984</td>
<td>usa</td>
<td>new orleans</td>
<td>109 m</td>
<td>the tallest pylon on a gondola lift; on 87 m pile foundations; demolished 1994</td>
</tr>
<tr>
<th>2</th>
<td>torre jaume i</td>
<td>1931</td>
<td>spain</td>
<td>barcelona</td>
<td>107 m</td>
<td>intermediate stop of the harbour aerial tramway, also observation tower</td>
</tr>
<tr>
<th>3</th>
<td>gant hohtaelli aerial tramway</td>
<td>none</td>
<td>switzerland</td>
<td>zermatt</td>
<td>94 m</td>
<td>one pylon</td>
</tr>
<tr>
<th>4</th>
<td>london emirates air line</td>
<td>early 2012</td>
<td>uk</td>
<td>london</td>
<td>88 m</td>
<td>north main tower. river thames aerial crossing between greenwich peninsular and royal docks</td>
</tr>
<tr>
<th>5</th>
<td>singapore cable car</td>
<td>1972</td>
<td>singapore</td>
<td>singapore</td>
<td>88 m</td>
<td>pylon i</td>
</tr>
<tr>
<th>6</th>
<td>eibsee aerial tramway</td>
<td>1962</td>
<td>germany</td>
<td>garmisch-partenkirchen</td>
<td>85 m</td>
<td>pylon ii</td>
</tr>
<tr>
<th>7</th>
<td>nizhny novgorod volga aerial tramway, tower 4 & 5</td>
<td>2012</td>
<td>russia</td>
<td>nizhny novgorod</td>
<td>82 m</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>mittersill goods aerial tramway</td>
<td>1940s</td>
<td>austria</td>
<td>mittersill</td>
<td>80 m</td>
<td>two pylons for a tramway that never went in service and was demolished in the 1950s. one of the pylons was built of timber, the other of steel</td>
</tr>
<tr>
<th>9</th>
<td>singapore cable car</td>
<td>1972</td>
<td>singapore</td>
<td>singapore</td>
<td>80 m</td>
<td>pylon ii</td>
</tr>
<tr>
<th>10</th>
<td>3s aerial tramway</td>
<td>2004</td>
<td>austria</td>
<td>kitzbuhel</td>
<td>80 m</td>
<td>one pylon</td>
</tr>
<tr>
<th>11</th>
<td>torre sant sebastia</td>
<td>1931</td>
<td>spain</td>
<td>barcelona</td>
<td>78 m</td>
<td>terminal of harbour aerial tramway</td>
</tr>
<tr>
<th>12</th>
<td>roosevelt island tramway</td>
<td>1976</td>
<td>usa</td>
<td>new york city</td>
<td>76 m</td>
<td>central pylon of commuter tramway</td>
</tr>
<tr>
<th>13</th>
<td>wendelstein aerial tramway</td>
<td>1970</td>
<td>germany</td>
<td>bayerischzell-osterhofen</td>
<td>75 m</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>vinpearl cable car</td>
<td>2007</td>
<td>vietnam</td>
<td>nha trang</td>
<td>75 m</td>
<td>7 pylons standing in the sea. total height from sea bed is 115 m</td>
</tr>
<tr>
<th>15</th>
<td>sandia peak tramway</td>
<td>1965</td>
<td>usa</td>
<td>albuquerque</td>
<td>70.7 m</td>
<td>pylon 1, inclined at an angle of 18 degrees</td>
</tr>
<tr>
<th>16</th>
<td>eibsee aerial tramway</td>
<td>1962</td>
<td>germany</td>
<td>garmisch-partenkirchen</td>
<td>65 m</td>
<td>pylon i</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "country" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( country ) where country = 'uk' <table_name> : table | | name | year built | country | town | height | remarks |
|---:|:--------------------------------------------------|:-------------|:------------|:-------------------------|:---------|:-----------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | glacial aerial tramway kaprun iii | 1966 | austria | kaprun | 113.6 m | the tallest pylon is on the third section |
| 1 | mississippi aerial river transit | 1984 | usa | new orleans | 109 m | the tallest pylon on a gondola lift; on 87 m pile foundations; demolished 1994 |
| 2 | torre jaume i | 1931 | spain | barcelona | 107 m | intermediate stop of the harbour aerial tramway, also observation tower |
| 3 | gant hohtaelli aerial tramway | none | switzerland | zermatt | 94 m | one pylon |
| 4 | london emirates air line | early 2012 | uk | london | 88 m | north main tower. river thames aerial crossing between greenwich peninsular and royal docks |
| 5 | singapore cable car | 1972 | singapore | singapore | 88 m | pylon i |
| 6 | eibsee aerial tramway | 1962 | germany | garmisch-partenkirchen | 85 m | pylon ii |
| 7 | nizhny novgorod volga aerial tramway, tower 4 & 5 | 2012 | russia | nizhny novgorod | 82 m | none |
| 8 | mittersill goods aerial tramway | 1940s | austria | mittersill | 80 m | two pylons for a tramway that never went in service and was demolished in the 1950s. one of the pylons was built of timber, the other of steel |
| 9 | singapore cable car | 1972 | singapore | singapore | 80 m | pylon ii |
| 10 | 3s aerial tramway | 2004 | austria | kitzbuhel | 80 m | one pylon |
| 11 | torre sant sebastia | 1931 | spain | barcelona | 78 m | terminal of harbour aerial tramway |
| 12 | roosevelt island tramway | 1976 | usa | new york city | 76 m | central pylon of commuter tramway |
| 13 | wendelstein aerial tramway | 1970 | germany | bayerischzell-osterhofen | 75 m | none |
| 14 | vinpearl cable car | 2007 | vietnam | nha trang | 75 m | 7 pylons standing in the sea. total height from sea bed is 115 m |
| 15 | sandia peak tramway | 1965 | usa | albuquerque | 70.7 m | pylon 1, inclined at an angle of 18 degrees |
| 16 | eibsee aerial tramway | 1962 | germany | garmisch-partenkirchen | 65 m | pylon i | | | | count ( "country" ) |
|---:|----------------------:|
| 0 | 1 | | [
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select count ( group ) where group = 'best actor on television' col : year | award | group | result | notes row 1 : 2004 | black reel awards | best actor: drama | nominated | the human stain (film) row 2 : 2004 | black reel awards | best breakthrough performance | nominated | the human stain (film) row 3 : 2006 | academy of science fiction, fantasy & horror films | best actor on television | nominated | prison break row 4 : 2006 | teen choice awards | tv - choice actor | nominated | prison break row 5 : 2006 | teen choice awards | tv - choice breakout star | nominated | prison break row 6 : 2006 | golden globes awards | best performance by an actor in a television series - drama | nominated | prison break row 7 : 2007 | teen choice awards | choice tv actor: drama | nominated | prison break row 8 : 2008 | teen choice awards | choice tv actor: action adventure | nominated | prison break row 9 : 2014 | fangoria chainsaw awards | best screenplay | pending | stoker (film) | col : count ( "group" ) row 1 : 1 | select count ( group ) where group = 'best actor on television' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & award & group & result & notes \\
\midrule
0 & 2004 & black reel awards & best actor: drama & nominated & the human stain (film) \\
1 & 2004 & black reel awards & best breakthrough performance & nominated & the human stain (film) \\
2 & 2006 & academy of science fiction, fantasy & horror films & best actor on television & nominated & prison break \\
3 & 2006 & teen choice awards & tv - choice actor & nominated & prison break \\
4 & 2006 & teen choice awards & tv - choice breakout star & nominated & prison break \\
5 & 2006 & golden globes awards & best performance by an actor in a television series - drama & nominated & prison break \\
6 & 2007 & teen choice awards & choice tv actor: drama & nominated & prison break \\
7 & 2008 & teen choice awards & choice tv actor: action adventure & nominated & prison break \\
8 & 2014 & fangoria chainsaw awards & best screenplay & pending & stoker (film) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "group" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( group ) where group = 'best actor on television' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>award</th>
<th>group</th>
<th>result</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004</td>
<td>black reel awards</td>
<td>best actor: drama</td>
<td>nominated</td>
<td>the human stain (film)</td>
</tr>
<tr>
<th>1</th>
<td>2004</td>
<td>black reel awards</td>
<td>best breakthrough performance</td>
<td>nominated</td>
<td>the human stain (film)</td>
</tr>
<tr>
<th>2</th>
<td>2006</td>
<td>academy of science fiction, fantasy & horror films</td>
<td>best actor on television</td>
<td>nominated</td>
<td>prison break</td>
</tr>
<tr>
<th>3</th>
<td>2006</td>
<td>teen choice awards</td>
<td>tv - choice actor</td>
<td>nominated</td>
<td>prison break</td>
</tr>
<tr>
<th>4</th>
<td>2006</td>
<td>teen choice awards</td>
<td>tv - choice breakout star</td>
<td>nominated</td>
<td>prison break</td>
</tr>
<tr>
<th>5</th>
<td>2006</td>
<td>golden globes awards</td>
<td>best performance by an actor in a television series - drama</td>
<td>nominated</td>
<td>prison break</td>
</tr>
<tr>
<th>6</th>
<td>2007</td>
<td>teen choice awards</td>
<td>choice tv actor: drama</td>
<td>nominated</td>
<td>prison break</td>
</tr>
<tr>
<th>7</th>
<td>2008</td>
<td>teen choice awards</td>
<td>choice tv actor: action adventure</td>
<td>nominated</td>
<td>prison break</td>
</tr>
<tr>
<th>8</th>
<td>2014</td>
<td>fangoria chainsaw awards</td>
<td>best screenplay</td>
<td>pending</td>
<td>stoker (film)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "group" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( group ) where group = 'best actor on television' <table_name> : table | | year | award | group | result | notes |
|---:|-------:|:---------------------------------------------------|:------------------------------------------------------------|:----------|:-----------------------|
| 0 | 2004 | black reel awards | best actor: drama | nominated | the human stain (film) |
| 1 | 2004 | black reel awards | best breakthrough performance | nominated | the human stain (film) |
| 2 | 2006 | academy of science fiction, fantasy & horror films | best actor on television | nominated | prison break |
| 3 | 2006 | teen choice awards | tv - choice actor | nominated | prison break |
| 4 | 2006 | teen choice awards | tv - choice breakout star | nominated | prison break |
| 5 | 2006 | golden globes awards | best performance by an actor in a television series - drama | nominated | prison break |
| 6 | 2007 | teen choice awards | choice tv actor: drama | nominated | prison break |
| 7 | 2008 | teen choice awards | choice tv actor: action adventure | nominated | prison break |
| 8 | 2014 | fangoria chainsaw awards | best screenplay | pending | stoker (film) | | | | count ( "group" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select count ( * ) where date = '19 october 2013' col : # | date | venue | opponent | score | result | competition row 1 : 1 | 2013-06-13 00:00:00 | zhejiang dragon sports centre, hangzhou | russia | 1 - 0 | 5 - 1 | friendly row 2 : 2 | 2013-06-13 00:00:00 | zhejiang dragon sports centre, hangzhou | russia | 3 - 0 | 5 - 1 | friendly row 3 : 3 | 2013-06-14 00:00:00 | zhejiang dragon sports centre, hangzhou | netherlands | none | 4 - 3 | friendly row 4 : 4 | 2013-06-14 00:00:00 | zhejiang dragon sports centre, hangzhou | netherlands | none | 4 - 3 | friendly row 5 : 5 | 2013-06-15 00:00:00 | zhejiang dragon sports centre, hangzhou | china | none | 5 - 2 | friendly row 6 : 6 | 2013-07-01 00:00:00 | songdo global university campus, incheon | iraq | 3 - 1 | 12 - 3 | 2013 asian indoor-martial arts games row 7 : 7 | 2013-07-01 00:00:00 | songdo global university campus, incheon | iraq | 4 - 1 | 12 - 3 | 2013 asian indoor-martial arts games row 8 : 8 | 2013-07-06 00:00:00 | songdo global university campus, incheon | japan | 5 - 2 | 5 - 2 | 2013 asian indoor-martial arts games row 9 : none | 2013-10-19 00:00:00 | sao keatano, brazil | bank | 3 - 0 | 3 - 0 | unofficial friendly row 10 : 9 | 2013-10-21 00:00:00 | maringa's futsal stadium, brazil | guatemala | none | 7 - 0 | friendly row 11 : 10 | 2013-10-23 00:00:00 | ginasio chico neto, maringa | argentina | 2 - 1 | 2 - 2 | 2013 grand prix de futsal | col : count ( "*" ) row 1 : 1 | select count ( * ) where date = '19 october 2013' <table_name> : table \begin{tabular}{llllllll}
\toprule
& # & date & venue & opponent & score & result & competition \\
\midrule
0 & 1 & 2013-06-13 00:00:00 & zhejiang dragon sports centre, hangzhou & russia & 1 - 0 & 5 - 1 & friendly \\
1 & 2 & 2013-06-13 00:00:00 & zhejiang dragon sports centre, hangzhou & russia & 3 - 0 & 5 - 1 & friendly \\
2 & 3 & 2013-06-14 00:00:00 & zhejiang dragon sports centre, hangzhou & netherlands & none & 4 - 3 & friendly \\
3 & 4 & 2013-06-14 00:00:00 & zhejiang dragon sports centre, hangzhou & netherlands & none & 4 - 3 & friendly \\
4 & 5 & 2013-06-15 00:00:00 & zhejiang dragon sports centre, hangzhou & china & none & 5 - 2 & friendly \\
5 & 6 & 2013-07-01 00:00:00 & songdo global university campus, incheon & iraq & 3 - 1 & 12 - 3 & 2013 asian indoor-martial arts games \\
6 & 7 & 2013-07-01 00:00:00 & songdo global university campus, incheon & iraq & 4 - 1 & 12 - 3 & 2013 asian indoor-martial arts games \\
7 & 8 & 2013-07-06 00:00:00 & songdo global university campus, incheon & japan & 5 - 2 & 5 - 2 & 2013 asian indoor-martial arts games \\
8 & none & 2013-10-19 00:00:00 & sao keatano, brazil & bank & 3 - 0 & 3 - 0 & unofficial friendly \\
9 & 9 & 2013-10-21 00:00:00 & maringa's futsal stadium, brazil & guatemala & none & 7 - 0 & friendly \\
10 & 10 & 2013-10-23 00:00:00 & ginasio chico neto, maringa & argentina & 2 - 1 & 2 - 2 & 2013 grand prix de futsal \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where date = '19 october 2013' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>date</th>
<th>venue</th>
<th>opponent</th>
<th>score</th>
<th>result</th>
<th>competition</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2013-06-13 00:00:00</td>
<td>zhejiang dragon sports centre, hangzhou</td>
<td>russia</td>
<td>1 - 0</td>
<td>5 - 1</td>
<td>friendly</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2013-06-13 00:00:00</td>
<td>zhejiang dragon sports centre, hangzhou</td>
<td>russia</td>
<td>3 - 0</td>
<td>5 - 1</td>
<td>friendly</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2013-06-14 00:00:00</td>
<td>zhejiang dragon sports centre, hangzhou</td>
<td>netherlands</td>
<td>none</td>
<td>4 - 3</td>
<td>friendly</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2013-06-14 00:00:00</td>
<td>zhejiang dragon sports centre, hangzhou</td>
<td>netherlands</td>
<td>none</td>
<td>4 - 3</td>
<td>friendly</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2013-06-15 00:00:00</td>
<td>zhejiang dragon sports centre, hangzhou</td>
<td>china</td>
<td>none</td>
<td>5 - 2</td>
<td>friendly</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2013-07-01 00:00:00</td>
<td>songdo global university campus, incheon</td>
<td>iraq</td>
<td>3 - 1</td>
<td>12 - 3</td>
<td>2013 asian indoor-martial arts games</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2013-07-01 00:00:00</td>
<td>songdo global university campus, incheon</td>
<td>iraq</td>
<td>4 - 1</td>
<td>12 - 3</td>
<td>2013 asian indoor-martial arts games</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2013-07-06 00:00:00</td>
<td>songdo global university campus, incheon</td>
<td>japan</td>
<td>5 - 2</td>
<td>5 - 2</td>
<td>2013 asian indoor-martial arts games</td>
</tr>
<tr>
<th>8</th>
<td>none</td>
<td>2013-10-19 00:00:00</td>
<td>sao keatano, brazil</td>
<td>bank</td>
<td>3 - 0</td>
<td>3 - 0</td>
<td>unofficial friendly</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>2013-10-21 00:00:00</td>
<td>maringa's futsal stadium, brazil</td>
<td>guatemala</td>
<td>none</td>
<td>7 - 0</td>
<td>friendly</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>2013-10-23 00:00:00</td>
<td>ginasio chico neto, maringa</td>
<td>argentina</td>
<td>2 - 1</td>
<td>2 - 2</td>
<td>2013 grand prix de futsal</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where date = '19 october 2013' <table_name> : table | | # | date | venue | opponent | score | result | competition |
|---:|:-----|:--------------------|:-----------------------------------------|:------------|:--------|:---------|:-------------------------------------|
| 0 | 1 | 2013-06-13 00:00:00 | zhejiang dragon sports centre, hangzhou | russia | 1 - 0 | 5 - 1 | friendly |
| 1 | 2 | 2013-06-13 00:00:00 | zhejiang dragon sports centre, hangzhou | russia | 3 - 0 | 5 - 1 | friendly |
| 2 | 3 | 2013-06-14 00:00:00 | zhejiang dragon sports centre, hangzhou | netherlands | none | 4 - 3 | friendly |
| 3 | 4 | 2013-06-14 00:00:00 | zhejiang dragon sports centre, hangzhou | netherlands | none | 4 - 3 | friendly |
| 4 | 5 | 2013-06-15 00:00:00 | zhejiang dragon sports centre, hangzhou | china | none | 5 - 2 | friendly |
| 5 | 6 | 2013-07-01 00:00:00 | songdo global university campus, incheon | iraq | 3 - 1 | 12 - 3 | 2013 asian indoor-martial arts games |
| 6 | 7 | 2013-07-01 00:00:00 | songdo global university campus, incheon | iraq | 4 - 1 | 12 - 3 | 2013 asian indoor-martial arts games |
| 7 | 8 | 2013-07-06 00:00:00 | songdo global university campus, incheon | japan | 5 - 2 | 5 - 2 | 2013 asian indoor-martial arts games |
| 8 | none | 2013-10-19 00:00:00 | sao keatano, brazil | bank | 3 - 0 | 3 - 0 | unofficial friendly |
| 9 | 9 | 2013-10-21 00:00:00 | maringa's futsal stadium, brazil | guatemala | none | 7 - 0 | friendly |
| 10 | 10 | 2013-10-23 00:00:00 | ginasio chico neto, maringa | argentina | 2 - 1 | 2 - 2 | 2013 grand prix de futsal | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select ime exchange (including spot, credit and forward transactions) where 2008/09 < 1672 col : ime exchange (including spot, credit and forward transactions) | 2007/08 | 2008/09 | 2009/10 | 2010/11 | 2011/12 row 1 : agricultural - volume (thousand tons) | 273.0 | 173.5 | 175.2 | 1633.9 | 550 row 2 : agricultural - value (billion rials) | 772.6 | 3729.7 | 484.8 | 3729.0 | 3793 row 3 : manufacturing and metal - volume (thousand tons) | 6443.8 | 6679.7 | 7438.5 | 8694.0 | 11685 row 4 : manufacturing and metal - value (billion rials) | 58044.2 | 62120.6 | 53842.0 | 75235.5 | 102356 row 5 : oil and petrochemical - volume (thousand tons) | 89.7 | 4339.2 | 7052.9 | 6662.6 | 8117 row 6 : oil and petrochemical - value (billion rials) | 352.7 | 19921.0 | 36450.7 | 41478.0 | 64370 row 7 : grand total - volume (thousand tons) | 6806.5 | 11192.4 | 14666.6 | 16990.5 | 20351 row 8 : grand total - value (billion rials) | 59169.4 | 82685.3 | 90777.5 | 120443.2 | 170519 | col : "ime exchange (including spot" row 1 : ime exchange (including spot | select ime exchange (including spot, credit and forward transactions) where 2008/09 < 1672 <table_name> : table \begin{tabular}{lllllll}
\toprule
& ime exchange (including spot, credit and forward transactions) & 2007/08 & 2008/09 & 2009/10 & 2010/11 & 2011/12 \\
\midrule
0 & agricultural - volume (thousand tons) & 273.0 & 173.5 & 175.2 & 1633.9 & 550 \\
1 & agricultural - value (billion rials) & 772.6 & 3729.7 & 484.8 & 3729.0 & 3793 \\
2 & manufacturing and metal - volume (thousand tons) & 6443.8 & 6679.7 & 7438.5 & 8694.0 & 11685 \\
3 & manufacturing and metal - value (billion rials) & 58044.2 & 62120.6 & 53842.0 & 75235.5 & 102356 \\
4 & oil and petrochemical - volume (thousand tons) & 89.7 & 4339.2 & 7052.9 & 6662.6 & 8117 \\
5 & oil and petrochemical - value (billion rials) & 352.7 & 19921.0 & 36450.7 & 41478.0 & 64370 \\
6 & grand total - volume (thousand tons) & 6806.5 & 11192.4 & 14666.6 & 16990.5 & 20351 \\
7 & grand total - value (billion rials) & 59169.4 & 82685.3 & 90777.5 & 120443.2 & 170519 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "ime exchange (including spot" \\
\midrule
0 & ime exchange (including spot \\
\bottomrule
\end{tabular}
| select ime exchange (including spot, credit and forward transactions) where 2008/09 < 1672 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>ime exchange (including spot, credit and forward transactions)</th>
<th>2007/08</th>
<th>2008/09</th>
<th>2009/10</th>
<th>2010/11</th>
<th>2011/12</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>agricultural - volume (thousand tons)</td>
<td>273.0</td>
<td>173.5</td>
<td>175.2</td>
<td>1633.9</td>
<td>550</td>
</tr>
<tr>
<th>1</th>
<td>agricultural - value (billion rials)</td>
<td>772.6</td>
<td>3729.7</td>
<td>484.8</td>
<td>3729.0</td>
<td>3793</td>
</tr>
<tr>
<th>2</th>
<td>manufacturing and metal - volume (thousand tons)</td>
<td>6443.8</td>
<td>6679.7</td>
<td>7438.5</td>
<td>8694.0</td>
<td>11685</td>
</tr>
<tr>
<th>3</th>
<td>manufacturing and metal - value (billion rials)</td>
<td>58044.2</td>
<td>62120.6</td>
<td>53842.0</td>
<td>75235.5</td>
<td>102356</td>
</tr>
<tr>
<th>4</th>
<td>oil and petrochemical - volume (thousand tons)</td>
<td>89.7</td>
<td>4339.2</td>
<td>7052.9</td>
<td>6662.6</td>
<td>8117</td>
</tr>
<tr>
<th>5</th>
<td>oil and petrochemical - value (billion rials)</td>
<td>352.7</td>
<td>19921.0</td>
<td>36450.7</td>
<td>41478.0</td>
<td>64370</td>
</tr>
<tr>
<th>6</th>
<td>grand total - volume (thousand tons)</td>
<td>6806.5</td>
<td>11192.4</td>
<td>14666.6</td>
<td>16990.5</td>
<td>20351</td>
</tr>
<tr>
<th>7</th>
<td>grand total - value (billion rials)</td>
<td>59169.4</td>
<td>82685.3</td>
<td>90777.5</td>
<td>120443.2</td>
<td>170519</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"ime exchange (including spot"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>ime exchange (including spot</td>
</tr>
</tbody>
</table> | select ime exchange (including spot, credit and forward transactions) where 2008/09 < 1672 <table_name> : table | | ime exchange (including spot, credit and forward transactions) | 2007/08 | 2008/09 | 2009/10 | 2010/11 | 2011/12 |
|---:|:-----------------------------------------------------------------|----------:|----------:|----------:|----------:|----------:|
| 0 | agricultural - volume (thousand tons) | 273 | 173.5 | 175.2 | 1633.9 | 550 |
| 1 | agricultural - value (billion rials) | 772.6 | 3729.7 | 484.8 | 3729 | 3793 |
| 2 | manufacturing and metal - volume (thousand tons) | 6443.8 | 6679.7 | 7438.5 | 8694 | 11685 |
| 3 | manufacturing and metal - value (billion rials) | 58044.2 | 62120.6 | 53842 | 75235.5 | 102356 |
| 4 | oil and petrochemical - volume (thousand tons) | 89.7 | 4339.2 | 7052.9 | 6662.6 | 8117 |
| 5 | oil and petrochemical - value (billion rials) | 352.7 | 19921 | 36450.7 | 41478 | 64370 |
| 6 | grand total - volume (thousand tons) | 6806.5 | 11192.4 | 14666.6 | 16990.5 | 20351 |
| 7 | grand total - value (billion rials) | 59169.4 | 82685.3 | 90777.5 | 120443 | 170519 | | | | "ime exchange (including spot" |
|---:|:---------------------------------|
| 0 | ime exchange (including spot | | [
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select parentage where parentage = 'reticulata × saluenensis' col : name | parentage | size | flower colour | flower type row 1 : cornish snow | cuspidata × saluenensis | 04.0m2 | white | single row 2 : cornish spring | cuspidata × saluenensis | 04.0m2 | pink | single row 3 : francie l | reticulata × saluenensis | 64.0m2 | rose-pink | double row 4 : freedom bell | × williamsii | 06.5m2 | red | semi-double row 5 : inspiration | reticulata × saluenensis | 10.0m2 | rose-pink | semi-double row 6 : leonard messel | reticulata × saluenensis | 16.0m2 | rose-pink | semi-double row 7 : royalty | japonica × reticulata | 01.0m2 | light red | semi-double row 8 : spring festival | × williamsii, cuspidata | 10.0m2 | pink | semi-double row 9 : tom knudsen | japonica × reticulata | 06.3m2 | deep red | double paeony row 10 : tristrem carlyon | reticulata | 10.0m2 | rose-pink | double paeony | col : parentage row 1 : reticulata × saluenensis row 2 : reticulata × saluenensis row 3 : reticulata × saluenensis | select parentage where parentage = 'reticulata × saluenensis' <table_name> : table \begin{tabular}{llllll}
\toprule
& name & parentage & size & flower colour & flower type \\
\midrule
0 & cornish snow & cuspidata × saluenensis & 04.0m2 & white & single \\
1 & cornish spring & cuspidata × saluenensis & 04.0m2 & pink & single \\
2 & francie l & reticulata × saluenensis & 64.0m2 & rose-pink & double \\
3 & freedom bell & × williamsii & 06.5m2 & red & semi-double \\
4 & inspiration & reticulata × saluenensis & 10.0m2 & rose-pink & semi-double \\
5 & leonard messel & reticulata × saluenensis & 16.0m2 & rose-pink & semi-double \\
6 & royalty & japonica × reticulata & 01.0m2 & light red & semi-double \\
7 & spring festival & × williamsii, cuspidata & 10.0m2 & pink & semi-double \\
8 & tom knudsen & japonica × reticulata & 06.3m2 & deep red & double paeony \\
9 & tristrem carlyon & reticulata & 10.0m2 & rose-pink & double paeony \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& parentage \\
\midrule
0 & reticulata × saluenensis \\
1 & reticulata × saluenensis \\
2 & reticulata × saluenensis \\
\bottomrule
\end{tabular}
| select parentage where parentage = 'reticulata × saluenensis' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>parentage</th>
<th>size</th>
<th>flower colour</th>
<th>flower type</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>cornish snow</td>
<td>cuspidata × saluenensis</td>
<td>04.0m2</td>
<td>white</td>
<td>single</td>
</tr>
<tr>
<th>1</th>
<td>cornish spring</td>
<td>cuspidata × saluenensis</td>
<td>04.0m2</td>
<td>pink</td>
<td>single</td>
</tr>
<tr>
<th>2</th>
<td>francie l</td>
<td>reticulata × saluenensis</td>
<td>64.0m2</td>
<td>rose-pink</td>
<td>double</td>
</tr>
<tr>
<th>3</th>
<td>freedom bell</td>
<td>× williamsii</td>
<td>06.5m2</td>
<td>red</td>
<td>semi-double</td>
</tr>
<tr>
<th>4</th>
<td>inspiration</td>
<td>reticulata × saluenensis</td>
<td>10.0m2</td>
<td>rose-pink</td>
<td>semi-double</td>
</tr>
<tr>
<th>5</th>
<td>leonard messel</td>
<td>reticulata × saluenensis</td>
<td>16.0m2</td>
<td>rose-pink</td>
<td>semi-double</td>
</tr>
<tr>
<th>6</th>
<td>royalty</td>
<td>japonica × reticulata</td>
<td>01.0m2</td>
<td>light red</td>
<td>semi-double</td>
</tr>
<tr>
<th>7</th>
<td>spring festival</td>
<td>× williamsii, cuspidata</td>
<td>10.0m2</td>
<td>pink</td>
<td>semi-double</td>
</tr>
<tr>
<th>8</th>
<td>tom knudsen</td>
<td>japonica × reticulata</td>
<td>06.3m2</td>
<td>deep red</td>
<td>double paeony</td>
</tr>
<tr>
<th>9</th>
<td>tristrem carlyon</td>
<td>reticulata</td>
<td>10.0m2</td>
<td>rose-pink</td>
<td>double paeony</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>parentage</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>reticulata × saluenensis</td>
</tr>
<tr>
<th>1</th>
<td>reticulata × saluenensis</td>
</tr>
<tr>
<th>2</th>
<td>reticulata × saluenensis</td>
</tr>
</tbody>
</table> | select parentage where parentage = 'reticulata × saluenensis' <table_name> : table | | name | parentage | size | flower colour | flower type |
|---:|:-----------------|:-------------------------|:-------|:----------------|:--------------|
| 0 | cornish snow | cuspidata × saluenensis | 04.0m2 | white | single |
| 1 | cornish spring | cuspidata × saluenensis | 04.0m2 | pink | single |
| 2 | francie l | reticulata × saluenensis | 64.0m2 | rose-pink | double |
| 3 | freedom bell | × williamsii | 06.5m2 | red | semi-double |
| 4 | inspiration | reticulata × saluenensis | 10.0m2 | rose-pink | semi-double |
| 5 | leonard messel | reticulata × saluenensis | 16.0m2 | rose-pink | semi-double |
| 6 | royalty | japonica × reticulata | 01.0m2 | light red | semi-double |
| 7 | spring festival | × williamsii, cuspidata | 10.0m2 | pink | semi-double |
| 8 | tom knudsen | japonica × reticulata | 06.3m2 | deep red | double paeony |
| 9 | tristrem carlyon | reticulata | 10.0m2 | rose-pink | double paeony | | | | parentage |
|---:|:-------------------------|
| 0 | reticulata × saluenensis |
| 1 | reticulata × saluenensis |
| 2 | reticulata × saluenensis | | [
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select pos where constructor = 'mclaren-ford' and pos != 5 col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 1 | emerson fittipaldi | mclaren-ford | 53 | 1:39:26.29 | 5 | 9 row 2 : 2 | 24 | james hunt | hesketh-ford | 53 | + 5.91 | 6 | 6 row 3 : 3 | 7 | carlos reutemann | brabham-ford | 53 | + 17.06 | 3 | 4 row 4 : 4 | 11 | clay regazzoni | ferrari | 53 | + 35.79 | 7 | 3 row 5 : 5 | 4 | patrick depailler | tyrrell-ford | 53 | + 54.25 | 8 | 2 row 6 : 6 | 12 | niki lauda | ferrari | 53 | + 1:19.65 | 4 | 1 row 7 : 7 | 28 | mark donohue | penske-ford | 52 | + 1 lap | 16 | none row 8 : 8 | 6 | jacky ickx | lotus-ford | 52 | + 1 lap | 18 | none row 9 : 9 | 9 | vittorio brambilla | march-ford | 52 | + 1 lap | 12 | none row 10 : 10 | 22 | graham hill | lola-ford | 52 | + 1 lap | 21 | none row 11 : 11 | 3 | jody scheckter | tyrrell-ford | 52 | + 1 lap | 9 | none row 12 : 12 | 16 | tom pryce | shadow-ford | 51 | transmission | 14 | none row 13 : 13 | 23 | rolf stommelen | lola-ford | 51 | + 2 laps | 19 | none row 14 : 14 | 2 | jochen mass | mclaren-ford | 50 | + 3 laps | 13 | none row 15 : ret | 8 | carlos pace | brabham-ford | 46 | engine | 2 | none row 16 : nc | 20 | arturo merzario | williams-ford | 44 | not classified | 20 | none row 17 : ret | 27 | mario andretti | parnelli-ford | 27 | transmission | 10 | none row 18 : ret | 14 | mike wilds | brm | 24 | engine | 22 | none row 19 : ret | 5 | ronnie peterson | lotus-ford | 15 | engine | 11 | none row 20 : ret | 21 | jacques laffite | williams-ford | 15 | gearbox | 17 | none row 21 : ret | 30 | wilson fittipaldi | fittipaldi-ford | 12 | accident | 23 | none row 22 : dsq | 18 | john watson | surtees-ford | 6 | disqualified | 15 | none row 23 : dns | 17 | jean-pierre jarier | shadow-ford | 0 | transmission | 1 | none | col : pos row 1 : 1 row 2 : 14 | select pos where constructor = 'mclaren-ford' and pos != 5 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & constructor & laps & time/retired & grid & points \\
\midrule
0 & 1 & 1 & emerson fittipaldi & mclaren-ford & 53 & 1:39:26.29 & 5 & 9 \\
1 & 2 & 24 & james hunt & hesketh-ford & 53 & + 5.91 & 6 & 6 \\
2 & 3 & 7 & carlos reutemann & brabham-ford & 53 & + 17.06 & 3 & 4 \\
3 & 4 & 11 & clay regazzoni & ferrari & 53 & + 35.79 & 7 & 3 \\
4 & 5 & 4 & patrick depailler & tyrrell-ford & 53 & + 54.25 & 8 & 2 \\
5 & 6 & 12 & niki lauda & ferrari & 53 & + 1:19.65 & 4 & 1 \\
6 & 7 & 28 & mark donohue & penske-ford & 52 & + 1 lap & 16 & none \\
7 & 8 & 6 & jacky ickx & lotus-ford & 52 & + 1 lap & 18 & none \\
8 & 9 & 9 & vittorio brambilla & march-ford & 52 & + 1 lap & 12 & none \\
9 & 10 & 22 & graham hill & lola-ford & 52 & + 1 lap & 21 & none \\
10 & 11 & 3 & jody scheckter & tyrrell-ford & 52 & + 1 lap & 9 & none \\
11 & 12 & 16 & tom pryce & shadow-ford & 51 & transmission & 14 & none \\
12 & 13 & 23 & rolf stommelen & lola-ford & 51 & + 2 laps & 19 & none \\
13 & 14 & 2 & jochen mass & mclaren-ford & 50 & + 3 laps & 13 & none \\
14 & ret & 8 & carlos pace & brabham-ford & 46 & engine & 2 & none \\
15 & nc & 20 & arturo merzario & williams-ford & 44 & not classified & 20 & none \\
16 & ret & 27 & mario andretti & parnelli-ford & 27 & transmission & 10 & none \\
17 & ret & 14 & mike wilds & brm & 24 & engine & 22 & none \\
18 & ret & 5 & ronnie peterson & lotus-ford & 15 & engine & 11 & none \\
19 & ret & 21 & jacques laffite & williams-ford & 15 & gearbox & 17 & none \\
20 & ret & 30 & wilson fittipaldi & fittipaldi-ford & 12 & accident & 23 & none \\
21 & dsq & 18 & john watson & surtees-ford & 6 & disqualified & 15 & none \\
22 & dns & 17 & jean-pierre jarier & shadow-ford & 0 & transmission & 1 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& pos \\
\midrule
0 & 1 \\
1 & 14 \\
\bottomrule
\end{tabular}
| select pos where constructor = 'mclaren-ford' and pos != 5 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>no</th>
<th>driver</th>
<th>constructor</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1</td>
<td>emerson fittipaldi</td>
<td>mclaren-ford</td>
<td>53</td>
<td>1:39:26.29</td>
<td>5</td>
<td>9</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>24</td>
<td>james hunt</td>
<td>hesketh-ford</td>
<td>53</td>
<td>+ 5.91</td>
<td>6</td>
<td>6</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>7</td>
<td>carlos reutemann</td>
<td>brabham-ford</td>
<td>53</td>
<td>+ 17.06</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>11</td>
<td>clay regazzoni</td>
<td>ferrari</td>
<td>53</td>
<td>+ 35.79</td>
<td>7</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>4</td>
<td>patrick depailler</td>
<td>tyrrell-ford</td>
<td>53</td>
<td>+ 54.25</td>
<td>8</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>12</td>
<td>niki lauda</td>
<td>ferrari</td>
<td>53</td>
<td>+ 1:19.65</td>
<td>4</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>28</td>
<td>mark donohue</td>
<td>penske-ford</td>
<td>52</td>
<td>+ 1 lap</td>
<td>16</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>6</td>
<td>jacky ickx</td>
<td>lotus-ford</td>
<td>52</td>
<td>+ 1 lap</td>
<td>18</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>9</td>
<td>vittorio brambilla</td>
<td>march-ford</td>
<td>52</td>
<td>+ 1 lap</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>22</td>
<td>graham hill</td>
<td>lola-ford</td>
<td>52</td>
<td>+ 1 lap</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>3</td>
<td>jody scheckter</td>
<td>tyrrell-ford</td>
<td>52</td>
<td>+ 1 lap</td>
<td>9</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>16</td>
<td>tom pryce</td>
<td>shadow-ford</td>
<td>51</td>
<td>transmission</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>23</td>
<td>rolf stommelen</td>
<td>lola-ford</td>
<td>51</td>
<td>+ 2 laps</td>
<td>19</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>2</td>
<td>jochen mass</td>
<td>mclaren-ford</td>
<td>50</td>
<td>+ 3 laps</td>
<td>13</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>ret</td>
<td>8</td>
<td>carlos pace</td>
<td>brabham-ford</td>
<td>46</td>
<td>engine</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>nc</td>
<td>20</td>
<td>arturo merzario</td>
<td>williams-ford</td>
<td>44</td>
<td>not classified</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>ret</td>
<td>27</td>
<td>mario andretti</td>
<td>parnelli-ford</td>
<td>27</td>
<td>transmission</td>
<td>10</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>ret</td>
<td>14</td>
<td>mike wilds</td>
<td>brm</td>
<td>24</td>
<td>engine</td>
<td>22</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>5</td>
<td>ronnie peterson</td>
<td>lotus-ford</td>
<td>15</td>
<td>engine</td>
<td>11</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>21</td>
<td>jacques laffite</td>
<td>williams-ford</td>
<td>15</td>
<td>gearbox</td>
<td>17</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>ret</td>
<td>30</td>
<td>wilson fittipaldi</td>
<td>fittipaldi-ford</td>
<td>12</td>
<td>accident</td>
<td>23</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>dsq</td>
<td>18</td>
<td>john watson</td>
<td>surtees-ford</td>
<td>6</td>
<td>disqualified</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>dns</td>
<td>17</td>
<td>jean-pierre jarier</td>
<td>shadow-ford</td>
<td>0</td>
<td>transmission</td>
<td>1</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
<tr>
<th>1</th>
<td>14</td>
</tr>
</tbody>
</table> | select pos where constructor = 'mclaren-ford' and pos != 5 <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points |
|---:|:------|-----:|:-------------------|:----------------|-------:|:---------------|-------:|:---------|
| 0 | 1 | 1 | emerson fittipaldi | mclaren-ford | 53 | 1:39:26.29 | 5 | 9 |
| 1 | 2 | 24 | james hunt | hesketh-ford | 53 | + 5.91 | 6 | 6 |
| 2 | 3 | 7 | carlos reutemann | brabham-ford | 53 | + 17.06 | 3 | 4 |
| 3 | 4 | 11 | clay regazzoni | ferrari | 53 | + 35.79 | 7 | 3 |
| 4 | 5 | 4 | patrick depailler | tyrrell-ford | 53 | + 54.25 | 8 | 2 |
| 5 | 6 | 12 | niki lauda | ferrari | 53 | + 1:19.65 | 4 | 1 |
| 6 | 7 | 28 | mark donohue | penske-ford | 52 | + 1 lap | 16 | none |
| 7 | 8 | 6 | jacky ickx | lotus-ford | 52 | + 1 lap | 18 | none |
| 8 | 9 | 9 | vittorio brambilla | march-ford | 52 | + 1 lap | 12 | none |
| 9 | 10 | 22 | graham hill | lola-ford | 52 | + 1 lap | 21 | none |
| 10 | 11 | 3 | jody scheckter | tyrrell-ford | 52 | + 1 lap | 9 | none |
| 11 | 12 | 16 | tom pryce | shadow-ford | 51 | transmission | 14 | none |
| 12 | 13 | 23 | rolf stommelen | lola-ford | 51 | + 2 laps | 19 | none |
| 13 | 14 | 2 | jochen mass | mclaren-ford | 50 | + 3 laps | 13 | none |
| 14 | ret | 8 | carlos pace | brabham-ford | 46 | engine | 2 | none |
| 15 | nc | 20 | arturo merzario | williams-ford | 44 | not classified | 20 | none |
| 16 | ret | 27 | mario andretti | parnelli-ford | 27 | transmission | 10 | none |
| 17 | ret | 14 | mike wilds | brm | 24 | engine | 22 | none |
| 18 | ret | 5 | ronnie peterson | lotus-ford | 15 | engine | 11 | none |
| 19 | ret | 21 | jacques laffite | williams-ford | 15 | gearbox | 17 | none |
| 20 | ret | 30 | wilson fittipaldi | fittipaldi-ford | 12 | accident | 23 | none |
| 21 | dsq | 18 | john watson | surtees-ford | 6 | disqualified | 15 | none |
| 22 | dns | 17 | jean-pierre jarier | shadow-ford | 0 | transmission | 1 | none | | | | pos |
|---:|------:|
| 0 | 1 |
| 1 | 14 | | [
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] |
select count ( * ) where retired = 'running' col : year | car | start | qual | rank | finish | laps | led | retired row 1 : 1956 | 14 | 23 | 142.535 | 16 | 7 | 200 | 0 | running row 2 : 1957 | 7 | 16 | 141.016 | 19 | 9 | 200 | 0 | running row 3 : 1958 | 14 | 4 | 144.881 | 4 | 26 | 1 | 0 | crash t3 row 4 : 1959 | 74 | 7 | 144.023 | 8 | 12 | 200 | 0 | running row 5 : 1960 | 44 | 25 | 143.363 | 23 | 8 | 200 | 0 | running row 6 : 1962 | 96 | 19 | 146.157 | 32 | 33 | 12 | 0 | engine row 7 : 1963 | 86 | 24 | 148.289 | 26 | 26 | 74 | 0 | valve row 8 : 1964 | 54 | 23 | 153.381 | 10 | 19 | 88 | 0 | piston row 9 : 1965 | 54 | 10 | 156.427 | 11 | 24 | 58 | 0 | piston row 10 : 1967 | 46 | 28 | 162.58 | 32 | 11 | 189 | 0 | flagged row 11 : 1968 | 16 | 24 | 163.495 | 24 | 11 | 196 | 0 | flagged row 12 : totals | totals | totals | totals | totals | totals | 1418 | 0 | none | col : count ( "*" ) row 1 : 4 | select count ( * ) where retired = 'running' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& year & car & start & qual & rank & finish & laps & led & retired \\
\midrule
0 & 1956 & 14 & 23 & 142.535 & 16 & 7 & 200 & 0 & running \\
1 & 1957 & 7 & 16 & 141.016 & 19 & 9 & 200 & 0 & running \\
2 & 1958 & 14 & 4 & 144.881 & 4 & 26 & 1 & 0 & crash t3 \\
3 & 1959 & 74 & 7 & 144.023 & 8 & 12 & 200 & 0 & running \\
4 & 1960 & 44 & 25 & 143.363 & 23 & 8 & 200 & 0 & running \\
5 & 1962 & 96 & 19 & 146.157 & 32 & 33 & 12 & 0 & engine \\
6 & 1963 & 86 & 24 & 148.289 & 26 & 26 & 74 & 0 & valve \\
7 & 1964 & 54 & 23 & 153.381 & 10 & 19 & 88 & 0 & piston \\
8 & 1965 & 54 & 10 & 156.427 & 11 & 24 & 58 & 0 & piston \\
9 & 1967 & 46 & 28 & 162.58 & 32 & 11 & 189 & 0 & flagged \\
10 & 1968 & 16 & 24 & 163.495 & 24 & 11 & 196 & 0 & flagged \\
11 & totals & totals & totals & totals & totals & totals & 1418 & 0 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( * ) where retired = 'running' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>car</th>
<th>start</th>
<th>qual</th>
<th>rank</th>
<th>finish</th>
<th>laps</th>
<th>led</th>
<th>retired</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1956</td>
<td>14</td>
<td>23</td>
<td>142.535</td>
<td>16</td>
<td>7</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>1</th>
<td>1957</td>
<td>7</td>
<td>16</td>
<td>141.016</td>
<td>19</td>
<td>9</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>2</th>
<td>1958</td>
<td>14</td>
<td>4</td>
<td>144.881</td>
<td>4</td>
<td>26</td>
<td>1</td>
<td>0</td>
<td>crash t3</td>
</tr>
<tr>
<th>3</th>
<td>1959</td>
<td>74</td>
<td>7</td>
<td>144.023</td>
<td>8</td>
<td>12</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>4</th>
<td>1960</td>
<td>44</td>
<td>25</td>
<td>143.363</td>
<td>23</td>
<td>8</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>5</th>
<td>1962</td>
<td>96</td>
<td>19</td>
<td>146.157</td>
<td>32</td>
<td>33</td>
<td>12</td>
<td>0</td>
<td>engine</td>
</tr>
<tr>
<th>6</th>
<td>1963</td>
<td>86</td>
<td>24</td>
<td>148.289</td>
<td>26</td>
<td>26</td>
<td>74</td>
<td>0</td>
<td>valve</td>
</tr>
<tr>
<th>7</th>
<td>1964</td>
<td>54</td>
<td>23</td>
<td>153.381</td>
<td>10</td>
<td>19</td>
<td>88</td>
<td>0</td>
<td>piston</td>
</tr>
<tr>
<th>8</th>
<td>1965</td>
<td>54</td>
<td>10</td>
<td>156.427</td>
<td>11</td>
<td>24</td>
<td>58</td>
<td>0</td>
<td>piston</td>
</tr>
<tr>
<th>9</th>
<td>1967</td>
<td>46</td>
<td>28</td>
<td>162.58</td>
<td>32</td>
<td>11</td>
<td>189</td>
<td>0</td>
<td>flagged</td>
</tr>
<tr>
<th>10</th>
<td>1968</td>
<td>16</td>
<td>24</td>
<td>163.495</td>
<td>24</td>
<td>11</td>
<td>196</td>
<td>0</td>
<td>flagged</td>
</tr>
<tr>
<th>11</th>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>1418</td>
<td>0</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select count ( * ) where retired = 'running' <table_name> : table | | year | car | start | qual | rank | finish | laps | led | retired |
|---:|:-------|:-------|:--------|:--------|:-------|:---------|-------:|------:|:----------|
| 0 | 1956 | 14 | 23 | 142.535 | 16 | 7 | 200 | 0 | running |
| 1 | 1957 | 7 | 16 | 141.016 | 19 | 9 | 200 | 0 | running |
| 2 | 1958 | 14 | 4 | 144.881 | 4 | 26 | 1 | 0 | crash t3 |
| 3 | 1959 | 74 | 7 | 144.023 | 8 | 12 | 200 | 0 | running |
| 4 | 1960 | 44 | 25 | 143.363 | 23 | 8 | 200 | 0 | running |
| 5 | 1962 | 96 | 19 | 146.157 | 32 | 33 | 12 | 0 | engine |
| 6 | 1963 | 86 | 24 | 148.289 | 26 | 26 | 74 | 0 | valve |
| 7 | 1964 | 54 | 23 | 153.381 | 10 | 19 | 88 | 0 | piston |
| 8 | 1965 | 54 | 10 | 156.427 | 11 | 24 | 58 | 0 | piston |
| 9 | 1967 | 46 | 28 | 162.58 | 32 | 11 | 189 | 0 | flagged |
| 10 | 1968 | 16 | 24 | 163.495 | 24 | 11 | 196 | 0 | flagged |
| 11 | totals | totals | totals | totals | totals | totals | 1418 | 0 | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 4 | | [
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select count ( left office ) where left office = '8' col : # | menteri besar | took office | left office | party row 1 : 1 | jaafar mohamed | 1886 | july 1890 | no party row 2 : 2 | mohamed mahbob | june 1920 | 1922 | no party row 3 : 3 | abdullah jaafar | september 1923 | 1928 | no party row 4 : 4 | mustapha jaafar | september 16, 1928 | november 23, 1931 | no party row 5 : 5 | abdul hamid yusof | november 23, 1931 | december 28, 1934 | no party row 6 : 6 | ungku abdul aziz abdul majid | april 1935 | june 1, 1947 | no party row 7 : 7 | onn jaafar | june 1, 1947 | may 18, 1950 | no party row 8 : 8 | syed abdul kadir mohamed | february 18, 1952 | june 5, 1955 | no party row 9 : 9 | wan idris ibrahim | october 1, 1955 | august 31, 1957 | no party | col : count ( "left office" ) row 1 : 0 | select count ( left office ) where left office = '8' <table_name> : table \begin{tabular}{llllll}
\toprule
& # & menteri besar & took office & left office & party \\
\midrule
0 & 1 & jaafar mohamed & 1886 & july 1890 & no party \\
1 & 2 & mohamed mahbob & june 1920 & 1922 & no party \\
2 & 3 & abdullah jaafar & september 1923 & 1928 & no party \\
3 & 4 & mustapha jaafar & september 16, 1928 & november 23, 1931 & no party \\
4 & 5 & abdul hamid yusof & november 23, 1931 & december 28, 1934 & no party \\
5 & 6 & ungku abdul aziz abdul majid & april 1935 & june 1, 1947 & no party \\
6 & 7 & onn jaafar & june 1, 1947 & may 18, 1950 & no party \\
7 & 8 & syed abdul kadir mohamed & february 18, 1952 & june 5, 1955 & no party \\
8 & 9 & wan idris ibrahim & october 1, 1955 & august 31, 1957 & no party \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "left office" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( left office ) where left office = '8' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>menteri besar</th>
<th>took office</th>
<th>left office</th>
<th>party</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>jaafar mohamed</td>
<td>1886</td>
<td>july 1890</td>
<td>no party</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>mohamed mahbob</td>
<td>june 1920</td>
<td>1922</td>
<td>no party</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>abdullah jaafar</td>
<td>september 1923</td>
<td>1928</td>
<td>no party</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>mustapha jaafar</td>
<td>september 16, 1928</td>
<td>november 23, 1931</td>
<td>no party</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>abdul hamid yusof</td>
<td>november 23, 1931</td>
<td>december 28, 1934</td>
<td>no party</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>ungku abdul aziz abdul majid</td>
<td>april 1935</td>
<td>june 1, 1947</td>
<td>no party</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>onn jaafar</td>
<td>june 1, 1947</td>
<td>may 18, 1950</td>
<td>no party</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>syed abdul kadir mohamed</td>
<td>february 18, 1952</td>
<td>june 5, 1955</td>
<td>no party</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>wan idris ibrahim</td>
<td>october 1, 1955</td>
<td>august 31, 1957</td>
<td>no party</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "left office" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( left office ) where left office = '8' <table_name> : table | | # | menteri besar | took office | left office | party |
|---:|----:|:-----------------------------|:-------------------|:------------------|:---------|
| 0 | 1 | jaafar mohamed | 1886 | july 1890 | no party |
| 1 | 2 | mohamed mahbob | june 1920 | 1922 | no party |
| 2 | 3 | abdullah jaafar | september 1923 | 1928 | no party |
| 3 | 4 | mustapha jaafar | september 16, 1928 | november 23, 1931 | no party |
| 4 | 5 | abdul hamid yusof | november 23, 1931 | december 28, 1934 | no party |
| 5 | 6 | ungku abdul aziz abdul majid | april 1935 | june 1, 1947 | no party |
| 6 | 7 | onn jaafar | june 1, 1947 | may 18, 1950 | no party |
| 7 | 8 | syed abdul kadir mohamed | february 18, 1952 | june 5, 1955 | no party |
| 8 | 9 | wan idris ibrahim | october 1, 1955 | august 31, 1957 | no party | | | | count ( "left office" ) |
|---:|--------------------------:|
| 0 | 0 | | [
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select count ( * ) where # = 9 col : # | nation | qualification tournament | place in qt | sailor row 1 : 1 | china | host country | none | none row 2 : 2 | brazil | 2007 worlds | 1 | robert scheidt, bruno prada row 3 : 3 | france | 2007 worlds | 2 | xavier rohart, pascal rambeau row 4 : 4 | great britain | 2007 worlds | 3 | iain percy, andrew simpson row 5 : 5 | new zealand | 2007 worlds | 4 | hamish pepper, carl williams row 6 : 6 | italy | 2007 worlds | 5 | diego negri, luigi viale row 7 : 7 | poland | 2007 worlds | 6 | mateusz kusznierewicz, dominik zycki row 8 : 8 | germany | 2007 worlds | 7 | marc pickel, ingo borkowski row 9 : 9 | sweden | 2007 worlds | 8 | fredrik loof, anders ekstrom row 10 : 10 | australia | 2007 worlds | 9 | iain murray, andrew palfrey row 11 : 11 | portugal | 2007 worlds | 10 | afonso domingos, bernardo santos row 12 : 12 | united states | 2007 worlds | 11 | mark reynolds, hal haenel row 13 : 13 | switzerland | 2008 worlds | 4 | flavio marazzi, enrico de maria row 14 : 14 | croatia | 2008 worlds | 12 | marin lovrovic, sinsa mikulicic row 15 : 15 | ireland | 2008 worlds | 14 | max treacy, anthony shanks row 16 : 16 | austria | 2008 worlds | 16 | hans spitzauer, christian nehammer | col : count ( "*" ) row 1 : 1 | select count ( * ) where # = 9 <table_name> : table \begin{tabular}{llllll}
\toprule
& # & nation & qualification tournament & place in qt & sailor \\
\midrule
0 & 1 & china & host country & none & none \\
1 & 2 & brazil & 2007 worlds & 1 & robert scheidt, bruno prada \\
2 & 3 & france & 2007 worlds & 2 & xavier rohart, pascal rambeau \\
3 & 4 & great britain & 2007 worlds & 3 & iain percy, andrew simpson \\
4 & 5 & new zealand & 2007 worlds & 4 & hamish pepper, carl williams \\
5 & 6 & italy & 2007 worlds & 5 & diego negri, luigi viale \\
6 & 7 & poland & 2007 worlds & 6 & mateusz kusznierewicz, dominik zycki \\
7 & 8 & germany & 2007 worlds & 7 & marc pickel, ingo borkowski \\
8 & 9 & sweden & 2007 worlds & 8 & fredrik loof, anders ekstrom \\
9 & 10 & australia & 2007 worlds & 9 & iain murray, andrew palfrey \\
10 & 11 & portugal & 2007 worlds & 10 & afonso domingos, bernardo santos \\
11 & 12 & united states & 2007 worlds & 11 & mark reynolds, hal haenel \\
12 & 13 & switzerland & 2008 worlds & 4 & flavio marazzi, enrico de maria \\
13 & 14 & croatia & 2008 worlds & 12 & marin lovrovic, sinsa mikulicic \\
14 & 15 & ireland & 2008 worlds & 14 & max treacy, anthony shanks \\
15 & 16 & austria & 2008 worlds & 16 & hans spitzauer, christian nehammer \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where # = 9 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>nation</th>
<th>qualification tournament</th>
<th>place in qt</th>
<th>sailor</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>china</td>
<td>host country</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>brazil</td>
<td>2007 worlds</td>
<td>1</td>
<td>robert scheidt, bruno prada</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>france</td>
<td>2007 worlds</td>
<td>2</td>
<td>xavier rohart, pascal rambeau</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>great britain</td>
<td>2007 worlds</td>
<td>3</td>
<td>iain percy, andrew simpson</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>new zealand</td>
<td>2007 worlds</td>
<td>4</td>
<td>hamish pepper, carl williams</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>italy</td>
<td>2007 worlds</td>
<td>5</td>
<td>diego negri, luigi viale</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>poland</td>
<td>2007 worlds</td>
<td>6</td>
<td>mateusz kusznierewicz, dominik zycki</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>germany</td>
<td>2007 worlds</td>
<td>7</td>
<td>marc pickel, ingo borkowski</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>sweden</td>
<td>2007 worlds</td>
<td>8</td>
<td>fredrik loof, anders ekstrom</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>australia</td>
<td>2007 worlds</td>
<td>9</td>
<td>iain murray, andrew palfrey</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>portugal</td>
<td>2007 worlds</td>
<td>10</td>
<td>afonso domingos, bernardo santos</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>united states</td>
<td>2007 worlds</td>
<td>11</td>
<td>mark reynolds, hal haenel</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>switzerland</td>
<td>2008 worlds</td>
<td>4</td>
<td>flavio marazzi, enrico de maria</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>croatia</td>
<td>2008 worlds</td>
<td>12</td>
<td>marin lovrovic, sinsa mikulicic</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>ireland</td>
<td>2008 worlds</td>
<td>14</td>
<td>max treacy, anthony shanks</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>austria</td>
<td>2008 worlds</td>
<td>16</td>
<td>hans spitzauer, christian nehammer</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where # = 9 <table_name> : table | | # | nation | qualification tournament | place in qt | sailor |
|---:|----:|:--------------|:---------------------------|:--------------|:-------------------------------------|
| 0 | 1 | china | host country | none | none |
| 1 | 2 | brazil | 2007 worlds | 1 | robert scheidt, bruno prada |
| 2 | 3 | france | 2007 worlds | 2 | xavier rohart, pascal rambeau |
| 3 | 4 | great britain | 2007 worlds | 3 | iain percy, andrew simpson |
| 4 | 5 | new zealand | 2007 worlds | 4 | hamish pepper, carl williams |
| 5 | 6 | italy | 2007 worlds | 5 | diego negri, luigi viale |
| 6 | 7 | poland | 2007 worlds | 6 | mateusz kusznierewicz, dominik zycki |
| 7 | 8 | germany | 2007 worlds | 7 | marc pickel, ingo borkowski |
| 8 | 9 | sweden | 2007 worlds | 8 | fredrik loof, anders ekstrom |
| 9 | 10 | australia | 2007 worlds | 9 | iain murray, andrew palfrey |
| 10 | 11 | portugal | 2007 worlds | 10 | afonso domingos, bernardo santos |
| 11 | 12 | united states | 2007 worlds | 11 | mark reynolds, hal haenel |
| 12 | 13 | switzerland | 2008 worlds | 4 | flavio marazzi, enrico de maria |
| 13 | 14 | croatia | 2008 worlds | 12 | marin lovrovic, sinsa mikulicic |
| 14 | 15 | ireland | 2008 worlds | 14 | max treacy, anthony shanks |
| 15 | 16 | austria | 2008 worlds | 16 | hans spitzauer, christian nehammer | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select enrollment where founded = 1930 col : institution | location | founded | type | enrollment | joined | nickname row 1 : bryan college | dayton, tennessee | 1930 | private (non-denominational) | 1044 | 2001 | lions row 2 : columbia college | columbia, south carolina | 1854 | private (methodist) | 1200 | 2011 | fighting koalas row 3 : milligan college | elizabethton, tennessee | 1866 | private (disciples of christ) | 1006 | 2001 | buffaloes row 4 : montreat college | montreat, north carolina | 1916 | private (presbyterian) | 1145 | 2001 | cavaliers row 5 : point university | west point, georgia | 1937 | private (christian churches and churches of christ) | 1000 | 2011 | skyhawks row 6 : reinhardt university | waleska, georgia | 1883 | private (methodist) | 1057 | 2009 | eagles row 7 : st. andrews university | laurinburg, north carolina | 1958 | private | 800 | 2012 | knights row 8 : savannah college of art and design at atlanta | atlanta, georgia | 2005 | private | 2000 | 2012 | bees row 9 : tennessee wesleyan college | athens, tennessee | 1857 | private (methodist) | 1103 | 2001 | bulldogs row 10 : truett-mcconnell college | cleveland, georgia | 1946 | private/christian (baptist) | 550 | 2013 | bears row 11 : union college | barbourville, kentucky | 1879 | private/christian (methodist) | 1368 | 2001 | bulldogs row 12 : virginia intermont college | bristol, virginia | 1884 | private/christian (baptist) | 916 | 2001 | cobras | col : enrollment row 1 : 1044 | select enrollment where founded = 1930 <table_name> : table \begin{tabular}{llllllll}
\toprule
& institution & location & founded & type & enrollment & joined & nickname \\
\midrule
0 & bryan college & dayton, tennessee & 1930 & private (non-denominational) & 1044 & 2001 & lions \\
1 & columbia college & columbia, south carolina & 1854 & private (methodist) & 1200 & 2011 & fighting koalas \\
2 & milligan college & elizabethton, tennessee & 1866 & private (disciples of christ) & 1006 & 2001 & buffaloes \\
3 & montreat college & montreat, north carolina & 1916 & private (presbyterian) & 1145 & 2001 & cavaliers \\
4 & point university & west point, georgia & 1937 & private (christian churches and churches of christ) & 1000 & 2011 & skyhawks \\
5 & reinhardt university & waleska, georgia & 1883 & private (methodist) & 1057 & 2009 & eagles \\
6 & st. andrews university & laurinburg, north carolina & 1958 & private & 800 & 2012 & knights \\
7 & savannah college of art and design at atlanta & atlanta, georgia & 2005 & private & 2000 & 2012 & bees \\
8 & tennessee wesleyan college & athens, tennessee & 1857 & private (methodist) & 1103 & 2001 & bulldogs \\
9 & truett-mcconnell college & cleveland, georgia & 1946 & private/christian (baptist) & 550 & 2013 & bears \\
10 & union college & barbourville, kentucky & 1879 & private/christian (methodist) & 1368 & 2001 & bulldogs \\
11 & virginia intermont college & bristol, virginia & 1884 & private/christian (baptist) & 916 & 2001 & cobras \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& enrollment \\
\midrule
0 & 1044 \\
\bottomrule
\end{tabular}
| select enrollment where founded = 1930 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>institution</th>
<th>location</th>
<th>founded</th>
<th>type</th>
<th>enrollment</th>
<th>joined</th>
<th>nickname</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>bryan college</td>
<td>dayton, tennessee</td>
<td>1930</td>
<td>private (non-denominational)</td>
<td>1044</td>
<td>2001</td>
<td>lions</td>
</tr>
<tr>
<th>1</th>
<td>columbia college</td>
<td>columbia, south carolina</td>
<td>1854</td>
<td>private (methodist)</td>
<td>1200</td>
<td>2011</td>
<td>fighting koalas</td>
</tr>
<tr>
<th>2</th>
<td>milligan college</td>
<td>elizabethton, tennessee</td>
<td>1866</td>
<td>private (disciples of christ)</td>
<td>1006</td>
<td>2001</td>
<td>buffaloes</td>
</tr>
<tr>
<th>3</th>
<td>montreat college</td>
<td>montreat, north carolina</td>
<td>1916</td>
<td>private (presbyterian)</td>
<td>1145</td>
<td>2001</td>
<td>cavaliers</td>
</tr>
<tr>
<th>4</th>
<td>point university</td>
<td>west point, georgia</td>
<td>1937</td>
<td>private (christian churches and churches of christ)</td>
<td>1000</td>
<td>2011</td>
<td>skyhawks</td>
</tr>
<tr>
<th>5</th>
<td>reinhardt university</td>
<td>waleska, georgia</td>
<td>1883</td>
<td>private (methodist)</td>
<td>1057</td>
<td>2009</td>
<td>eagles</td>
</tr>
<tr>
<th>6</th>
<td>st. andrews university</td>
<td>laurinburg, north carolina</td>
<td>1958</td>
<td>private</td>
<td>800</td>
<td>2012</td>
<td>knights</td>
</tr>
<tr>
<th>7</th>
<td>savannah college of art and design at atlanta</td>
<td>atlanta, georgia</td>
<td>2005</td>
<td>private</td>
<td>2000</td>
<td>2012</td>
<td>bees</td>
</tr>
<tr>
<th>8</th>
<td>tennessee wesleyan college</td>
<td>athens, tennessee</td>
<td>1857</td>
<td>private (methodist)</td>
<td>1103</td>
<td>2001</td>
<td>bulldogs</td>
</tr>
<tr>
<th>9</th>
<td>truett-mcconnell college</td>
<td>cleveland, georgia</td>
<td>1946</td>
<td>private/christian (baptist)</td>
<td>550</td>
<td>2013</td>
<td>bears</td>
</tr>
<tr>
<th>10</th>
<td>union college</td>
<td>barbourville, kentucky</td>
<td>1879</td>
<td>private/christian (methodist)</td>
<td>1368</td>
<td>2001</td>
<td>bulldogs</td>
</tr>
<tr>
<th>11</th>
<td>virginia intermont college</td>
<td>bristol, virginia</td>
<td>1884</td>
<td>private/christian (baptist)</td>
<td>916</td>
<td>2001</td>
<td>cobras</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>enrollment</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1044</td>
</tr>
</tbody>
</table> | select enrollment where founded = 1930 <table_name> : table | | institution | location | founded | type | enrollment | joined | nickname |
|---:|:----------------------------------------------|:---------------------------|----------:|:----------------------------------------------------|-------------:|---------:|:----------------|
| 0 | bryan college | dayton, tennessee | 1930 | private (non-denominational) | 1044 | 2001 | lions |
| 1 | columbia college | columbia, south carolina | 1854 | private (methodist) | 1200 | 2011 | fighting koalas |
| 2 | milligan college | elizabethton, tennessee | 1866 | private (disciples of christ) | 1006 | 2001 | buffaloes |
| 3 | montreat college | montreat, north carolina | 1916 | private (presbyterian) | 1145 | 2001 | cavaliers |
| 4 | point university | west point, georgia | 1937 | private (christian churches and churches of christ) | 1000 | 2011 | skyhawks |
| 5 | reinhardt university | waleska, georgia | 1883 | private (methodist) | 1057 | 2009 | eagles |
| 6 | st. andrews university | laurinburg, north carolina | 1958 | private | 800 | 2012 | knights |
| 7 | savannah college of art and design at atlanta | atlanta, georgia | 2005 | private | 2000 | 2012 | bees |
| 8 | tennessee wesleyan college | athens, tennessee | 1857 | private (methodist) | 1103 | 2001 | bulldogs |
| 9 | truett-mcconnell college | cleveland, georgia | 1946 | private/christian (baptist) | 550 | 2013 | bears |
| 10 | union college | barbourville, kentucky | 1879 | private/christian (methodist) | 1368 | 2001 | bulldogs |
| 11 | virginia intermont college | bristol, virginia | 1884 | private/christian (baptist) | 916 | 2001 | cobras | | | | enrollment |
|---:|-------------:|
| 0 | 1044 | | [
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select tie no where home team = 'sheffield united' col : tie no | home team | score | away team | date | attendance row 1 : 1 | rochdale | 2 - 0 | coventry city | 2003-01-25 00:00:00 | none row 2 : 2 | southampton | 1 - 1 | millwall | 2003-01-25 00:00:00 | 23809 row 3 : replay | millwall | 1 - 2 | southampton | 2003-02-05 00:00:00 | 10197 row 4 : 3 | watford | 1 - 0 | west bromwich albion | 2003-01-25 00:00:00 | 16975 row 5 : 4 | walsall | 2 - 0 | wimbledon | 2003-01-25 00:00:00 | 6693 row 6 : 5 | gillingham | 1 - 1 | leeds united | 2003-01-25 00:00:00 | 11093 row 7 : replay | leeds united | 2 - 1 | gillingham | 2003-02-04 00:00:00 | 29359 row 8 : 6 | blackburn rovers | 3 - 3 | sunderland | 2003-01-25 00:00:00 | 14315 row 9 : replay | sunderland | 2 - 2 | blackburn rovers | 2003-02-05 00:00:00 | 15745 row 10 : 7 | wolverhampton wanderers | 4 - 1 | leicester city | 2003-01-25 00:00:00 | 28164 row 11 : 8 | shrewsbury town | 0 - 4 | chelsea | 2003-01-26 00:00:00 | 7950 row 12 : 9 | sheffield united | 4 - 3 | ipswich town | 2003-01-25 00:00:00 | 12757 row 13 : 10 | fulham | 3 - 0 | charlton athletic | 2003-01-26 00:00:00 | 12203 row 14 : 11 | brentford | 0 - 3 | burnley | 2003-01-25 00:00:00 | 9563 row 15 : 12 | manchester united | 6 - 0 | west ham united | 2003-01-26 00:00:00 | 67181 row 16 : 13 | norwich city | 1 - 0 | dagenham & redbridge | 2003-01-25 00:00:00 | 21164 row 17 : 14 | crystal palace | 0 - 0 | liverpool | 2003-01-26 00:00:00 | 26054 row 18 : replay | liverpool | 0 - 2 | crystal palace | 2003-02-05 00:00:00 | 35109 row 19 : 15 | farnborough town | 1 - 5 | arsenal | 2003-01-25 00:00:00 | 35108 row 20 : 16 | stoke city | 3 - 0 | bournemouth | 2003-01-26 00:00:00 | 12004 | col : tie no row 1 : 9 | select tie no where home team = 'sheffield united' <table_name> : table \begin{tabular}{lllllll}
\toprule
& tie no & home team & score & away team & date & attendance \\
\midrule
0 & 1 & rochdale & 2 - 0 & coventry city & 2003-01-25 00:00:00 & none \\
1 & 2 & southampton & 1 - 1 & millwall & 2003-01-25 00:00:00 & 23809 \\
2 & replay & millwall & 1 - 2 & southampton & 2003-02-05 00:00:00 & 10197 \\
3 & 3 & watford & 1 - 0 & west bromwich albion & 2003-01-25 00:00:00 & 16975 \\
4 & 4 & walsall & 2 - 0 & wimbledon & 2003-01-25 00:00:00 & 6693 \\
5 & 5 & gillingham & 1 - 1 & leeds united & 2003-01-25 00:00:00 & 11093 \\
6 & replay & leeds united & 2 - 1 & gillingham & 2003-02-04 00:00:00 & 29359 \\
7 & 6 & blackburn rovers & 3 - 3 & sunderland & 2003-01-25 00:00:00 & 14315 \\
8 & replay & sunderland & 2 - 2 & blackburn rovers & 2003-02-05 00:00:00 & 15745 \\
9 & 7 & wolverhampton wanderers & 4 - 1 & leicester city & 2003-01-25 00:00:00 & 28164 \\
10 & 8 & shrewsbury town & 0 - 4 & chelsea & 2003-01-26 00:00:00 & 7950 \\
11 & 9 & sheffield united & 4 - 3 & ipswich town & 2003-01-25 00:00:00 & 12757 \\
12 & 10 & fulham & 3 - 0 & charlton athletic & 2003-01-26 00:00:00 & 12203 \\
13 & 11 & brentford & 0 - 3 & burnley & 2003-01-25 00:00:00 & 9563 \\
14 & 12 & manchester united & 6 - 0 & west ham united & 2003-01-26 00:00:00 & 67181 \\
15 & 13 & norwich city & 1 - 0 & dagenham & redbridge & 2003-01-25 00:00:00 & 21164 \\
16 & 14 & crystal palace & 0 - 0 & liverpool & 2003-01-26 00:00:00 & 26054 \\
17 & replay & liverpool & 0 - 2 & crystal palace & 2003-02-05 00:00:00 & 35109 \\
18 & 15 & farnborough town & 1 - 5 & arsenal & 2003-01-25 00:00:00 & 35108 \\
19 & 16 & stoke city & 3 - 0 & bournemouth & 2003-01-26 00:00:00 & 12004 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& tie no \\
\midrule
0 & 9 \\
\bottomrule
\end{tabular}
| select tie no where home team = 'sheffield united' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>tie no</th>
<th>home team</th>
<th>score</th>
<th>away team</th>
<th>date</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>rochdale</td>
<td>2 - 0</td>
<td>coventry city</td>
<td>2003-01-25 00:00:00</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>southampton</td>
<td>1 - 1</td>
<td>millwall</td>
<td>2003-01-25 00:00:00</td>
<td>23809</td>
</tr>
<tr>
<th>2</th>
<td>replay</td>
<td>millwall</td>
<td>1 - 2</td>
<td>southampton</td>
<td>2003-02-05 00:00:00</td>
<td>10197</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>watford</td>
<td>1 - 0</td>
<td>west bromwich albion</td>
<td>2003-01-25 00:00:00</td>
<td>16975</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>walsall</td>
<td>2 - 0</td>
<td>wimbledon</td>
<td>2003-01-25 00:00:00</td>
<td>6693</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>gillingham</td>
<td>1 - 1</td>
<td>leeds united</td>
<td>2003-01-25 00:00:00</td>
<td>11093</td>
</tr>
<tr>
<th>6</th>
<td>replay</td>
<td>leeds united</td>
<td>2 - 1</td>
<td>gillingham</td>
<td>2003-02-04 00:00:00</td>
<td>29359</td>
</tr>
<tr>
<th>7</th>
<td>6</td>
<td>blackburn rovers</td>
<td>3 - 3</td>
<td>sunderland</td>
<td>2003-01-25 00:00:00</td>
<td>14315</td>
</tr>
<tr>
<th>8</th>
<td>replay</td>
<td>sunderland</td>
<td>2 - 2</td>
<td>blackburn rovers</td>
<td>2003-02-05 00:00:00</td>
<td>15745</td>
</tr>
<tr>
<th>9</th>
<td>7</td>
<td>wolverhampton wanderers</td>
<td>4 - 1</td>
<td>leicester city</td>
<td>2003-01-25 00:00:00</td>
<td>28164</td>
</tr>
<tr>
<th>10</th>
<td>8</td>
<td>shrewsbury town</td>
<td>0 - 4</td>
<td>chelsea</td>
<td>2003-01-26 00:00:00</td>
<td>7950</td>
</tr>
<tr>
<th>11</th>
<td>9</td>
<td>sheffield united</td>
<td>4 - 3</td>
<td>ipswich town</td>
<td>2003-01-25 00:00:00</td>
<td>12757</td>
</tr>
<tr>
<th>12</th>
<td>10</td>
<td>fulham</td>
<td>3 - 0</td>
<td>charlton athletic</td>
<td>2003-01-26 00:00:00</td>
<td>12203</td>
</tr>
<tr>
<th>13</th>
<td>11</td>
<td>brentford</td>
<td>0 - 3</td>
<td>burnley</td>
<td>2003-01-25 00:00:00</td>
<td>9563</td>
</tr>
<tr>
<th>14</th>
<td>12</td>
<td>manchester united</td>
<td>6 - 0</td>
<td>west ham united</td>
<td>2003-01-26 00:00:00</td>
<td>67181</td>
</tr>
<tr>
<th>15</th>
<td>13</td>
<td>norwich city</td>
<td>1 - 0</td>
<td>dagenham & redbridge</td>
<td>2003-01-25 00:00:00</td>
<td>21164</td>
</tr>
<tr>
<th>16</th>
<td>14</td>
<td>crystal palace</td>
<td>0 - 0</td>
<td>liverpool</td>
<td>2003-01-26 00:00:00</td>
<td>26054</td>
</tr>
<tr>
<th>17</th>
<td>replay</td>
<td>liverpool</td>
<td>0 - 2</td>
<td>crystal palace</td>
<td>2003-02-05 00:00:00</td>
<td>35109</td>
</tr>
<tr>
<th>18</th>
<td>15</td>
<td>farnborough town</td>
<td>1 - 5</td>
<td>arsenal</td>
<td>2003-01-25 00:00:00</td>
<td>35108</td>
</tr>
<tr>
<th>19</th>
<td>16</td>
<td>stoke city</td>
<td>3 - 0</td>
<td>bournemouth</td>
<td>2003-01-26 00:00:00</td>
<td>12004</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>tie no</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9</td>
</tr>
</tbody>
</table> | select tie no where home team = 'sheffield united' <table_name> : table | | tie no | home team | score | away team | date | attendance |
|---:|:---------|:------------------------|:--------|:---------------------|:--------------------|:-------------|
| 0 | 1 | rochdale | 2 - 0 | coventry city | 2003-01-25 00:00:00 | none |
| 1 | 2 | southampton | 1 - 1 | millwall | 2003-01-25 00:00:00 | 23809 |
| 2 | replay | millwall | 1 - 2 | southampton | 2003-02-05 00:00:00 | 10197 |
| 3 | 3 | watford | 1 - 0 | west bromwich albion | 2003-01-25 00:00:00 | 16975 |
| 4 | 4 | walsall | 2 - 0 | wimbledon | 2003-01-25 00:00:00 | 6693 |
| 5 | 5 | gillingham | 1 - 1 | leeds united | 2003-01-25 00:00:00 | 11093 |
| 6 | replay | leeds united | 2 - 1 | gillingham | 2003-02-04 00:00:00 | 29359 |
| 7 | 6 | blackburn rovers | 3 - 3 | sunderland | 2003-01-25 00:00:00 | 14315 |
| 8 | replay | sunderland | 2 - 2 | blackburn rovers | 2003-02-05 00:00:00 | 15745 |
| 9 | 7 | wolverhampton wanderers | 4 - 1 | leicester city | 2003-01-25 00:00:00 | 28164 |
| 10 | 8 | shrewsbury town | 0 - 4 | chelsea | 2003-01-26 00:00:00 | 7950 |
| 11 | 9 | sheffield united | 4 - 3 | ipswich town | 2003-01-25 00:00:00 | 12757 |
| 12 | 10 | fulham | 3 - 0 | charlton athletic | 2003-01-26 00:00:00 | 12203 |
| 13 | 11 | brentford | 0 - 3 | burnley | 2003-01-25 00:00:00 | 9563 |
| 14 | 12 | manchester united | 6 - 0 | west ham united | 2003-01-26 00:00:00 | 67181 |
| 15 | 13 | norwich city | 1 - 0 | dagenham & redbridge | 2003-01-25 00:00:00 | 21164 |
| 16 | 14 | crystal palace | 0 - 0 | liverpool | 2003-01-26 00:00:00 | 26054 |
| 17 | replay | liverpool | 0 - 2 | crystal palace | 2003-02-05 00:00:00 | 35109 |
| 18 | 15 | farnborough town | 1 - 5 | arsenal | 2003-01-25 00:00:00 | 35108 |
| 19 | 16 | stoke city | 3 - 0 | bournemouth | 2003-01-26 00:00:00 | 12004 | | | | tie no |
|---:|---------:|
| 0 | 9 | | [
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select count ( derby winner ) where year < 2008 col : year | derby winner | galaxy | draw | chivas row 1 : 2005 | galaxy | 5 | 0 | 0 row 2 : 2006 | galaxy | 2 | 1 | 1 row 3 : 2007 | chivas | 1 | 1 | 2 row 4 : 2008 | galaxy | 1 | 2 | 0 row 5 : 2009 | galaxy | 3 | 2 | 0 row 6 : 2010 | galaxy | 2 | 0 | 0 row 7 : 2011 | galaxy | 2 | 0 | 0 row 8 : 2012 | galaxy | 2 | 0 | 1 row 9 : 2013 | galaxy | 2 | 1 | 0 row 10 : total | none | 20 | 7 | 4 | col : count ( "derby winner" ) row 1 : 3 | select count ( derby winner ) where year < 2008 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & derby winner & galaxy & draw & chivas \\
\midrule
0 & 2005 & galaxy & 5 & 0 & 0 \\
1 & 2006 & galaxy & 2 & 1 & 1 \\
2 & 2007 & chivas & 1 & 1 & 2 \\
3 & 2008 & galaxy & 1 & 2 & 0 \\
4 & 2009 & galaxy & 3 & 2 & 0 \\
5 & 2010 & galaxy & 2 & 0 & 0 \\
6 & 2011 & galaxy & 2 & 0 & 0 \\
7 & 2012 & galaxy & 2 & 0 & 1 \\
8 & 2013 & galaxy & 2 & 1 & 0 \\
9 & total & none & 20 & 7 & 4 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "derby winner" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( derby winner ) where year < 2008 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>derby winner</th>
<th>galaxy</th>
<th>draw</th>
<th>chivas</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2005</td>
<td>galaxy</td>
<td>5</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>1</th>
<td>2006</td>
<td>galaxy</td>
<td>2</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>2007</td>
<td>chivas</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>3</th>
<td>2008</td>
<td>galaxy</td>
<td>1</td>
<td>2</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>2009</td>
<td>galaxy</td>
<td>3</td>
<td>2</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>2010</td>
<td>galaxy</td>
<td>2</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>2011</td>
<td>galaxy</td>
<td>2</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>2012</td>
<td>galaxy</td>
<td>2</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>2013</td>
<td>galaxy</td>
<td>2</td>
<td>1</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>total</td>
<td>none</td>
<td>20</td>
<td>7</td>
<td>4</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "derby winner" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( derby winner ) where year < 2008 <table_name> : table | | year | derby winner | galaxy | draw | chivas |
|---:|:-------|:---------------|---------:|-------:|---------:|
| 0 | 2005 | galaxy | 5 | 0 | 0 |
| 1 | 2006 | galaxy | 2 | 1 | 1 |
| 2 | 2007 | chivas | 1 | 1 | 2 |
| 3 | 2008 | galaxy | 1 | 2 | 0 |
| 4 | 2009 | galaxy | 3 | 2 | 0 |
| 5 | 2010 | galaxy | 2 | 0 | 0 |
| 6 | 2011 | galaxy | 2 | 0 | 0 |
| 7 | 2012 | galaxy | 2 | 0 | 1 |
| 8 | 2013 | galaxy | 2 | 1 | 0 |
| 9 | total | none | 20 | 7 | 4 | | | | count ( "derby winner" ) |
|---:|---------------------------:|
| 0 | 3 | | [
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select year where class = 'c1' col : year | team | co-drivers | car | class | laps | pos. | class pos. row 1 : 1972 | ford motor company deutschland | jochen mass | ford capri 2600rs | s 3.0 | 152 | dnf | dnf row 2 : 1973 | bmw motorsport | chris amon | bmw 3.0csl | t 5.0 | 160 | dnf | dnf row 3 : 1980 | bmw motorsport gmbh | hans-georg burger dominique lacaud | bmw m1 | imsa | 283 | 15th | 5th row 4 : 1981 | basf cassetten team gs sport | jean-pierre jarier helmut henzler | bmw m1 | imsa gtx | 57 | dnf | dnf row 5 : 1982 | basf cassetten team gs sport | jean-louis schlesser dieter quester | sauber shs c6-ford | c | 76 | dnf | dnf row 6 : 1985 | rothmans porsche | derek bell | porsche 962c | c1 | 367 | 3rd | 3rd row 7 : 1986 | rothmans porsche | derek bell al holbert | porsche 962c | c1 | 368 | 1st | 1st row 8 : 1987 | rothmans porsche ag | derek bell al holbert | porsche 962c | c1 | 368 | 1st | 1st row 9 : 1988 | porsche ag | klaus ludwig derek bell | porsche 962c | c1 | 394 | 2nd | 2nd row 10 : 1989 | joest racing | bob wollek | porsche 962c | c1 | 382 | 3rd | 3rd row 11 : 1990 | joest porsche racing | derek bell frank jelinski | porsche 962c | c1 | 350 | 4th | 4th row 12 : 1991 | konrad motorsport | derek bell frank jelinski | porsche 962c | c2 | 347 | 7th | 7th row 13 : 1993 | le mans porsche team | walter rohrl hurley haywood | porsche 911 turbo s lm-gt | gt | 79 | dnf | dnf row 14 : 1994 | le mans porsche team joest racing | thierry boutsen danny sullivan | dauer 962 le mans | gt1 | 343 | 3rd | 2nd row 15 : 1995 | porsche kremer racing | thierry boutsen christophe bouchut | kremer k8 spyder | wsc | 289 | 6th | 2nd row 16 : 1996 | porsche ag | thierry boutsen bob wollek | porsche 911 gt1 | gt1 | 353 | 2nd | 1st row 17 : 1997 | porsche ag | thierry boutsen bob wollek | porsche 911 gt1 | gt1 | 238 | dnf | dnf row 18 : 1998 | team bmw motorsport | steve soper tom kristensen | bmw v12 lm | lmp1 | 60 | dnf | dnf | col : year row 1 : 1985 row 2 : 1986 row 3 : 1987 row 4 : 1988 row 5 : 1989 row 6 : 1990 | select year where class = 'c1' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& year & team & co-drivers & car & class & laps & pos. & class pos. \\
\midrule
0 & 1972 & ford motor company deutschland & jochen mass & ford capri 2600rs & s 3.0 & 152 & dnf & dnf \\
1 & 1973 & bmw motorsport & chris amon & bmw 3.0csl & t 5.0 & 160 & dnf & dnf \\
2 & 1980 & bmw motorsport gmbh & hans-georg burger dominique lacaud & bmw m1 & imsa & 283 & 15th & 5th \\
3 & 1981 & basf cassetten team gs sport & jean-pierre jarier helmut henzler & bmw m1 & imsa gtx & 57 & dnf & dnf \\
4 & 1982 & basf cassetten team gs sport & jean-louis schlesser dieter quester & sauber shs c6-ford & c & 76 & dnf & dnf \\
5 & 1985 & rothmans porsche & derek bell & porsche 962c & c1 & 367 & 3rd & 3rd \\
6 & 1986 & rothmans porsche & derek bell al holbert & porsche 962c & c1 & 368 & 1st & 1st \\
7 & 1987 & rothmans porsche ag & derek bell al holbert & porsche 962c & c1 & 368 & 1st & 1st \\
8 & 1988 & porsche ag & klaus ludwig derek bell & porsche 962c & c1 & 394 & 2nd & 2nd \\
9 & 1989 & joest racing & bob wollek & porsche 962c & c1 & 382 & 3rd & 3rd \\
10 & 1990 & joest porsche racing & derek bell frank jelinski & porsche 962c & c1 & 350 & 4th & 4th \\
11 & 1991 & konrad motorsport & derek bell frank jelinski & porsche 962c & c2 & 347 & 7th & 7th \\
12 & 1993 & le mans porsche team & walter rohrl hurley haywood & porsche 911 turbo s lm-gt & gt & 79 & dnf & dnf \\
13 & 1994 & le mans porsche team joest racing & thierry boutsen danny sullivan & dauer 962 le mans & gt1 & 343 & 3rd & 2nd \\
14 & 1995 & porsche kremer racing & thierry boutsen christophe bouchut & kremer k8 spyder & wsc & 289 & 6th & 2nd \\
15 & 1996 & porsche ag & thierry boutsen bob wollek & porsche 911 gt1 & gt1 & 353 & 2nd & 1st \\
16 & 1997 & porsche ag & thierry boutsen bob wollek & porsche 911 gt1 & gt1 & 238 & dnf & dnf \\
17 & 1998 & team bmw motorsport & steve soper tom kristensen & bmw v12 lm & lmp1 & 60 & dnf & dnf \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1985 \\
1 & 1986 \\
2 & 1987 \\
3 & 1988 \\
4 & 1989 \\
5 & 1990 \\
\bottomrule
\end{tabular}
| select year where class = 'c1' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>team</th>
<th>co-drivers</th>
<th>car</th>
<th>class</th>
<th>laps</th>
<th>pos.</th>
<th>class pos.</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1972</td>
<td>ford motor company deutschland</td>
<td>jochen mass</td>
<td>ford capri 2600rs</td>
<td>s 3.0</td>
<td>152</td>
<td>dnf</td>
<td>dnf</td>
</tr>
<tr>
<th>1</th>
<td>1973</td>
<td>bmw motorsport</td>
<td>chris amon</td>
<td>bmw 3.0csl</td>
<td>t 5.0</td>
<td>160</td>
<td>dnf</td>
<td>dnf</td>
</tr>
<tr>
<th>2</th>
<td>1980</td>
<td>bmw motorsport gmbh</td>
<td>hans-georg burger dominique lacaud</td>
<td>bmw m1</td>
<td>imsa</td>
<td>283</td>
<td>15th</td>
<td>5th</td>
</tr>
<tr>
<th>3</th>
<td>1981</td>
<td>basf cassetten team gs sport</td>
<td>jean-pierre jarier helmut henzler</td>
<td>bmw m1</td>
<td>imsa gtx</td>
<td>57</td>
<td>dnf</td>
<td>dnf</td>
</tr>
<tr>
<th>4</th>
<td>1982</td>
<td>basf cassetten team gs sport</td>
<td>jean-louis schlesser dieter quester</td>
<td>sauber shs c6-ford</td>
<td>c</td>
<td>76</td>
<td>dnf</td>
<td>dnf</td>
</tr>
<tr>
<th>5</th>
<td>1985</td>
<td>rothmans porsche</td>
<td>derek bell</td>
<td>porsche 962c</td>
<td>c1</td>
<td>367</td>
<td>3rd</td>
<td>3rd</td>
</tr>
<tr>
<th>6</th>
<td>1986</td>
<td>rothmans porsche</td>
<td>derek bell al holbert</td>
<td>porsche 962c</td>
<td>c1</td>
<td>368</td>
<td>1st</td>
<td>1st</td>
</tr>
<tr>
<th>7</th>
<td>1987</td>
<td>rothmans porsche ag</td>
<td>derek bell al holbert</td>
<td>porsche 962c</td>
<td>c1</td>
<td>368</td>
<td>1st</td>
<td>1st</td>
</tr>
<tr>
<th>8</th>
<td>1988</td>
<td>porsche ag</td>
<td>klaus ludwig derek bell</td>
<td>porsche 962c</td>
<td>c1</td>
<td>394</td>
<td>2nd</td>
<td>2nd</td>
</tr>
<tr>
<th>9</th>
<td>1989</td>
<td>joest racing</td>
<td>bob wollek</td>
<td>porsche 962c</td>
<td>c1</td>
<td>382</td>
<td>3rd</td>
<td>3rd</td>
</tr>
<tr>
<th>10</th>
<td>1990</td>
<td>joest porsche racing</td>
<td>derek bell frank jelinski</td>
<td>porsche 962c</td>
<td>c1</td>
<td>350</td>
<td>4th</td>
<td>4th</td>
</tr>
<tr>
<th>11</th>
<td>1991</td>
<td>konrad motorsport</td>
<td>derek bell frank jelinski</td>
<td>porsche 962c</td>
<td>c2</td>
<td>347</td>
<td>7th</td>
<td>7th</td>
</tr>
<tr>
<th>12</th>
<td>1993</td>
<td>le mans porsche team</td>
<td>walter rohrl hurley haywood</td>
<td>porsche 911 turbo s lm-gt</td>
<td>gt</td>
<td>79</td>
<td>dnf</td>
<td>dnf</td>
</tr>
<tr>
<th>13</th>
<td>1994</td>
<td>le mans porsche team joest racing</td>
<td>thierry boutsen danny sullivan</td>
<td>dauer 962 le mans</td>
<td>gt1</td>
<td>343</td>
<td>3rd</td>
<td>2nd</td>
</tr>
<tr>
<th>14</th>
<td>1995</td>
<td>porsche kremer racing</td>
<td>thierry boutsen christophe bouchut</td>
<td>kremer k8 spyder</td>
<td>wsc</td>
<td>289</td>
<td>6th</td>
<td>2nd</td>
</tr>
<tr>
<th>15</th>
<td>1996</td>
<td>porsche ag</td>
<td>thierry boutsen bob wollek</td>
<td>porsche 911 gt1</td>
<td>gt1</td>
<td>353</td>
<td>2nd</td>
<td>1st</td>
</tr>
<tr>
<th>16</th>
<td>1997</td>
<td>porsche ag</td>
<td>thierry boutsen bob wollek</td>
<td>porsche 911 gt1</td>
<td>gt1</td>
<td>238</td>
<td>dnf</td>
<td>dnf</td>
</tr>
<tr>
<th>17</th>
<td>1998</td>
<td>team bmw motorsport</td>
<td>steve soper tom kristensen</td>
<td>bmw v12 lm</td>
<td>lmp1</td>
<td>60</td>
<td>dnf</td>
<td>dnf</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1985</td>
</tr>
<tr>
<th>1</th>
<td>1986</td>
</tr>
<tr>
<th>2</th>
<td>1987</td>
</tr>
<tr>
<th>3</th>
<td>1988</td>
</tr>
<tr>
<th>4</th>
<td>1989</td>
</tr>
<tr>
<th>5</th>
<td>1990</td>
</tr>
</tbody>
</table> | select year where class = 'c1' <table_name> : table | | year | team | co-drivers | car | class | laps | pos. | class pos. |
|---:|-------:|:----------------------------------|:------------------------------------|:--------------------------|:---------|-------:|:-------|:-------------|
| 0 | 1972 | ford motor company deutschland | jochen mass | ford capri 2600rs | s 3.0 | 152 | dnf | dnf |
| 1 | 1973 | bmw motorsport | chris amon | bmw 3.0csl | t 5.0 | 160 | dnf | dnf |
| 2 | 1980 | bmw motorsport gmbh | hans-georg burger dominique lacaud | bmw m1 | imsa | 283 | 15th | 5th |
| 3 | 1981 | basf cassetten team gs sport | jean-pierre jarier helmut henzler | bmw m1 | imsa gtx | 57 | dnf | dnf |
| 4 | 1982 | basf cassetten team gs sport | jean-louis schlesser dieter quester | sauber shs c6-ford | c | 76 | dnf | dnf |
| 5 | 1985 | rothmans porsche | derek bell | porsche 962c | c1 | 367 | 3rd | 3rd |
| 6 | 1986 | rothmans porsche | derek bell al holbert | porsche 962c | c1 | 368 | 1st | 1st |
| 7 | 1987 | rothmans porsche ag | derek bell al holbert | porsche 962c | c1 | 368 | 1st | 1st |
| 8 | 1988 | porsche ag | klaus ludwig derek bell | porsche 962c | c1 | 394 | 2nd | 2nd |
| 9 | 1989 | joest racing | bob wollek | porsche 962c | c1 | 382 | 3rd | 3rd |
| 10 | 1990 | joest porsche racing | derek bell frank jelinski | porsche 962c | c1 | 350 | 4th | 4th |
| 11 | 1991 | konrad motorsport | derek bell frank jelinski | porsche 962c | c2 | 347 | 7th | 7th |
| 12 | 1993 | le mans porsche team | walter rohrl hurley haywood | porsche 911 turbo s lm-gt | gt | 79 | dnf | dnf |
| 13 | 1994 | le mans porsche team joest racing | thierry boutsen danny sullivan | dauer 962 le mans | gt1 | 343 | 3rd | 2nd |
| 14 | 1995 | porsche kremer racing | thierry boutsen christophe bouchut | kremer k8 spyder | wsc | 289 | 6th | 2nd |
| 15 | 1996 | porsche ag | thierry boutsen bob wollek | porsche 911 gt1 | gt1 | 353 | 2nd | 1st |
| 16 | 1997 | porsche ag | thierry boutsen bob wollek | porsche 911 gt1 | gt1 | 238 | dnf | dnf |
| 17 | 1998 | team bmw motorsport | steve soper tom kristensen | bmw v12 lm | lmp1 | 60 | dnf | dnf | | | | year |
|---:|-------:|
| 0 | 1985 |
| 1 | 1986 |
| 2 | 1987 |
| 3 | 1988 |
| 4 | 1989 |
| 5 | 1990 | | [
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select count ( withdrew due to ) where points defending > 317 col : rank | player | points | points defending | points won | new points | withdrew due to row 1 : 5 | juan martin del potro | 5115 | 720 | 0 | 4395 | right wrist surgery row 2 : 6 | nikolay davydenko | 5145 | 360 | 0 | 4785 | broken wrist row 3 : 20 | radek stepanek | 1705 | 90 | 0 | 1615 | fatigue row 4 : 23 | tommy haas | 1660 | 180 | 0 | 1480 | right hip surgery row 5 : 32 | gilles simon | 1395 | 90 | 0 | 1305 | right knee injury row 6 : 36 | ivo karlovic | 1295 | 10 | 0 | 1285 | right foot injury row 7 : 10 | kim clijsters | 3890 | 0 | 0 | 3890 | left foot injury | col : count ( "withdrew due to" ) row 1 : 4 | select count ( withdrew due to ) where points defending > 317 <table_name> : table \begin{tabular}{llllllll}
\toprule
& rank & player & points & points defending & points won & new points & withdrew due to \\
\midrule
0 & 5 & juan martin del potro & 5115 & 720 & 0 & 4395 & right wrist surgery \\
1 & 6 & nikolay davydenko & 5145 & 360 & 0 & 4785 & broken wrist \\
2 & 20 & radek stepanek & 1705 & 90 & 0 & 1615 & fatigue \\
3 & 23 & tommy haas & 1660 & 180 & 0 & 1480 & right hip surgery \\
4 & 32 & gilles simon & 1395 & 90 & 0 & 1305 & right knee injury \\
5 & 36 & ivo karlovic & 1295 & 10 & 0 & 1285 & right foot injury \\
6 & 10 & kim clijsters & 3890 & 0 & 0 & 3890 & left foot injury \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "withdrew due to" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( withdrew due to ) where points defending > 317 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>player</th>
<th>points</th>
<th>points defending</th>
<th>points won</th>
<th>new points</th>
<th>withdrew due to</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
<td>juan martin del potro</td>
<td>5115</td>
<td>720</td>
<td>0</td>
<td>4395</td>
<td>right wrist surgery</td>
</tr>
<tr>
<th>1</th>
<td>6</td>
<td>nikolay davydenko</td>
<td>5145</td>
<td>360</td>
<td>0</td>
<td>4785</td>
<td>broken wrist</td>
</tr>
<tr>
<th>2</th>
<td>20</td>
<td>radek stepanek</td>
<td>1705</td>
<td>90</td>
<td>0</td>
<td>1615</td>
<td>fatigue</td>
</tr>
<tr>
<th>3</th>
<td>23</td>
<td>tommy haas</td>
<td>1660</td>
<td>180</td>
<td>0</td>
<td>1480</td>
<td>right hip surgery</td>
</tr>
<tr>
<th>4</th>
<td>32</td>
<td>gilles simon</td>
<td>1395</td>
<td>90</td>
<td>0</td>
<td>1305</td>
<td>right knee injury</td>
</tr>
<tr>
<th>5</th>
<td>36</td>
<td>ivo karlovic</td>
<td>1295</td>
<td>10</td>
<td>0</td>
<td>1285</td>
<td>right foot injury</td>
</tr>
<tr>
<th>6</th>
<td>10</td>
<td>kim clijsters</td>
<td>3890</td>
<td>0</td>
<td>0</td>
<td>3890</td>
<td>left foot injury</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "withdrew due to" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select count ( withdrew due to ) where points defending > 317 <table_name> : table | | rank | player | points | points defending | points won | new points | withdrew due to |
|---:|-------:|:----------------------|---------:|-------------------:|-------------:|-------------:|:--------------------|
| 0 | 5 | juan martin del potro | 5115 | 720 | 0 | 4395 | right wrist surgery |
| 1 | 6 | nikolay davydenko | 5145 | 360 | 0 | 4785 | broken wrist |
| 2 | 20 | radek stepanek | 1705 | 90 | 0 | 1615 | fatigue |
| 3 | 23 | tommy haas | 1660 | 180 | 0 | 1480 | right hip surgery |
| 4 | 32 | gilles simon | 1395 | 90 | 0 | 1305 | right knee injury |
| 5 | 36 | ivo karlovic | 1295 | 10 | 0 | 1285 | right foot injury |
| 6 | 10 | kim clijsters | 3890 | 0 | 0 | 3890 | left foot injury | | | | count ( "withdrew due to" ) |
|---:|------------------------------:|
| 0 | 4 | | [
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select title where name = 'dr. alberto abdala' col : state | title | name | entered office row 1 : barbados | president of the senate | sir stanley robinson | 1966 row 2 : barbados | speaker of the house of assembly | sir theodore brancker | 1961 row 3 : bolivia | president of the senate | none | 1970 row 4 : bolivia | president of the chamber of deputies | none | 1970 row 5 : brazil | president of the senate | joao cleofas de oliveira | 1970 row 6 : brazil | president of the chamber of deputies | geraldo freire da silva | 1970 row 7 : canada | speaker of the senate | hon. jean-paul deschatelets | september 5, 1968 row 8 : canada | speaker of the house of commons | hon. lucien lamoureux | january 18, 1966 row 9 : chile | president of the senate | tomas pablo elorza | 1969 row 10 : chile | president of the chamber of deputies | fernando humberto andres sanhueza herbarge | july 20, 1970 row 11 : colombia | president of the senate | eduardo abuchaibe ramirez | 1970 row 12 : colombia | president of the chamber of representatives | none | none row 13 : costa rica | president of the congress | daniel oduber quiros | 1970 row 14 : dominican republic | president of assembly | pedro valdez ? | 1966 ? row 15 : ecuador | president of the senate | none | none row 16 : ecuador | president of the chamber of deputies | none | none row 17 : el salvador | president of the legislative assembly | dr. benjamin iteriano ? | 1970 ? row 18 : guatemala | president of the congress | mario sandoval alarcon | 1970 row 19 : guyana | speaker of the legislative assembly | hon. rahman bacchus gajraj | 1968 row 20 : haiti | president of the national assembly | ulrick st. louis ? | none row 21 : honduras | president of the national congress | lic. mario rivera lopez | 1965 row 22 : jamaica | president of the senate | g. s. ranglin | december 7, 1962 row 23 : jamaica | speaker of the house of representatives | eugene parkinson | 1967 row 24 : mexico | president of the senate | lic. manuel aguirre[disambiguation needed] ? | 1967 ? row 25 : mexico | president of the federal chamber of deputies | lic. luis farias ? | 1967 ? row 26 : nicaragua | president of the senate | dr. adrian cuadra gutierrez ? | none row 27 : nicaragua | president of the chamber of deputies | dr. orlando montenegro ? | none row 28 : paraguay | president of the council of state | dr. juan ramon chavez ? | 1967 ? row 29 : trinidad and tobago | president of the senate | j. hamilton maurice | december 29, 1961 row 30 : trinidad and tobago | speaker of the house of representatives | a. c. thomasos | december 29, 1961 row 31 : usa | president of the senate (the vice president of the united states of america) | spiro agnew | january 20, 1969 row 32 : usa | president pro tempore of the senate | richard b. russell | january 2, 1969 row 33 : usa | speaker of the house of representatives | john william mccormack | january 10, 1962 row 34 : puerto rico | president of the senate | rafael hernandez colon | 1969 row 35 : puerto rico | speaker of the house of representatives | angel viera martinez | january 13, 1969 row 36 : uruguay | president of the senate (the vice president of uruguay) | dr. alberto abdala | december 6, 1967 row 37 : uruguay | president of the chamber of deputies | fernando elichirigoity | march 1, 1970 row 38 : venezuela | president of the senate | dr. jose a. perez diaz ? | 1968 ? row 39 : venezuela | president of the chamber of deputies | prof. jorge dargen ? | 1968 ? | col : title row 1 : president of the senate (the vice president of uruguay) | select title where name = 'dr. alberto abdala' <table_name> : table \begin{tabular}{lllll}
\toprule
& state & title & name & entered office \\
\midrule
0 & barbados & president of the senate & sir stanley robinson & 1966 \\
1 & barbados & speaker of the house of assembly & sir theodore brancker & 1961 \\
2 & bolivia & president of the senate & none & 1970 \\
3 & bolivia & president of the chamber of deputies & none & 1970 \\
4 & brazil & president of the senate & joao cleofas de oliveira & 1970 \\
5 & brazil & president of the chamber of deputies & geraldo freire da silva & 1970 \\
6 & canada & speaker of the senate & hon. jean-paul deschatelets & september 5, 1968 \\
7 & canada & speaker of the house of commons & hon. lucien lamoureux & january 18, 1966 \\
8 & chile & president of the senate & tomas pablo elorza & 1969 \\
9 & chile & president of the chamber of deputies & fernando humberto andres sanhueza herbarge & july 20, 1970 \\
10 & colombia & president of the senate & eduardo abuchaibe ramirez & 1970 \\
11 & colombia & president of the chamber of representatives & none & none \\
12 & costa rica & president of the congress & daniel oduber quiros & 1970 \\
13 & dominican republic & president of assembly & pedro valdez ? & 1966 ? \\
14 & ecuador & president of the senate & none & none \\
15 & ecuador & president of the chamber of deputies & none & none \\
16 & el salvador & president of the legislative assembly & dr. benjamin iteriano ? & 1970 ? \\
17 & guatemala & president of the congress & mario sandoval alarcon & 1970 \\
18 & guyana & speaker of the legislative assembly & hon. rahman bacchus gajraj & 1968 \\
19 & haiti & president of the national assembly & ulrick st. louis ? & none \\
20 & honduras & president of the national congress & lic. mario rivera lopez & 1965 \\
21 & jamaica & president of the senate & g. s. ranglin & december 7, 1962 \\
22 & jamaica & speaker of the house of representatives & eugene parkinson & 1967 \\
23 & mexico & president of the senate & lic. manuel aguirre[disambiguation needed] ? & 1967 ? \\
24 & mexico & president of the federal chamber of deputies & lic. luis farias ? & 1967 ? \\
25 & nicaragua & president of the senate & dr. adrian cuadra gutierrez ? & none \\
26 & nicaragua & president of the chamber of deputies & dr. orlando montenegro ? & none \\
27 & paraguay & president of the council of state & dr. juan ramon chavez ? & 1967 ? \\
28 & trinidad and tobago & president of the senate & j. hamilton maurice & december 29, 1961 \\
29 & trinidad and tobago & speaker of the house of representatives & a. c. thomasos & december 29, 1961 \\
30 & usa & president of the senate (the vice president of the united states of america) & spiro agnew & january 20, 1969 \\
31 & usa & president pro tempore of the senate & richard b. russell & january 2, 1969 \\
32 & usa & speaker of the house of representatives & john william mccormack & january 10, 1962 \\
33 & puerto rico & president of the senate & rafael hernandez colon & 1969 \\
34 & puerto rico & speaker of the house of representatives & angel viera martinez & january 13, 1969 \\
35 & uruguay & president of the senate (the vice president of uruguay) & dr. alberto abdala & december 6, 1967 \\
36 & uruguay & president of the chamber of deputies & fernando elichirigoity & march 1, 1970 \\
37 & venezuela & president of the senate & dr. jose a. perez diaz ? & 1968 ? \\
38 & venezuela & president of the chamber of deputies & prof. jorge dargen ? & 1968 ? \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& title \\
\midrule
0 & president of the senate (the vice president of uruguay) \\
\bottomrule
\end{tabular}
| select title where name = 'dr. alberto abdala' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>state</th>
<th>title</th>
<th>name</th>
<th>entered office</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>barbados</td>
<td>president of the senate</td>
<td>sir stanley robinson</td>
<td>1966</td>
</tr>
<tr>
<th>1</th>
<td>barbados</td>
<td>speaker of the house of assembly</td>
<td>sir theodore brancker</td>
<td>1961</td>
</tr>
<tr>
<th>2</th>
<td>bolivia</td>
<td>president of the senate</td>
<td>none</td>
<td>1970</td>
</tr>
<tr>
<th>3</th>
<td>bolivia</td>
<td>president of the chamber of deputies</td>
<td>none</td>
<td>1970</td>
</tr>
<tr>
<th>4</th>
<td>brazil</td>
<td>president of the senate</td>
<td>joao cleofas de oliveira</td>
<td>1970</td>
</tr>
<tr>
<th>5</th>
<td>brazil</td>
<td>president of the chamber of deputies</td>
<td>geraldo freire da silva</td>
<td>1970</td>
</tr>
<tr>
<th>6</th>
<td>canada</td>
<td>speaker of the senate</td>
<td>hon. jean-paul deschatelets</td>
<td>september 5, 1968</td>
</tr>
<tr>
<th>7</th>
<td>canada</td>
<td>speaker of the house of commons</td>
<td>hon. lucien lamoureux</td>
<td>january 18, 1966</td>
</tr>
<tr>
<th>8</th>
<td>chile</td>
<td>president of the senate</td>
<td>tomas pablo elorza</td>
<td>1969</td>
</tr>
<tr>
<th>9</th>
<td>chile</td>
<td>president of the chamber of deputies</td>
<td>fernando humberto andres sanhueza herbarge</td>
<td>july 20, 1970</td>
</tr>
<tr>
<th>10</th>
<td>colombia</td>
<td>president of the senate</td>
<td>eduardo abuchaibe ramirez</td>
<td>1970</td>
</tr>
<tr>
<th>11</th>
<td>colombia</td>
<td>president of the chamber of representatives</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>costa rica</td>
<td>president of the congress</td>
<td>daniel oduber quiros</td>
<td>1970</td>
</tr>
<tr>
<th>13</th>
<td>dominican republic</td>
<td>president of assembly</td>
<td>pedro valdez ?</td>
<td>1966 ?</td>
</tr>
<tr>
<th>14</th>
<td>ecuador</td>
<td>president of the senate</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>ecuador</td>
<td>president of the chamber of deputies</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>el salvador</td>
<td>president of the legislative assembly</td>
<td>dr. benjamin iteriano ?</td>
<td>1970 ?</td>
</tr>
<tr>
<th>17</th>
<td>guatemala</td>
<td>president of the congress</td>
<td>mario sandoval alarcon</td>
<td>1970</td>
</tr>
<tr>
<th>18</th>
<td>guyana</td>
<td>speaker of the legislative assembly</td>
<td>hon. rahman bacchus gajraj</td>
<td>1968</td>
</tr>
<tr>
<th>19</th>
<td>haiti</td>
<td>president of the national assembly</td>
<td>ulrick st. louis ?</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>honduras</td>
<td>president of the national congress</td>
<td>lic. mario rivera lopez</td>
<td>1965</td>
</tr>
<tr>
<th>21</th>
<td>jamaica</td>
<td>president of the senate</td>
<td>g. s. ranglin</td>
<td>december 7, 1962</td>
</tr>
<tr>
<th>22</th>
<td>jamaica</td>
<td>speaker of the house of representatives</td>
<td>eugene parkinson</td>
<td>1967</td>
</tr>
<tr>
<th>23</th>
<td>mexico</td>
<td>president of the senate</td>
<td>lic. manuel aguirre[disambiguation needed] ?</td>
<td>1967 ?</td>
</tr>
<tr>
<th>24</th>
<td>mexico</td>
<td>president of the federal chamber of deputies</td>
<td>lic. luis farias ?</td>
<td>1967 ?</td>
</tr>
<tr>
<th>25</th>
<td>nicaragua</td>
<td>president of the senate</td>
<td>dr. adrian cuadra gutierrez ?</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>nicaragua</td>
<td>president of the chamber of deputies</td>
<td>dr. orlando montenegro ?</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>paraguay</td>
<td>president of the council of state</td>
<td>dr. juan ramon chavez ?</td>
<td>1967 ?</td>
</tr>
<tr>
<th>28</th>
<td>trinidad and tobago</td>
<td>president of the senate</td>
<td>j. hamilton maurice</td>
<td>december 29, 1961</td>
</tr>
<tr>
<th>29</th>
<td>trinidad and tobago</td>
<td>speaker of the house of representatives</td>
<td>a. c. thomasos</td>
<td>december 29, 1961</td>
</tr>
<tr>
<th>30</th>
<td>usa</td>
<td>president of the senate (the vice president of the united states of america)</td>
<td>spiro agnew</td>
<td>january 20, 1969</td>
</tr>
<tr>
<th>31</th>
<td>usa</td>
<td>president pro tempore of the senate</td>
<td>richard b. russell</td>
<td>january 2, 1969</td>
</tr>
<tr>
<th>32</th>
<td>usa</td>
<td>speaker of the house of representatives</td>
<td>john william mccormack</td>
<td>january 10, 1962</td>
</tr>
<tr>
<th>33</th>
<td>puerto rico</td>
<td>president of the senate</td>
<td>rafael hernandez colon</td>
<td>1969</td>
</tr>
<tr>
<th>34</th>
<td>puerto rico</td>
<td>speaker of the house of representatives</td>
<td>angel viera martinez</td>
<td>january 13, 1969</td>
</tr>
<tr>
<th>35</th>
<td>uruguay</td>
<td>president of the senate (the vice president of uruguay)</td>
<td>dr. alberto abdala</td>
<td>december 6, 1967</td>
</tr>
<tr>
<th>36</th>
<td>uruguay</td>
<td>president of the chamber of deputies</td>
<td>fernando elichirigoity</td>
<td>march 1, 1970</td>
</tr>
<tr>
<th>37</th>
<td>venezuela</td>
<td>president of the senate</td>
<td>dr. jose a. perez diaz ?</td>
<td>1968 ?</td>
</tr>
<tr>
<th>38</th>
<td>venezuela</td>
<td>president of the chamber of deputies</td>
<td>prof. jorge dargen ?</td>
<td>1968 ?</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>title</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>president of the senate (the vice president of uruguay)</td>
</tr>
</tbody>
</table> | select title where name = 'dr. alberto abdala' <table_name> : table | | state | title | name | entered office |
|---:|:--------------------|:-----------------------------------------------------------------------------|:---------------------------------------------|:------------------|
| 0 | barbados | president of the senate | sir stanley robinson | 1966 |
| 1 | barbados | speaker of the house of assembly | sir theodore brancker | 1961 |
| 2 | bolivia | president of the senate | none | 1970 |
| 3 | bolivia | president of the chamber of deputies | none | 1970 |
| 4 | brazil | president of the senate | joao cleofas de oliveira | 1970 |
| 5 | brazil | president of the chamber of deputies | geraldo freire da silva | 1970 |
| 6 | canada | speaker of the senate | hon. jean-paul deschatelets | september 5, 1968 |
| 7 | canada | speaker of the house of commons | hon. lucien lamoureux | january 18, 1966 |
| 8 | chile | president of the senate | tomas pablo elorza | 1969 |
| 9 | chile | president of the chamber of deputies | fernando humberto andres sanhueza herbarge | july 20, 1970 |
| 10 | colombia | president of the senate | eduardo abuchaibe ramirez | 1970 |
| 11 | colombia | president of the chamber of representatives | none | none |
| 12 | costa rica | president of the congress | daniel oduber quiros | 1970 |
| 13 | dominican republic | president of assembly | pedro valdez ? | 1966 ? |
| 14 | ecuador | president of the senate | none | none |
| 15 | ecuador | president of the chamber of deputies | none | none |
| 16 | el salvador | president of the legislative assembly | dr. benjamin iteriano ? | 1970 ? |
| 17 | guatemala | president of the congress | mario sandoval alarcon | 1970 |
| 18 | guyana | speaker of the legislative assembly | hon. rahman bacchus gajraj | 1968 |
| 19 | haiti | president of the national assembly | ulrick st. louis ? | none |
| 20 | honduras | president of the national congress | lic. mario rivera lopez | 1965 |
| 21 | jamaica | president of the senate | g. s. ranglin | december 7, 1962 |
| 22 | jamaica | speaker of the house of representatives | eugene parkinson | 1967 |
| 23 | mexico | president of the senate | lic. manuel aguirre[disambiguation needed] ? | 1967 ? |
| 24 | mexico | president of the federal chamber of deputies | lic. luis farias ? | 1967 ? |
| 25 | nicaragua | president of the senate | dr. adrian cuadra gutierrez ? | none |
| 26 | nicaragua | president of the chamber of deputies | dr. orlando montenegro ? | none |
| 27 | paraguay | president of the council of state | dr. juan ramon chavez ? | 1967 ? |
| 28 | trinidad and tobago | president of the senate | j. hamilton maurice | december 29, 1961 |
| 29 | trinidad and tobago | speaker of the house of representatives | a. c. thomasos | december 29, 1961 |
| 30 | usa | president of the senate (the vice president of the united states of america) | spiro agnew | january 20, 1969 |
| 31 | usa | president pro tempore of the senate | richard b. russell | january 2, 1969 |
| 32 | usa | speaker of the house of representatives | john william mccormack | january 10, 1962 |
| 33 | puerto rico | president of the senate | rafael hernandez colon | 1969 |
| 34 | puerto rico | speaker of the house of representatives | angel viera martinez | january 13, 1969 |
| 35 | uruguay | president of the senate (the vice president of uruguay) | dr. alberto abdala | december 6, 1967 |
| 36 | uruguay | president of the chamber of deputies | fernando elichirigoity | march 1, 1970 |
| 37 | venezuela | president of the senate | dr. jose a. perez diaz ? | 1968 ? |
| 38 | venezuela | president of the chamber of deputies | prof. jorge dargen ? | 1968 ? | | | | title |
|---:|:--------------------------------------------------------|
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] |
select position where cup = 'dnq' col : season | division | tier | position | cup row 1 : 1994-95 | regionalliga sud | iii | 7 | quarter-final row 2 : 1995-96 | regionalliga sud | iii | 13 | round 1 row 3 : 1997-97 | regionalliga sud | iii | 8 | dnq row 4 : 1997-98 | regionalliga sud | iii | 6 | dnq row 5 : 1998-99 | regionalliga sud | iii | 8 | dnq row 6 : 1999-00 | regionalliga sud | iii | 5 | dnq row 7 : 2000-01 | regionalliga sud | iii | 9 | dnq row 8 : 2001-02 | regionalliga sud | iii | 10 | dnq row 9 : 2002-03 | regionalliga sud | iii | 4 | round 1 row 10 : 2003-04 | regionalliga sud | iii | 1 | dnq row 11 : 2004-05 | regionalliga sud | iii | 6 | quarter-final row 12 : 2005-06 | regionalliga sud | iii | 11 | dnq row 13 : 2006-07 | regionalliga sud | iii | 8 | dnq row 14 : 2007-08 | regionalliga sud | iii | 8 | dnq row 15 : 2008-09 | 3. liga | iii | 5 | none row 16 : 2009-10 | 3. liga | iii | 8 | none row 17 : 2010-11 | 3. liga | iii | 20 | none row 18 : 2011-12 | regionalliga sud | iv | 14 | none row 19 : 2012-13 | regionalliga bayern | iv | 2 | none | col : position row 1 : 8 row 2 : 6 row 3 : 8 row 4 : 5 row 5 : 9 row 6 : 10 row 7 : 1 row 8 : 11 row 9 : 8 row 10 : 8 | select position where cup = 'dnq' <table_name> : table \begin{tabular}{llllll}
\toprule
& season & division & tier & position & cup \\
\midrule
0 & 1994-95 & regionalliga sud & iii & 7 & quarter-final \\
1 & 1995-96 & regionalliga sud & iii & 13 & round 1 \\
2 & 1997-97 & regionalliga sud & iii & 8 & dnq \\
3 & 1997-98 & regionalliga sud & iii & 6 & dnq \\
4 & 1998-99 & regionalliga sud & iii & 8 & dnq \\
5 & 1999-00 & regionalliga sud & iii & 5 & dnq \\
6 & 2000-01 & regionalliga sud & iii & 9 & dnq \\
7 & 2001-02 & regionalliga sud & iii & 10 & dnq \\
8 & 2002-03 & regionalliga sud & iii & 4 & round 1 \\
9 & 2003-04 & regionalliga sud & iii & 1 & dnq \\
10 & 2004-05 & regionalliga sud & iii & 6 & quarter-final \\
11 & 2005-06 & regionalliga sud & iii & 11 & dnq \\
12 & 2006-07 & regionalliga sud & iii & 8 & dnq \\
13 & 2007-08 & regionalliga sud & iii & 8 & dnq \\
14 & 2008-09 & 3. liga & iii & 5 & none \\
15 & 2009-10 & 3. liga & iii & 8 & none \\
16 & 2010-11 & 3. liga & iii & 20 & none \\
17 & 2011-12 & regionalliga sud & iv & 14 & none \\
18 & 2012-13 & regionalliga bayern & iv & 2 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& position \\
\midrule
0 & 8 \\
1 & 6 \\
2 & 8 \\
3 & 5 \\
4 & 9 \\
5 & 10 \\
6 & 1 \\
7 & 11 \\
8 & 8 \\
9 & 8 \\
\bottomrule
\end{tabular}
| select position where cup = 'dnq' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>division</th>
<th>tier</th>
<th>position</th>
<th>cup</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1994-95</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>7</td>
<td>quarter-final</td>
</tr>
<tr>
<th>1</th>
<td>1995-96</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>13</td>
<td>round 1</td>
</tr>
<tr>
<th>2</th>
<td>1997-97</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>8</td>
<td>dnq</td>
</tr>
<tr>
<th>3</th>
<td>1997-98</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>6</td>
<td>dnq</td>
</tr>
<tr>
<th>4</th>
<td>1998-99</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>8</td>
<td>dnq</td>
</tr>
<tr>
<th>5</th>
<td>1999-00</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>5</td>
<td>dnq</td>
</tr>
<tr>
<th>6</th>
<td>2000-01</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>9</td>
<td>dnq</td>
</tr>
<tr>
<th>7</th>
<td>2001-02</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>10</td>
<td>dnq</td>
</tr>
<tr>
<th>8</th>
<td>2002-03</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>4</td>
<td>round 1</td>
</tr>
<tr>
<th>9</th>
<td>2003-04</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>1</td>
<td>dnq</td>
</tr>
<tr>
<th>10</th>
<td>2004-05</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>6</td>
<td>quarter-final</td>
</tr>
<tr>
<th>11</th>
<td>2005-06</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>11</td>
<td>dnq</td>
</tr>
<tr>
<th>12</th>
<td>2006-07</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>8</td>
<td>dnq</td>
</tr>
<tr>
<th>13</th>
<td>2007-08</td>
<td>regionalliga sud</td>
<td>iii</td>
<td>8</td>
<td>dnq</td>
</tr>
<tr>
<th>14</th>
<td>2008-09</td>
<td>3. liga</td>
<td>iii</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>2009-10</td>
<td>3. liga</td>
<td>iii</td>
<td>8</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>2010-11</td>
<td>3. liga</td>
<td>iii</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>2011-12</td>
<td>regionalliga sud</td>
<td>iv</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>2012-13</td>
<td>regionalliga bayern</td>
<td>iv</td>
<td>2</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>position</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>8</td>
</tr>
<tr>
<th>1</th>
<td>6</td>
</tr>
<tr>
<th>2</th>
<td>8</td>
</tr>
<tr>
<th>3</th>
<td>5</td>
</tr>
<tr>
<th>4</th>
<td>9</td>
</tr>
<tr>
<th>5</th>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>1</td>
</tr>
<tr>
<th>7</th>
<td>11</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
</tr>
<tr>
<th>9</th>
<td>8</td>
</tr>
</tbody>
</table> | select position where cup = 'dnq' <table_name> : table | | season | division | tier | position | cup |
|---:|:---------|:--------------------|:-------|-----------:|:--------------|
| 0 | 1994-95 | regionalliga sud | iii | 7 | quarter-final |
| 1 | 1995-96 | regionalliga sud | iii | 13 | round 1 |
| 2 | 1997-97 | regionalliga sud | iii | 8 | dnq |
| 3 | 1997-98 | regionalliga sud | iii | 6 | dnq |
| 4 | 1998-99 | regionalliga sud | iii | 8 | dnq |
| 5 | 1999-00 | regionalliga sud | iii | 5 | dnq |
| 6 | 2000-01 | regionalliga sud | iii | 9 | dnq |
| 7 | 2001-02 | regionalliga sud | iii | 10 | dnq |
| 8 | 2002-03 | regionalliga sud | iii | 4 | round 1 |
| 9 | 2003-04 | regionalliga sud | iii | 1 | dnq |
| 10 | 2004-05 | regionalliga sud | iii | 6 | quarter-final |
| 11 | 2005-06 | regionalliga sud | iii | 11 | dnq |
| 12 | 2006-07 | regionalliga sud | iii | 8 | dnq |
| 13 | 2007-08 | regionalliga sud | iii | 8 | dnq |
| 14 | 2008-09 | 3. liga | iii | 5 | none |
| 15 | 2009-10 | 3. liga | iii | 8 | none |
| 16 | 2010-11 | 3. liga | iii | 20 | none |
| 17 | 2011-12 | regionalliga sud | iv | 14 | none |
| 18 | 2012-13 | regionalliga bayern | iv | 2 | none | | | | position |
|---:|-----------:|
| 0 | 8 |
| 1 | 6 |
| 2 | 8 |
| 3 | 5 |
| 4 | 9 |
| 5 | 10 |
| 6 | 1 |
| 7 | 11 |
| 8 | 8 |
| 9 | 8 | | [
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select count ( * ) where competition = 'world cup' col : year | competition | venue | position | event | notes row 1 : 2001 | world youth championships | debrecen, hungary | 4th | 400 m | none row 2 : 2002 | asian games | busan, south korea | 2nd | 4x400 m relay | none row 3 : 2005 | asian championships | incheon, south korea | 2nd | 4x400 m relay | none row 4 : 2005 | universiade | izmir, turkey | 6th | 4x400 m relay | none row 5 : 2006 | asian games | doha, qatar | 2nd | 4x400 m relay | none row 6 : 2006 | asian games | doha, qatar | 1st | 400 m | none row 7 : 2006 | world cup | athens, greece | 7th | 400 m | none row 8 : 2007 | universiade | bangkok, thailand | 1st | 400 m | none row 9 : 2011 | universiade | shenzhen, china | none | 400 m | dq | col : count ( "*" ) row 1 : 1 | select count ( * ) where competition = 'world cup' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & competition & venue & position & event & notes \\
\midrule
0 & 2001 & world youth championships & debrecen, hungary & 4th & 400 m & none \\
1 & 2002 & asian games & busan, south korea & 2nd & 4x400 m relay & none \\
2 & 2005 & asian championships & incheon, south korea & 2nd & 4x400 m relay & none \\
3 & 2005 & universiade & izmir, turkey & 6th & 4x400 m relay & none \\
4 & 2006 & asian games & doha, qatar & 2nd & 4x400 m relay & none \\
5 & 2006 & asian games & doha, qatar & 1st & 400 m & none \\
6 & 2006 & world cup & athens, greece & 7th & 400 m & none \\
7 & 2007 & universiade & bangkok, thailand & 1st & 400 m & none \\
8 & 2011 & universiade & shenzhen, china & none & 400 m & dq \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where competition = 'world cup' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>competition</th>
<th>venue</th>
<th>position</th>
<th>event</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2001</td>
<td>world youth championships</td>
<td>debrecen, hungary</td>
<td>4th</td>
<td>400 m</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2002</td>
<td>asian games</td>
<td>busan, south korea</td>
<td>2nd</td>
<td>4x400 m relay</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>asian championships</td>
<td>incheon, south korea</td>
<td>2nd</td>
<td>4x400 m relay</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2005</td>
<td>universiade</td>
<td>izmir, turkey</td>
<td>6th</td>
<td>4x400 m relay</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2006</td>
<td>asian games</td>
<td>doha, qatar</td>
<td>2nd</td>
<td>4x400 m relay</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2006</td>
<td>asian games</td>
<td>doha, qatar</td>
<td>1st</td>
<td>400 m</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2006</td>
<td>world cup</td>
<td>athens, greece</td>
<td>7th</td>
<td>400 m</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>2007</td>
<td>universiade</td>
<td>bangkok, thailand</td>
<td>1st</td>
<td>400 m</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>universiade</td>
<td>shenzhen, china</td>
<td>none</td>
<td>400 m</td>
<td>dq</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where competition = 'world cup' <table_name> : table | | year | competition | venue | position | event | notes |
|---:|-------:|:--------------------------|:---------------------|:-----------|:--------------|:--------|
| 0 | 2001 | world youth championships | debrecen, hungary | 4th | 400 m | none |
| 1 | 2002 | asian games | busan, south korea | 2nd | 4x400 m relay | none |
| 2 | 2005 | asian championships | incheon, south korea | 2nd | 4x400 m relay | none |
| 3 | 2005 | universiade | izmir, turkey | 6th | 4x400 m relay | none |
| 4 | 2006 | asian games | doha, qatar | 2nd | 4x400 m relay | none |
| 5 | 2006 | asian games | doha, qatar | 1st | 400 m | none |
| 6 | 2006 | world cup | athens, greece | 7th | 400 m | none |
| 7 | 2007 | universiade | bangkok, thailand | 1st | 400 m | none |
| 8 | 2011 | universiade | shenzhen, china | none | 400 m | dq | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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] |
select movements where section = 'sodra norrland' col : season | level | division | section | position | movements row 1 : 1960 | tier 4 | division 4 | halsingland | 3rd | none row 2 : 1961 | tier 4 | division 4 | halsingland | 2nd | none row 3 : 1962 | tier 4 | division 4 | halsingland | 1st | promoted row 4 : 1963 | tier 3 | division 3 | sodra norrland | 6th | none row 5 : 1964 | tier 3 | division 3 | sodra norrland nedre | 4th | none row 6 : 1965 | tier 3 | division 3 | sodra norrland nedre | 10th | relegated row 7 : 1966 | tier 4 | division 4 | halsingland | 9th | none row 8 : 1967 | tier 4 | division 4 | halsingland | 2nd | none row 9 : 1968 | tier 4 | division 4 | halsingland | 6th | none row 10 : 1969 | tier 4 | division 4 | halsingland | 3rd | none row 11 : 1970 | tier 4 | division 4 | halsingland | 2nd | none row 12 : 1971 | tier 4 | division 4 | halsingland | 1st | promotion playoffs - promoted row 13 : 1972 | tier 3 | division 3 | norra svealand | 6th | none row 14 : 1973 | tier 3 | division 3 | norra svealand | 11th | relegated row 15 : 1974 | tier 4 | division 4 | halsingland | 1st | promoted row 16 : 1975 | tier 3 | division 3 | sodra norrland | 9th | none row 17 : 1976 | tier 3 | division 3 | sodra norrland | 9th | none row 18 : 1977 | tier 3 | division 3 | sodra norrland | 9th | none row 19 : 1978 | tier 3 | division 3 | sodra norrland | 6th | none row 20 : 1979 | tier 3 | division 3 | sodra norrland | 9th | none row 21 : 1980 | tier 3 | division 3 | sodra norrland | 7th | none row 22 : 1981 | tier 3 | division 3 | sodra norrland | 9th | none row 23 : 1982 | tier 3 | division 3 | sodra norrland | 12th | relegated row 24 : 1982 | tier 4 | division 4 | halsingland | 3rd | none | col : movements row 1 : none row 2 : none row 3 : none row 4 : none row 5 : none row 6 : none row 7 : none row 8 : none row 9 : relegated | select movements where section = 'sodra norrland' <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & level & division & section & position & movements \\
\midrule
0 & 1960 & tier 4 & division 4 & halsingland & 3rd & none \\
1 & 1961 & tier 4 & division 4 & halsingland & 2nd & none \\
2 & 1962 & tier 4 & division 4 & halsingland & 1st & promoted \\
3 & 1963 & tier 3 & division 3 & sodra norrland & 6th & none \\
4 & 1964 & tier 3 & division 3 & sodra norrland nedre & 4th & none \\
5 & 1965 & tier 3 & division 3 & sodra norrland nedre & 10th & relegated \\
6 & 1966 & tier 4 & division 4 & halsingland & 9th & none \\
7 & 1967 & tier 4 & division 4 & halsingland & 2nd & none \\
8 & 1968 & tier 4 & division 4 & halsingland & 6th & none \\
9 & 1969 & tier 4 & division 4 & halsingland & 3rd & none \\
10 & 1970 & tier 4 & division 4 & halsingland & 2nd & none \\
11 & 1971 & tier 4 & division 4 & halsingland & 1st & promotion playoffs - promoted \\
12 & 1972 & tier 3 & division 3 & norra svealand & 6th & none \\
13 & 1973 & tier 3 & division 3 & norra svealand & 11th & relegated \\
14 & 1974 & tier 4 & division 4 & halsingland & 1st & promoted \\
15 & 1975 & tier 3 & division 3 & sodra norrland & 9th & none \\
16 & 1976 & tier 3 & division 3 & sodra norrland & 9th & none \\
17 & 1977 & tier 3 & division 3 & sodra norrland & 9th & none \\
18 & 1978 & tier 3 & division 3 & sodra norrland & 6th & none \\
19 & 1979 & tier 3 & division 3 & sodra norrland & 9th & none \\
20 & 1980 & tier 3 & division 3 & sodra norrland & 7th & none \\
21 & 1981 & tier 3 & division 3 & sodra norrland & 9th & none \\
22 & 1982 & tier 3 & division 3 & sodra norrland & 12th & relegated \\
23 & 1982 & tier 4 & division 4 & halsingland & 3rd & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& movements \\
\midrule
0 & none \\
1 & none \\
2 & none \\
3 & none \\
4 & none \\
5 & none \\
6 & none \\
7 & none \\
8 & relegated \\
\bottomrule
\end{tabular}
| select movements where section = 'sodra norrland' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>level</th>
<th>division</th>
<th>section</th>
<th>position</th>
<th>movements</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1960</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1961</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1962</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>1st</td>
<td>promoted</td>
</tr>
<tr>
<th>3</th>
<td>1963</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1964</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland nedre</td>
<td>4th</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1965</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland nedre</td>
<td>10th</td>
<td>relegated</td>
</tr>
<tr>
<th>6</th>
<td>1966</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1967</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1968</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1969</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>1970</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>1971</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>1st</td>
<td>promotion playoffs - promoted</td>
</tr>
<tr>
<th>12</th>
<td>1972</td>
<td>tier 3</td>
<td>division 3</td>
<td>norra svealand</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>1973</td>
<td>tier 3</td>
<td>division 3</td>
<td>norra svealand</td>
<td>11th</td>
<td>relegated</td>
</tr>
<tr>
<th>14</th>
<td>1974</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>1st</td>
<td>promoted</td>
</tr>
<tr>
<th>15</th>
<td>1975</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>1976</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>1977</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>1978</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>1979</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>1980</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>7th</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>1981</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>1982</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>12th</td>
<td>relegated</td>
</tr>
<tr>
<th>23</th>
<td>1982</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>3rd</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>movements</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>relegated</td>
</tr>
</tbody>
</table> | select movements where section = 'sodra norrland' <table_name> : table | | season | level | division | section | position | movements |
|---:|---------:|:--------|:-----------|:---------------------|:-----------|:------------------------------|
| 0 | 1960 | tier 4 | division 4 | halsingland | 3rd | none |
| 1 | 1961 | tier 4 | division 4 | halsingland | 2nd | none |
| 2 | 1962 | tier 4 | division 4 | halsingland | 1st | promoted |
| 3 | 1963 | tier 3 | division 3 | sodra norrland | 6th | none |
| 4 | 1964 | tier 3 | division 3 | sodra norrland nedre | 4th | none |
| 5 | 1965 | tier 3 | division 3 | sodra norrland nedre | 10th | relegated |
| 6 | 1966 | tier 4 | division 4 | halsingland | 9th | none |
| 7 | 1967 | tier 4 | division 4 | halsingland | 2nd | none |
| 8 | 1968 | tier 4 | division 4 | halsingland | 6th | none |
| 9 | 1969 | tier 4 | division 4 | halsingland | 3rd | none |
| 10 | 1970 | tier 4 | division 4 | halsingland | 2nd | none |
| 11 | 1971 | tier 4 | division 4 | halsingland | 1st | promotion playoffs - promoted |
| 12 | 1972 | tier 3 | division 3 | norra svealand | 6th | none |
| 13 | 1973 | tier 3 | division 3 | norra svealand | 11th | relegated |
| 14 | 1974 | tier 4 | division 4 | halsingland | 1st | promoted |
| 15 | 1975 | tier 3 | division 3 | sodra norrland | 9th | none |
| 16 | 1976 | tier 3 | division 3 | sodra norrland | 9th | none |
| 17 | 1977 | tier 3 | division 3 | sodra norrland | 9th | none |
| 18 | 1978 | tier 3 | division 3 | sodra norrland | 6th | none |
| 19 | 1979 | tier 3 | division 3 | sodra norrland | 9th | none |
| 20 | 1980 | tier 3 | division 3 | sodra norrland | 7th | none |
| 21 | 1981 | tier 3 | division 3 | sodra norrland | 9th | none |
| 22 | 1982 | tier 3 | division 3 | sodra norrland | 12th | relegated |
| 23 | 1982 | tier 4 | division 4 | halsingland | 3rd | none | | | | movements |
|---:|:------------|
| 0 | none |
| 1 | none |
| 2 | none |
| 3 | none |
| 4 | none |
| 5 | none |
| 6 | none |
| 7 | none |
| 8 | relegated | | [
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] |
select count ( version ) where in service = 4 col : model | origin | type | version | in service | notes row 1 : larc-v | united states | amphibious support vehicle | larc-v | 5 | most refurbished in 2006 row 2 : gkn aquatrack | united kingdom | amphibious support vehicle | aquatrack | 2 | introduced in mid 1990s. originally owned by the office of civil defense but under pmc stewardship row 3 : am general hmmwv | united states | light utility vehicle | m998a1 m1038a1 m1025a1 | none | divided into several variants and series row 4 : maxi-ambulance | united states | light utility vehicle | m997a2 | 4 | 150 delivered to afp on november 2011, pmc received 50 units row 5 : m939 truck | united states | heavy utility vehicle | m923 | none | several delivered to afp in 2013, several units for the marines row 6 : m35 truck | united states | 2 1/2-ton utility vehicle | m35 | none | divided into several variants and series. more delivered in 2013 row 7 : m151 | united states | 1/4-ton light utility vehicle and weapons carrier | standard | none | in service, several carrying m40 106mm recoilless rifle row 8 : delta mini cruiser | philippines | 1/4-ton light utility vehicle | m1777 | none | divided into several variants and series, including short and stretched utility and armed variants, and modified variants for specialized units row 9 : marine multi-purpose vehicle | philippines | light utility vehicle and weapons carrier | standard | none | to replace the m151 mutt, usually armed with an m40 106mm recoilless rifle, or as a cheaper alternative to the humvee row 10 : km-50 series | republic of korea | 5-ton utility vehicle | km-500 | 12 | 155mm artillery prime mover. 1st batch of 6 delivered 2012 row 11 : km-45 series | republic of korea | 1 1/2-ton utility vehicle | km-450 | >50 | 3000 purchased by afp on 2007, 1000 units shared by navy/marines and air force row 12 : km-45 series | republic of korea | field ambulance | km-451 | 12 | 500 purchased by afp in 2012, 200 went to the marines | col : count ( "version" ) row 1 : 1 | select count ( version ) where in service = 4 <table_name> : table \begin{tabular}{lllllll}
\toprule
& model & origin & type & version & in service & notes \\
\midrule
0 & larc-v & united states & amphibious support vehicle & larc-v & 5 & most refurbished in 2006 \\
1 & gkn aquatrack & united kingdom & amphibious support vehicle & aquatrack & 2 & introduced in mid 1990s. originally owned by the office of civil defense but under pmc stewardship \\
2 & am general hmmwv & united states & light utility vehicle & m998a1 m1038a1 m1025a1 & none & divided into several variants and series \\
3 & maxi-ambulance & united states & light utility vehicle & m997a2 & 4 & 150 delivered to afp on november 2011, pmc received 50 units \\
4 & m939 truck & united states & heavy utility vehicle & m923 & none & several delivered to afp in 2013, several units for the marines \\
5 & m35 truck & united states & 2 1/2-ton utility vehicle & m35 & none & divided into several variants and series. more delivered in 2013 \\
6 & m151 & united states & 1/4-ton light utility vehicle and weapons carrier & standard & none & in service, several carrying m40 106mm recoilless rifle \\
7 & delta mini cruiser & philippines & 1/4-ton light utility vehicle & m1777 & none & divided into several variants and series, including short and stretched utility and armed variants, and modified variants for specialized units \\
8 & marine multi-purpose vehicle & philippines & light utility vehicle and weapons carrier & standard & none & to replace the m151 mutt, usually armed with an m40 106mm recoilless rifle, or as a cheaper alternative to the humvee \\
9 & km-50 series & republic of korea & 5-ton utility vehicle & km-500 & 12 & 155mm artillery prime mover. 1st batch of 6 delivered 2012 \\
10 & km-45 series & republic of korea & 1 1/2-ton utility vehicle & km-450 & >50 & 3000 purchased by afp on 2007, 1000 units shared by navy/marines and air force \\
11 & km-45 series & republic of korea & field ambulance & km-451 & 12 & 500 purchased by afp in 2012, 200 went to the marines \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "version" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( version ) where in service = 4 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>model</th>
<th>origin</th>
<th>type</th>
<th>version</th>
<th>in service</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>larc-v</td>
<td>united states</td>
<td>amphibious support vehicle</td>
<td>larc-v</td>
<td>5</td>
<td>most refurbished in 2006</td>
</tr>
<tr>
<th>1</th>
<td>gkn aquatrack</td>
<td>united kingdom</td>
<td>amphibious support vehicle</td>
<td>aquatrack</td>
<td>2</td>
<td>introduced in mid 1990s. originally owned by the office of civil defense but under pmc stewardship</td>
</tr>
<tr>
<th>2</th>
<td>am general hmmwv</td>
<td>united states</td>
<td>light utility vehicle</td>
<td>m998a1 m1038a1 m1025a1</td>
<td>none</td>
<td>divided into several variants and series</td>
</tr>
<tr>
<th>3</th>
<td>maxi-ambulance</td>
<td>united states</td>
<td>light utility vehicle</td>
<td>m997a2</td>
<td>4</td>
<td>150 delivered to afp on november 2011, pmc received 50 units</td>
</tr>
<tr>
<th>4</th>
<td>m939 truck</td>
<td>united states</td>
<td>heavy utility vehicle</td>
<td>m923</td>
<td>none</td>
<td>several delivered to afp in 2013, several units for the marines</td>
</tr>
<tr>
<th>5</th>
<td>m35 truck</td>
<td>united states</td>
<td>2 1/2-ton utility vehicle</td>
<td>m35</td>
<td>none</td>
<td>divided into several variants and series. more delivered in 2013</td>
</tr>
<tr>
<th>6</th>
<td>m151</td>
<td>united states</td>
<td>1/4-ton light utility vehicle and weapons carrier</td>
<td>standard</td>
<td>none</td>
<td>in service, several carrying m40 106mm recoilless rifle</td>
</tr>
<tr>
<th>7</th>
<td>delta mini cruiser</td>
<td>philippines</td>
<td>1/4-ton light utility vehicle</td>
<td>m1777</td>
<td>none</td>
<td>divided into several variants and series, including short and stretched utility and armed variants, and modified variants for specialized units</td>
</tr>
<tr>
<th>8</th>
<td>marine multi-purpose vehicle</td>
<td>philippines</td>
<td>light utility vehicle and weapons carrier</td>
<td>standard</td>
<td>none</td>
<td>to replace the m151 mutt, usually armed with an m40 106mm recoilless rifle, or as a cheaper alternative to the humvee</td>
</tr>
<tr>
<th>9</th>
<td>km-50 series</td>
<td>republic of korea</td>
<td>5-ton utility vehicle</td>
<td>km-500</td>
<td>12</td>
<td>155mm artillery prime mover. 1st batch of 6 delivered 2012</td>
</tr>
<tr>
<th>10</th>
<td>km-45 series</td>
<td>republic of korea</td>
<td>1 1/2-ton utility vehicle</td>
<td>km-450</td>
<td>>50</td>
<td>3000 purchased by afp on 2007, 1000 units shared by navy/marines and air force</td>
</tr>
<tr>
<th>11</th>
<td>km-45 series</td>
<td>republic of korea</td>
<td>field ambulance</td>
<td>km-451</td>
<td>12</td>
<td>500 purchased by afp in 2012, 200 went to the marines</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "version" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( version ) where in service = 4 <table_name> : table | | model | origin | type | version | in service | notes |
|---:|:-----------------------------|:------------------|:--------------------------------------------------|:-----------------------|:-------------|:------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | larc-v | united states | amphibious support vehicle | larc-v | 5 | most refurbished in 2006 |
| 1 | gkn aquatrack | united kingdom | amphibious support vehicle | aquatrack | 2 | introduced in mid 1990s. originally owned by the office of civil defense but under pmc stewardship |
| 2 | am general hmmwv | united states | light utility vehicle | m998a1 m1038a1 m1025a1 | none | divided into several variants and series |
| 3 | maxi-ambulance | united states | light utility vehicle | m997a2 | 4 | 150 delivered to afp on november 2011, pmc received 50 units |
| 4 | m939 truck | united states | heavy utility vehicle | m923 | none | several delivered to afp in 2013, several units for the marines |
| 5 | m35 truck | united states | 2 1/2-ton utility vehicle | m35 | none | divided into several variants and series. more delivered in 2013 |
| 6 | m151 | united states | 1/4-ton light utility vehicle and weapons carrier | standard | none | in service, several carrying m40 106mm recoilless rifle |
| 7 | delta mini cruiser | philippines | 1/4-ton light utility vehicle | m1777 | none | divided into several variants and series, including short and stretched utility and armed variants, and modified variants for specialized units |
| 8 | marine multi-purpose vehicle | philippines | light utility vehicle and weapons carrier | standard | none | to replace the m151 mutt, usually armed with an m40 106mm recoilless rifle, or as a cheaper alternative to the humvee |
| 9 | km-50 series | republic of korea | 5-ton utility vehicle | km-500 | 12 | 155mm artillery prime mover. 1st batch of 6 delivered 2012 |
| 10 | km-45 series | republic of korea | 1 1/2-ton utility vehicle | km-450 | >50 | 3000 purchased by afp on 2007, 1000 units shared by navy/marines and air force |
| 11 | km-45 series | republic of korea | field ambulance | km-451 | 12 | 500 purchased by afp in 2012, 200 went to the marines | | | | count ( "version" ) |
|---:|----------------------:|
| 0 | 1 | | [
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select brakes where notes = 'fitted with buckeye couplings' col : tops design code | electrical system | max speed | weight | brakes | route availability | notes row 1 : 08-0av | 90 v | 20 mph (32 km/h) | 49.8 te (496 kn) | vacuum | 5 | none row 2 : 08-0bx | 110 v | 20 mph (32 km/h) | 50.4 te (502 kn) | dual | 5 | none row 3 : 08-0ca | 90 v | 20 mph (32 km/h) | 49.6 te (494 kn) | air | 5 | none row 4 : 08-0dv | 90 v | 15 mph (24 km/h) | 49.8 te (496 kn) | vacuum | 5 | none row 5 : 08-0bx | 90 v | 15 mph (24 km/h) | 50.4 te (502 kn) | dual | 5 | none row 6 : 08-0fa | 90 v | 15 mph (24 km/h) | 49.6 te (494 kn) | air | 5 | none row 7 : 08-0kx | 110 v | 15 mph (24 km/h) | 50.4 te (502 kn) | dual | 5 | none row 8 : 08-0lx | 110 v | 15 mph (24 km/h) | 50.4 te (502 kn) | dual | 5 | scharfenberg adapter fitted row 9 : 08-0ma | 110 v | 15 mph (24 km/h) | 49.8 te (496 kn) | air | 5 | none row 10 : 08-0na | 90 v | 15 mph (24 km/h) | 49.8 te (496 kn) | air | 5 | fitted with buckeye couplings row 11 : 08-0pa | 90 v | 15 mph (24 km/h) | 51 te (508 kn) | air | 6 | fitted with buckeye couplings row 12 : 08-0qa | 90 v | 15 mph (24 km/h) | 51 te (508 kn) | air | 6 | fitted with buckeye couplings row 13 : 08-0ra | 110 v | 15 mph (24 km/h) | 51 te (508 kn) | air | 6 | fitted with buckeye couplings row 14 : 08-0sa | 110 v | 15 mph (24 km/h) | 49 te (488 kn) | air | 6 | none | col : brakes row 1 : air row 2 : air row 3 : air row 4 : air | select brakes where notes = 'fitted with buckeye couplings' <table_name> : table \begin{tabular}{llllllll}
\toprule
& tops design code & electrical system & max speed & weight & brakes & route availability & notes \\
\midrule
0 & 08-0av & 90 v & 20 mph (32 km/h) & 49.8 te (496 kn) & vacuum & 5 & none \\
1 & 08-0bx & 110 v & 20 mph (32 km/h) & 50.4 te (502 kn) & dual & 5 & none \\
2 & 08-0ca & 90 v & 20 mph (32 km/h) & 49.6 te (494 kn) & air & 5 & none \\
3 & 08-0dv & 90 v & 15 mph (24 km/h) & 49.8 te (496 kn) & vacuum & 5 & none \\
4 & 08-0bx & 90 v & 15 mph (24 km/h) & 50.4 te (502 kn) & dual & 5 & none \\
5 & 08-0fa & 90 v & 15 mph (24 km/h) & 49.6 te (494 kn) & air & 5 & none \\
6 & 08-0kx & 110 v & 15 mph (24 km/h) & 50.4 te (502 kn) & dual & 5 & none \\
7 & 08-0lx & 110 v & 15 mph (24 km/h) & 50.4 te (502 kn) & dual & 5 & scharfenberg adapter fitted \\
8 & 08-0ma & 110 v & 15 mph (24 km/h) & 49.8 te (496 kn) & air & 5 & none \\
9 & 08-0na & 90 v & 15 mph (24 km/h) & 49.8 te (496 kn) & air & 5 & fitted with buckeye couplings \\
10 & 08-0pa & 90 v & 15 mph (24 km/h) & 51 te (508 kn) & air & 6 & fitted with buckeye couplings \\
11 & 08-0qa & 90 v & 15 mph (24 km/h) & 51 te (508 kn) & air & 6 & fitted with buckeye couplings \\
12 & 08-0ra & 110 v & 15 mph (24 km/h) & 51 te (508 kn) & air & 6 & fitted with buckeye couplings \\
13 & 08-0sa & 110 v & 15 mph (24 km/h) & 49 te (488 kn) & air & 6 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& brakes \\
\midrule
0 & air \\
1 & air \\
2 & air \\
3 & air \\
\bottomrule
\end{tabular}
| select brakes where notes = 'fitted with buckeye couplings' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>tops design code</th>
<th>electrical system</th>
<th>max speed</th>
<th>weight</th>
<th>brakes</th>
<th>route availability</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>08-0av</td>
<td>90 v</td>
<td>20 mph (32 km/h)</td>
<td>49.8 te (496 kn)</td>
<td>vacuum</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>08-0bx</td>
<td>110 v</td>
<td>20 mph (32 km/h)</td>
<td>50.4 te (502 kn)</td>
<td>dual</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>08-0ca</td>
<td>90 v</td>
<td>20 mph (32 km/h)</td>
<td>49.6 te (494 kn)</td>
<td>air</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>08-0dv</td>
<td>90 v</td>
<td>15 mph (24 km/h)</td>
<td>49.8 te (496 kn)</td>
<td>vacuum</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>08-0bx</td>
<td>90 v</td>
<td>15 mph (24 km/h)</td>
<td>50.4 te (502 kn)</td>
<td>dual</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>08-0fa</td>
<td>90 v</td>
<td>15 mph (24 km/h)</td>
<td>49.6 te (494 kn)</td>
<td>air</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>08-0kx</td>
<td>110 v</td>
<td>15 mph (24 km/h)</td>
<td>50.4 te (502 kn)</td>
<td>dual</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>08-0lx</td>
<td>110 v</td>
<td>15 mph (24 km/h)</td>
<td>50.4 te (502 kn)</td>
<td>dual</td>
<td>5</td>
<td>scharfenberg adapter fitted</td>
</tr>
<tr>
<th>8</th>
<td>08-0ma</td>
<td>110 v</td>
<td>15 mph (24 km/h)</td>
<td>49.8 te (496 kn)</td>
<td>air</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>08-0na</td>
<td>90 v</td>
<td>15 mph (24 km/h)</td>
<td>49.8 te (496 kn)</td>
<td>air</td>
<td>5</td>
<td>fitted with buckeye couplings</td>
</tr>
<tr>
<th>10</th>
<td>08-0pa</td>
<td>90 v</td>
<td>15 mph (24 km/h)</td>
<td>51 te (508 kn)</td>
<td>air</td>
<td>6</td>
<td>fitted with buckeye couplings</td>
</tr>
<tr>
<th>11</th>
<td>08-0qa</td>
<td>90 v</td>
<td>15 mph (24 km/h)</td>
<td>51 te (508 kn)</td>
<td>air</td>
<td>6</td>
<td>fitted with buckeye couplings</td>
</tr>
<tr>
<th>12</th>
<td>08-0ra</td>
<td>110 v</td>
<td>15 mph (24 km/h)</td>
<td>51 te (508 kn)</td>
<td>air</td>
<td>6</td>
<td>fitted with buckeye couplings</td>
</tr>
<tr>
<th>13</th>
<td>08-0sa</td>
<td>110 v</td>
<td>15 mph (24 km/h)</td>
<td>49 te (488 kn)</td>
<td>air</td>
<td>6</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>brakes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>air</td>
</tr>
<tr>
<th>1</th>
<td>air</td>
</tr>
<tr>
<th>2</th>
<td>air</td>
</tr>
<tr>
<th>3</th>
<td>air</td>
</tr>
</tbody>
</table> | select brakes where notes = 'fitted with buckeye couplings' <table_name> : table | | tops design code | electrical system | max speed | weight | brakes | route availability | notes |
|---:|:-------------------|:--------------------|:-----------------|:-----------------|:---------|---------------------:|:------------------------------|
| 0 | 08-0av | 90 v | 20 mph (32 km/h) | 49.8 te (496 kn) | vacuum | 5 | none |
| 1 | 08-0bx | 110 v | 20 mph (32 km/h) | 50.4 te (502 kn) | dual | 5 | none |
| 2 | 08-0ca | 90 v | 20 mph (32 km/h) | 49.6 te (494 kn) | air | 5 | none |
| 3 | 08-0dv | 90 v | 15 mph (24 km/h) | 49.8 te (496 kn) | vacuum | 5 | none |
| 4 | 08-0bx | 90 v | 15 mph (24 km/h) | 50.4 te (502 kn) | dual | 5 | none |
| 5 | 08-0fa | 90 v | 15 mph (24 km/h) | 49.6 te (494 kn) | air | 5 | none |
| 6 | 08-0kx | 110 v | 15 mph (24 km/h) | 50.4 te (502 kn) | dual | 5 | none |
| 7 | 08-0lx | 110 v | 15 mph (24 km/h) | 50.4 te (502 kn) | dual | 5 | scharfenberg adapter fitted |
| 8 | 08-0ma | 110 v | 15 mph (24 km/h) | 49.8 te (496 kn) | air | 5 | none |
| 9 | 08-0na | 90 v | 15 mph (24 km/h) | 49.8 te (496 kn) | air | 5 | fitted with buckeye couplings |
| 10 | 08-0pa | 90 v | 15 mph (24 km/h) | 51 te (508 kn) | air | 6 | fitted with buckeye couplings |
| 11 | 08-0qa | 90 v | 15 mph (24 km/h) | 51 te (508 kn) | air | 6 | fitted with buckeye couplings |
| 12 | 08-0ra | 110 v | 15 mph (24 km/h) | 51 te (508 kn) | air | 6 | fitted with buckeye couplings |
| 13 | 08-0sa | 110 v | 15 mph (24 km/h) | 49 te (488 kn) | air | 6 | none | | | | brakes |
|---:|:---------|
| 0 | air |
| 1 | air |
| 2 | air |
| 3 | air | | [
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select agg. where team 1 = 'cska moscow' col : team 1 | agg. | team 2 | 1st leg | 2nd leg row 1 : benfica | 3-2 | paris saint-germain | 2-1 | 1-1 row 2 : dynamo kyiv | 2-1 | manchester city | 2-0 | 0-1 row 3 : twente | 3-2 | zenit saint petersburg | 3-0 | 0-2 row 4 : cska moscow | 1-3 | porto | 0-1 | 1-2 row 5 : psv eindhoven | 1-0 | rangers | 0-0 | 1-0 row 6 : bayer leverkusen | 3-5 | villarreal | 2-3 | 1-2 row 7 : ajax | 0-4 | spartak moscow | 0-1 | 0-3 row 8 : braga | 1-08 | liverpool | 1-0 | 0-0 | col : agg. row 1 : 1-3 | select agg. where team 1 = 'cska moscow' <table_name> : table \begin{tabular}{llllll}
\toprule
& team 1 & agg. & team 2 & 1st leg & 2nd leg \\
\midrule
0 & benfica & 3-2 & paris saint-germain & 2-1 & 1-1 \\
1 & dynamo kyiv & 2-1 & manchester city & 2-0 & 0-1 \\
2 & twente & 3-2 & zenit saint petersburg & 3-0 & 0-2 \\
3 & cska moscow & 1-3 & porto & 0-1 & 1-2 \\
4 & psv eindhoven & 1-0 & rangers & 0-0 & 1-0 \\
5 & bayer leverkusen & 3-5 & villarreal & 2-3 & 1-2 \\
6 & ajax & 0-4 & spartak moscow & 0-1 & 0-3 \\
7 & braga & 1-08 & liverpool & 1-0 & 0-0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& agg. \\
\midrule
0 & 1-3 \\
\bottomrule
\end{tabular}
| select agg. where team 1 = 'cska moscow' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>team 1</th>
<th>agg.</th>
<th>team 2</th>
<th>1st leg</th>
<th>2nd leg</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>benfica</td>
<td>3-2</td>
<td>paris saint-germain</td>
<td>2-1</td>
<td>1-1</td>
</tr>
<tr>
<th>1</th>
<td>dynamo kyiv</td>
<td>2-1</td>
<td>manchester city</td>
<td>2-0</td>
<td>0-1</td>
</tr>
<tr>
<th>2</th>
<td>twente</td>
<td>3-2</td>
<td>zenit saint petersburg</td>
<td>3-0</td>
<td>0-2</td>
</tr>
<tr>
<th>3</th>
<td>cska moscow</td>
<td>1-3</td>
<td>porto</td>
<td>0-1</td>
<td>1-2</td>
</tr>
<tr>
<th>4</th>
<td>psv eindhoven</td>
<td>1-0</td>
<td>rangers</td>
<td>0-0</td>
<td>1-0</td>
</tr>
<tr>
<th>5</th>
<td>bayer leverkusen</td>
<td>3-5</td>
<td>villarreal</td>
<td>2-3</td>
<td>1-2</td>
</tr>
<tr>
<th>6</th>
<td>ajax</td>
<td>0-4</td>
<td>spartak moscow</td>
<td>0-1</td>
<td>0-3</td>
</tr>
<tr>
<th>7</th>
<td>braga</td>
<td>1-08</td>
<td>liverpool</td>
<td>1-0</td>
<td>0-0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>agg.</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1-3</td>
</tr>
</tbody>
</table> | select agg. where team 1 = 'cska moscow' <table_name> : table | | team 1 | agg. | team 2 | 1st leg | 2nd leg |
|---:|:-----------------|:-------|:-----------------------|:----------|:----------|
| 0 | benfica | 3-2 | paris saint-germain | 2-1 | 1-1 |
| 1 | dynamo kyiv | 2-1 | manchester city | 2-0 | 0-1 |
| 2 | twente | 3-2 | zenit saint petersburg | 3-0 | 0-2 |
| 3 | cska moscow | 1-3 | porto | 0-1 | 1-2 |
| 4 | psv eindhoven | 1-0 | rangers | 0-0 | 1-0 |
| 5 | bayer leverkusen | 3-5 | villarreal | 2-3 | 1-2 |
| 6 | ajax | 0-4 | spartak moscow | 0-1 | 0-3 |
| 7 | braga | 1-08 | liverpool | 1-0 | 0-0 | | | | agg. |
|---:|:-------|
| 0 | 1-3 | | [
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select year where notes = 'fugitive pieces (film)' col : year | group | award | result | notes row 1 : 1994 | venice film festival | best actor | won | before the rain (1994 film) row 2 : 1996 | new zealand film and tv awards | best foreign performer | won | broken english (1996 film) row 3 : 2006 | monaco international film festival | best actor | won | short order row 4 : 2007 | rome film fest | best actor | won | fugitive pieces (film) row 5 : 2008 | satellite awards | best actor in a supporting role | nominated | fugitive pieces (film) row 6 : 2008 | vancouver film critics circle | best supporting actor in a canadian film | nominated | fugitive pieces (film) row 7 : 2009 | genie awards | best performance by an actor in a supporting role | nominated | fugitive pieces (film) row 8 : 2012 | tetouan international mediterranean film festival | best actor | won | io sono li | col : year row 1 : 2007 row 2 : 2008 row 3 : 2008 row 4 : 2009 | select year where notes = 'fugitive pieces (film)' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & group & award & result & notes \\
\midrule
0 & 1994 & venice film festival & best actor & won & before the rain (1994 film) \\
1 & 1996 & new zealand film and tv awards & best foreign performer & won & broken english (1996 film) \\
2 & 2006 & monaco international film festival & best actor & won & short order \\
3 & 2007 & rome film fest & best actor & won & fugitive pieces (film) \\
4 & 2008 & satellite awards & best actor in a supporting role & nominated & fugitive pieces (film) \\
5 & 2008 & vancouver film critics circle & best supporting actor in a canadian film & nominated & fugitive pieces (film) \\
6 & 2009 & genie awards & best performance by an actor in a supporting role & nominated & fugitive pieces (film) \\
7 & 2012 & tetouan international mediterranean film festival & best actor & won & io sono li \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 2007 \\
1 & 2008 \\
2 & 2008 \\
3 & 2009 \\
\bottomrule
\end{tabular}
| select year where notes = 'fugitive pieces (film)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>group</th>
<th>award</th>
<th>result</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1994</td>
<td>venice film festival</td>
<td>best actor</td>
<td>won</td>
<td>before the rain (1994 film)</td>
</tr>
<tr>
<th>1</th>
<td>1996</td>
<td>new zealand film and tv awards</td>
<td>best foreign performer</td>
<td>won</td>
<td>broken english (1996 film)</td>
</tr>
<tr>
<th>2</th>
<td>2006</td>
<td>monaco international film festival</td>
<td>best actor</td>
<td>won</td>
<td>short order</td>
</tr>
<tr>
<th>3</th>
<td>2007</td>
<td>rome film fest</td>
<td>best actor</td>
<td>won</td>
<td>fugitive pieces (film)</td>
</tr>
<tr>
<th>4</th>
<td>2008</td>
<td>satellite awards</td>
<td>best actor in a supporting role</td>
<td>nominated</td>
<td>fugitive pieces (film)</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>vancouver film critics circle</td>
<td>best supporting actor in a canadian film</td>
<td>nominated</td>
<td>fugitive pieces (film)</td>
</tr>
<tr>
<th>6</th>
<td>2009</td>
<td>genie awards</td>
<td>best performance by an actor in a supporting role</td>
<td>nominated</td>
<td>fugitive pieces (film)</td>
</tr>
<tr>
<th>7</th>
<td>2012</td>
<td>tetouan international mediterranean film festival</td>
<td>best actor</td>
<td>won</td>
<td>io sono li</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2007</td>
</tr>
<tr>
<th>1</th>
<td>2008</td>
</tr>
<tr>
<th>2</th>
<td>2008</td>
</tr>
<tr>
<th>3</th>
<td>2009</td>
</tr>
</tbody>
</table> | select year where notes = 'fugitive pieces (film)' <table_name> : table | | year | group | award | result | notes |
|---:|-------:|:--------------------------------------------------|:--------------------------------------------------|:----------|:----------------------------|
| 0 | 1994 | venice film festival | best actor | won | before the rain (1994 film) |
| 1 | 1996 | new zealand film and tv awards | best foreign performer | won | broken english (1996 film) |
| 2 | 2006 | monaco international film festival | best actor | won | short order |
| 3 | 2007 | rome film fest | best actor | won | fugitive pieces (film) |
| 4 | 2008 | satellite awards | best actor in a supporting role | nominated | fugitive pieces (film) |
| 5 | 2008 | vancouver film critics circle | best supporting actor in a canadian film | nominated | fugitive pieces (film) |
| 6 | 2009 | genie awards | best performance by an actor in a supporting role | nominated | fugitive pieces (film) |
| 7 | 2012 | tetouan international mediterranean film festival | best actor | won | io sono li | | | | year |
|---:|-------:|
| 0 | 2007 |
| 1 | 2008 |
| 2 | 2008 |
| 3 | 2009 | | [
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select count ( fate ) where fate = 979 and launched = 37 col : name | pennant | builder | launched | original name | fate row 1 : wave baron | a242 | furness shipbuilding company | 19 february 1946 | empire flodden | scrapped in 1972 row 2 : wave chief | a265 | harland and wolff | 30 august 1946 | empire edgehill | scrapped in 1974 row 3 : wave commander | a244 | furness shipbuilding company | 21 april 1944 | empire paladin | scrapped in 1959 row 4 : wave conqueror | a245 | furness shipbuilding company | 27 november 1943 | empire law | scrapped in 1960 row 5 : wave duke | a246 | sir j. laing & sons ltd | 16 november 1944 | empire mars | scrapped in 1969 row 6 : wave emperor | a100 | furness shipbuilding company | 16 october 1944 | none | scrapped in 1966 row 7 : wave governor | a247 | furness shipbuilding company | 30 november 1944 | none | scrapped in 1960 row 8 : wave king | a182 | harland and wolff | 21 july 1944 | none | scrapped in 1966 row 9 : wave knight | a249 | sir j. laing & sons ltd | 22 october 1945 | empire naseby | scrapped in 1964 row 10 : wave laird | a119 | sir j. laing & sons ltd | 3 april 1946 | empire dunbar | scrapped in 1970 row 11 : wave liberator | a248 | furness shipbuilding company | 9 february 1944 | empire milner | scrapped in 1959 row 12 : wave master | a193 | sir j. laing & sons ltd | 20 may 1944 | empire salisbury | scrapped in 1963 row 13 : wave monarch | a264 | harland and wolff | 6 july 1944 | none | sold as oil hulk in 1960 row 14 : wave premier | a129 | furness shipbuilding company | 27 june 1946 | none | scrapped in 1960 row 15 : wave prince | a207 | sir j. laing & sons ltd | 27 july 1945 | empire herald | scrapped in 1971 row 16 : wave protector | a215 | furness shipbuilding company | 20 july 1944 | empire protector | scrapped in 1963 row 17 : wave regent | a210 | furness shipbuilding company | 29 march 1945 | none | scrapped in 1960 row 18 : wave ruler | a212 | furness shipbuilding company | 17 january 1946 | empire evesham | scrapped in 1977 row 19 : wave sovereign | a211 | furness shipbuilding company | 20 november 1945 | none | scrapped in 1966 row 20 : wave victor | a220 | furness shipbuilding company | 30 september 1943 | empire bounty | chartered to air ministry in 1960 | col : count ( "fate" ) row 1 : 0 | select count ( fate ) where fate = 979 and launched = 37 <table_name> : table \begin{tabular}{lllllll}
\toprule
& name & pennant & builder & launched & original name & fate \\
\midrule
0 & wave baron & a242 & furness shipbuilding company & 19 february 1946 & empire flodden & scrapped in 1972 \\
1 & wave chief & a265 & harland and wolff & 30 august 1946 & empire edgehill & scrapped in 1974 \\
2 & wave commander & a244 & furness shipbuilding company & 21 april 1944 & empire paladin & scrapped in 1959 \\
3 & wave conqueror & a245 & furness shipbuilding company & 27 november 1943 & empire law & scrapped in 1960 \\
4 & wave duke & a246 & sir j. laing & sons ltd & 16 november 1944 & empire mars & scrapped in 1969 \\
5 & wave emperor & a100 & furness shipbuilding company & 16 october 1944 & none & scrapped in 1966 \\
6 & wave governor & a247 & furness shipbuilding company & 30 november 1944 & none & scrapped in 1960 \\
7 & wave king & a182 & harland and wolff & 21 july 1944 & none & scrapped in 1966 \\
8 & wave knight & a249 & sir j. laing & sons ltd & 22 october 1945 & empire naseby & scrapped in 1964 \\
9 & wave laird & a119 & sir j. laing & sons ltd & 3 april 1946 & empire dunbar & scrapped in 1970 \\
10 & wave liberator & a248 & furness shipbuilding company & 9 february 1944 & empire milner & scrapped in 1959 \\
11 & wave master & a193 & sir j. laing & sons ltd & 20 may 1944 & empire salisbury & scrapped in 1963 \\
12 & wave monarch & a264 & harland and wolff & 6 july 1944 & none & sold as oil hulk in 1960 \\
13 & wave premier & a129 & furness shipbuilding company & 27 june 1946 & none & scrapped in 1960 \\
14 & wave prince & a207 & sir j. laing & sons ltd & 27 july 1945 & empire herald & scrapped in 1971 \\
15 & wave protector & a215 & furness shipbuilding company & 20 july 1944 & empire protector & scrapped in 1963 \\
16 & wave regent & a210 & furness shipbuilding company & 29 march 1945 & none & scrapped in 1960 \\
17 & wave ruler & a212 & furness shipbuilding company & 17 january 1946 & empire evesham & scrapped in 1977 \\
18 & wave sovereign & a211 & furness shipbuilding company & 20 november 1945 & none & scrapped in 1966 \\
19 & wave victor & a220 & furness shipbuilding company & 30 september 1943 & empire bounty & chartered to air ministry in 1960 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "fate" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( fate ) where fate = 979 and launched = 37 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>pennant</th>
<th>builder</th>
<th>launched</th>
<th>original name</th>
<th>fate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>wave baron</td>
<td>a242</td>
<td>furness shipbuilding company</td>
<td>19 february 1946</td>
<td>empire flodden</td>
<td>scrapped in 1972</td>
</tr>
<tr>
<th>1</th>
<td>wave chief</td>
<td>a265</td>
<td>harland and wolff</td>
<td>30 august 1946</td>
<td>empire edgehill</td>
<td>scrapped in 1974</td>
</tr>
<tr>
<th>2</th>
<td>wave commander</td>
<td>a244</td>
<td>furness shipbuilding company</td>
<td>21 april 1944</td>
<td>empire paladin</td>
<td>scrapped in 1959</td>
</tr>
<tr>
<th>3</th>
<td>wave conqueror</td>
<td>a245</td>
<td>furness shipbuilding company</td>
<td>27 november 1943</td>
<td>empire law</td>
<td>scrapped in 1960</td>
</tr>
<tr>
<th>4</th>
<td>wave duke</td>
<td>a246</td>
<td>sir j. laing & sons ltd</td>
<td>16 november 1944</td>
<td>empire mars</td>
<td>scrapped in 1969</td>
</tr>
<tr>
<th>5</th>
<td>wave emperor</td>
<td>a100</td>
<td>furness shipbuilding company</td>
<td>16 october 1944</td>
<td>none</td>
<td>scrapped in 1966</td>
</tr>
<tr>
<th>6</th>
<td>wave governor</td>
<td>a247</td>
<td>furness shipbuilding company</td>
<td>30 november 1944</td>
<td>none</td>
<td>scrapped in 1960</td>
</tr>
<tr>
<th>7</th>
<td>wave king</td>
<td>a182</td>
<td>harland and wolff</td>
<td>21 july 1944</td>
<td>none</td>
<td>scrapped in 1966</td>
</tr>
<tr>
<th>8</th>
<td>wave knight</td>
<td>a249</td>
<td>sir j. laing & sons ltd</td>
<td>22 october 1945</td>
<td>empire naseby</td>
<td>scrapped in 1964</td>
</tr>
<tr>
<th>9</th>
<td>wave laird</td>
<td>a119</td>
<td>sir j. laing & sons ltd</td>
<td>3 april 1946</td>
<td>empire dunbar</td>
<td>scrapped in 1970</td>
</tr>
<tr>
<th>10</th>
<td>wave liberator</td>
<td>a248</td>
<td>furness shipbuilding company</td>
<td>9 february 1944</td>
<td>empire milner</td>
<td>scrapped in 1959</td>
</tr>
<tr>
<th>11</th>
<td>wave master</td>
<td>a193</td>
<td>sir j. laing & sons ltd</td>
<td>20 may 1944</td>
<td>empire salisbury</td>
<td>scrapped in 1963</td>
</tr>
<tr>
<th>12</th>
<td>wave monarch</td>
<td>a264</td>
<td>harland and wolff</td>
<td>6 july 1944</td>
<td>none</td>
<td>sold as oil hulk in 1960</td>
</tr>
<tr>
<th>13</th>
<td>wave premier</td>
<td>a129</td>
<td>furness shipbuilding company</td>
<td>27 june 1946</td>
<td>none</td>
<td>scrapped in 1960</td>
</tr>
<tr>
<th>14</th>
<td>wave prince</td>
<td>a207</td>
<td>sir j. laing & sons ltd</td>
<td>27 july 1945</td>
<td>empire herald</td>
<td>scrapped in 1971</td>
</tr>
<tr>
<th>15</th>
<td>wave protector</td>
<td>a215</td>
<td>furness shipbuilding company</td>
<td>20 july 1944</td>
<td>empire protector</td>
<td>scrapped in 1963</td>
</tr>
<tr>
<th>16</th>
<td>wave regent</td>
<td>a210</td>
<td>furness shipbuilding company</td>
<td>29 march 1945</td>
<td>none</td>
<td>scrapped in 1960</td>
</tr>
<tr>
<th>17</th>
<td>wave ruler</td>
<td>a212</td>
<td>furness shipbuilding company</td>
<td>17 january 1946</td>
<td>empire evesham</td>
<td>scrapped in 1977</td>
</tr>
<tr>
<th>18</th>
<td>wave sovereign</td>
<td>a211</td>
<td>furness shipbuilding company</td>
<td>20 november 1945</td>
<td>none</td>
<td>scrapped in 1966</td>
</tr>
<tr>
<th>19</th>
<td>wave victor</td>
<td>a220</td>
<td>furness shipbuilding company</td>
<td>30 september 1943</td>
<td>empire bounty</td>
<td>chartered to air ministry in 1960</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "fate" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( fate ) where fate = 979 and launched = 37 <table_name> : table | | name | pennant | builder | launched | original name | fate |
|---:|:---------------|:----------|:-----------------------------|:------------------|:-----------------|:----------------------------------|
| 0 | wave baron | a242 | furness shipbuilding company | 19 february 1946 | empire flodden | scrapped in 1972 |
| 1 | wave chief | a265 | harland and wolff | 30 august 1946 | empire edgehill | scrapped in 1974 |
| 2 | wave commander | a244 | furness shipbuilding company | 21 april 1944 | empire paladin | scrapped in 1959 |
| 3 | wave conqueror | a245 | furness shipbuilding company | 27 november 1943 | empire law | scrapped in 1960 |
| 4 | wave duke | a246 | sir j. laing & sons ltd | 16 november 1944 | empire mars | scrapped in 1969 |
| 5 | wave emperor | a100 | furness shipbuilding company | 16 october 1944 | none | scrapped in 1966 |
| 6 | wave governor | a247 | furness shipbuilding company | 30 november 1944 | none | scrapped in 1960 |
| 7 | wave king | a182 | harland and wolff | 21 july 1944 | none | scrapped in 1966 |
| 8 | wave knight | a249 | sir j. laing & sons ltd | 22 october 1945 | empire naseby | scrapped in 1964 |
| 9 | wave laird | a119 | sir j. laing & sons ltd | 3 april 1946 | empire dunbar | scrapped in 1970 |
| 10 | wave liberator | a248 | furness shipbuilding company | 9 february 1944 | empire milner | scrapped in 1959 |
| 11 | wave master | a193 | sir j. laing & sons ltd | 20 may 1944 | empire salisbury | scrapped in 1963 |
| 12 | wave monarch | a264 | harland and wolff | 6 july 1944 | none | sold as oil hulk in 1960 |
| 13 | wave premier | a129 | furness shipbuilding company | 27 june 1946 | none | scrapped in 1960 |
| 14 | wave prince | a207 | sir j. laing & sons ltd | 27 july 1945 | empire herald | scrapped in 1971 |
| 15 | wave protector | a215 | furness shipbuilding company | 20 july 1944 | empire protector | scrapped in 1963 |
| 16 | wave regent | a210 | furness shipbuilding company | 29 march 1945 | none | scrapped in 1960 |
| 17 | wave ruler | a212 | furness shipbuilding company | 17 january 1946 | empire evesham | scrapped in 1977 |
| 18 | wave sovereign | a211 | furness shipbuilding company | 20 november 1945 | none | scrapped in 1966 |
| 19 | wave victor | a220 | furness shipbuilding company | 30 september 1943 | empire bounty | chartered to air ministry in 1960 | | | | count ( "fate" ) |
|---:|-------------------:|
| 0 | 0 | | [
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select count ( album details ) where peak positions jpn > 1973 col : title | album details | peak positions jpn | sales row 1 : the remixes | released: september 17, 1997 label: avex trax formats: cd | 2 | 640,000 row 2 : the remixes ii | released: november 18, 1998 label: avex trax formats: cd | 5 | 300,000 row 3 : super eurobeat presents euro every little thing | released: september 5, 2001 label: avex trax formats: cd | 3 | 200,000 row 4 : the remixes iii: mix rice plantation | released: february 27, 2002 label: avex trax formats: cd | 19 | 35,000 row 5 : cyber trance presents elt trance | released: february 27, 2002 label: avex trax formats: cd | 16 | 60,000 | col : count ( "album details" ) row 1 : 3 | select count ( album details ) where peak positions jpn > 1973 <table_name> : table \begin{tabular}{lllll}
\toprule
& title & album details & peak positions jpn & sales \\
\midrule
0 & the remixes & released: september 17, 1997 label: avex trax formats: cd & 2 & 640,000 \\
1 & the remixes ii & released: november 18, 1998 label: avex trax formats: cd & 5 & 300,000 \\
2 & super eurobeat presents euro every little thing & released: september 5, 2001 label: avex trax formats: cd & 3 & 200,000 \\
3 & the remixes iii: mix rice plantation & released: february 27, 2002 label: avex trax formats: cd & 19 & 35,000 \\
4 & cyber trance presents elt trance & released: february 27, 2002 label: avex trax formats: cd & 16 & 60,000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "album details" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( album details ) where peak positions jpn > 1973 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>title</th>
<th>album details</th>
<th>peak positions jpn</th>
<th>sales</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>the remixes</td>
<td>released: september 17, 1997 label: avex trax formats: cd</td>
<td>2</td>
<td>640,000</td>
</tr>
<tr>
<th>1</th>
<td>the remixes ii</td>
<td>released: november 18, 1998 label: avex trax formats: cd</td>
<td>5</td>
<td>300,000</td>
</tr>
<tr>
<th>2</th>
<td>super eurobeat presents euro every little thing</td>
<td>released: september 5, 2001 label: avex trax formats: cd</td>
<td>3</td>
<td>200,000</td>
</tr>
<tr>
<th>3</th>
<td>the remixes iii: mix rice plantation</td>
<td>released: february 27, 2002 label: avex trax formats: cd</td>
<td>19</td>
<td>35,000</td>
</tr>
<tr>
<th>4</th>
<td>cyber trance presents elt trance</td>
<td>released: february 27, 2002 label: avex trax formats: cd</td>
<td>16</td>
<td>60,000</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "album details" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( album details ) where peak positions jpn > 1973 <table_name> : table | | title | album details | peak positions jpn | sales |
|---:|:------------------------------------------------|:----------------------------------------------------------|---------------------:|:--------|
| 0 | the remixes | released: september 17, 1997 label: avex trax formats: cd | 2 | 640,000 |
| 1 | the remixes ii | released: november 18, 1998 label: avex trax formats: cd | 5 | 300,000 |
| 2 | super eurobeat presents euro every little thing | released: september 5, 2001 label: avex trax formats: cd | 3 | 200,000 |
| 3 | the remixes iii: mix rice plantation | released: february 27, 2002 label: avex trax formats: cd | 19 | 35,000 |
| 4 | cyber trance presents elt trance | released: february 27, 2002 label: avex trax formats: cd | 16 | 60,000 | | | | count ( "album details" ) |
|---:|----------------------------:|
| 0 | 3 | | [
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select total voters where party = 'minor parties' col : party | active voters | inactive voters | total voters | percentage row 1 : democratic | 3683 | 251 | 3934 | 36.93% row 2 : republican | 1322 | 78 | 1400 | 13.14% row 3 : unaffiliated | 4709 | 606 | 5315 | 49.90% row 4 : minor parties | 3 | 0 | 3 | 0.03% row 5 : total | 9717 | 935 | 10652 | 100% | col : total voters row 1 : 3 | select total voters where party = 'minor parties' <table_name> : table \begin{tabular}{llllll}
\toprule
& party & active voters & inactive voters & total voters & percentage \\
\midrule
0 & democratic & 3683 & 251 & 3934 & 36.93% \\
1 & republican & 1322 & 78 & 1400 & 13.14% \\
2 & unaffiliated & 4709 & 606 & 5315 & 49.90% \\
3 & minor parties & 3 & 0 & 3 & 0.03% \\
4 & total & 9717 & 935 & 10652 & 100% \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& total voters \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select total voters where party = 'minor parties' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
<th>active voters</th>
<th>inactive voters</th>
<th>total voters</th>
<th>percentage</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>democratic</td>
<td>3683</td>
<td>251</td>
<td>3934</td>
<td>36.93%</td>
</tr>
<tr>
<th>1</th>
<td>republican</td>
<td>1322</td>
<td>78</td>
<td>1400</td>
<td>13.14%</td>
</tr>
<tr>
<th>2</th>
<td>unaffiliated</td>
<td>4709</td>
<td>606</td>
<td>5315</td>
<td>49.90%</td>
</tr>
<tr>
<th>3</th>
<td>minor parties</td>
<td>3</td>
<td>0</td>
<td>3</td>
<td>0.03%</td>
</tr>
<tr>
<th>4</th>
<td>total</td>
<td>9717</td>
<td>935</td>
<td>10652</td>
<td>100%</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>total voters</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select total voters where party = 'minor parties' <table_name> : table | | party | active voters | inactive voters | total voters | percentage |
|---:|:--------------|----------------:|------------------:|---------------:|:-------------|
| 0 | democratic | 3683 | 251 | 3934 | 36.93% |
| 1 | republican | 1322 | 78 | 1400 | 13.14% |
| 2 | unaffiliated | 4709 | 606 | 5315 | 49.90% |
| 3 | minor parties | 3 | 0 | 3 | 0.03% |
| 4 | total | 9717 | 935 | 10652 | 100% | | | | total voters |
|---:|---------------:|
| 0 | 3 | | [
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select total where npc = 'russia (rus)' col : rank | npc | gold | silver | bronze | total row 1 : 1 | china (chn) | 95 | 71 | 65 | 231 row 2 : 2 | russia (rus) | 36 | 38 | 28 | 102 row 3 : 3 | great britain (gbr) | 34 | 43 | 43 | 120 row 4 : 4 | ukraine (ukr) | 32 | 24 | 28 | 84 row 5 : 5 | australia (aus) | 32 | 23 | 30 | 85 row 6 : 6 | united states (usa) | 31 | 29 | 38 | 98 row 7 : 7 | brazil (bra) | 21 | 14 | 8 | 43 row 8 : 8 | germany (ger) | 18 | 26 | 22 | 66 row 9 : 9 | poland (pol) | 14 | 13 | 9 | 36 row 10 : 10 | netherlands (ned) | 10 | 10 | 19 | 39 row 11 : total (75 npcs) | total (75 npcs) | 503 | 503 | 516 | 1522 | col : total row 1 : 102 | select total where npc = 'russia (rus)' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & npc & gold & silver & bronze & total \\
\midrule
0 & 1 & china (chn) & 95 & 71 & 65 & 231 \\
1 & 2 & russia (rus) & 36 & 38 & 28 & 102 \\
2 & 3 & great britain (gbr) & 34 & 43 & 43 & 120 \\
3 & 4 & ukraine (ukr) & 32 & 24 & 28 & 84 \\
4 & 5 & australia (aus) & 32 & 23 & 30 & 85 \\
5 & 6 & united states (usa) & 31 & 29 & 38 & 98 \\
6 & 7 & brazil (bra) & 21 & 14 & 8 & 43 \\
7 & 8 & germany (ger) & 18 & 26 & 22 & 66 \\
8 & 9 & poland (pol) & 14 & 13 & 9 & 36 \\
9 & 10 & netherlands (ned) & 10 & 10 & 19 & 39 \\
10 & total (75 npcs) & total (75 npcs) & 503 & 503 & 516 & 1522 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& total \\
\midrule
0 & 102 \\
\bottomrule
\end{tabular}
| select total where npc = 'russia (rus)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>npc</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>china (chn)</td>
<td>95</td>
<td>71</td>
<td>65</td>
<td>231</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>russia (rus)</td>
<td>36</td>
<td>38</td>
<td>28</td>
<td>102</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>great britain (gbr)</td>
<td>34</td>
<td>43</td>
<td>43</td>
<td>120</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>ukraine (ukr)</td>
<td>32</td>
<td>24</td>
<td>28</td>
<td>84</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>australia (aus)</td>
<td>32</td>
<td>23</td>
<td>30</td>
<td>85</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>united states (usa)</td>
<td>31</td>
<td>29</td>
<td>38</td>
<td>98</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>brazil (bra)</td>
<td>21</td>
<td>14</td>
<td>8</td>
<td>43</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>germany (ger)</td>
<td>18</td>
<td>26</td>
<td>22</td>
<td>66</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>poland (pol)</td>
<td>14</td>
<td>13</td>
<td>9</td>
<td>36</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>netherlands (ned)</td>
<td>10</td>
<td>10</td>
<td>19</td>
<td>39</td>
</tr>
<tr>
<th>10</th>
<td>total (75 npcs)</td>
<td>total (75 npcs)</td>
<td>503</td>
<td>503</td>
<td>516</td>
<td>1522</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>102</td>
</tr>
</tbody>
</table> | select total where npc = 'russia (rus)' <table_name> : table | | rank | npc | gold | silver | bronze | total |
|---:|:----------------|:--------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | china (chn) | 95 | 71 | 65 | 231 |
| 1 | 2 | russia (rus) | 36 | 38 | 28 | 102 |
| 2 | 3 | great britain (gbr) | 34 | 43 | 43 | 120 |
| 3 | 4 | ukraine (ukr) | 32 | 24 | 28 | 84 |
| 4 | 5 | australia (aus) | 32 | 23 | 30 | 85 |
| 5 | 6 | united states (usa) | 31 | 29 | 38 | 98 |
| 6 | 7 | brazil (bra) | 21 | 14 | 8 | 43 |
| 7 | 8 | germany (ger) | 18 | 26 | 22 | 66 |
| 8 | 9 | poland (pol) | 14 | 13 | 9 | 36 |
| 9 | 10 | netherlands (ned) | 10 | 10 | 19 | 39 |
| 10 | total (75 npcs) | total (75 npcs) | 503 | 503 | 516 | 1522 | | | | total |
|---:|--------:|
| 0 | 102 | | [
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select ships where note = 'chartered' order by displacement desc limit 1 col : class | type | ships | displacement | note row 1 : rari class | tug supply vessel | a635 revi | 1,450 tonnes | none row 2 : malabar class | ocean going tug | a664 malabar a669 tenace | 1,440 tonnes | ice-breaking capabilities to 2 meters level ice row 3 : ut507 class | salvage tug | abeille flandre abeille languedoc | 1,500 tonnes | chartered row 4 : ut515 class | salvage tug | abeille bourbon abeille liberte | 4,000 tonnes | chartered row 5 : ut710 class | support, assistance, pollution control vessel | argonaute jason | 2,100 tonnes | chartered, configured to accommodate nato submarine rescue system row 6 : ut711 class | support, assistance, pollution control vessel | alcyon ailette | 2,000 tonnes | chartered row 7 : none | training ships | vn partisan | 2,250 tonnes | chartered row 8 : none | training ships | vn rebel | none | chartered | col : ships row 1 : vn rebel | select ships where note = 'chartered' order by displacement desc limit 1 <table_name> : table \begin{tabular}{llllll}
\toprule
& class & type & ships & displacement & note \\
\midrule
0 & rari class & tug supply vessel & a635 revi & 1,450 tonnes & none \\
1 & malabar class & ocean going tug & a664 malabar a669 tenace & 1,440 tonnes & ice-breaking capabilities to 2 meters level ice \\
2 & ut507 class & salvage tug & abeille flandre abeille languedoc & 1,500 tonnes & chartered \\
3 & ut515 class & salvage tug & abeille bourbon abeille liberte & 4,000 tonnes & chartered \\
4 & ut710 class & support, assistance, pollution control vessel & argonaute jason & 2,100 tonnes & chartered, configured to accommodate nato submarine rescue system \\
5 & ut711 class & support, assistance, pollution control vessel & alcyon ailette & 2,000 tonnes & chartered \\
6 & none & training ships & vn partisan & 2,250 tonnes & chartered \\
7 & none & training ships & vn rebel & none & chartered \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& ships \\
\midrule
0 & vn rebel \\
\bottomrule
\end{tabular}
| select ships where note = 'chartered' order by displacement desc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>class</th>
<th>type</th>
<th>ships</th>
<th>displacement</th>
<th>note</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>rari class</td>
<td>tug supply vessel</td>
<td>a635 revi</td>
<td>1,450 tonnes</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>malabar class</td>
<td>ocean going tug</td>
<td>a664 malabar a669 tenace</td>
<td>1,440 tonnes</td>
<td>ice-breaking capabilities to 2 meters level ice</td>
</tr>
<tr>
<th>2</th>
<td>ut507 class</td>
<td>salvage tug</td>
<td>abeille flandre abeille languedoc</td>
<td>1,500 tonnes</td>
<td>chartered</td>
</tr>
<tr>
<th>3</th>
<td>ut515 class</td>
<td>salvage tug</td>
<td>abeille bourbon abeille liberte</td>
<td>4,000 tonnes</td>
<td>chartered</td>
</tr>
<tr>
<th>4</th>
<td>ut710 class</td>
<td>support, assistance, pollution control vessel</td>
<td>argonaute jason</td>
<td>2,100 tonnes</td>
<td>chartered, configured to accommodate nato submarine rescue system</td>
</tr>
<tr>
<th>5</th>
<td>ut711 class</td>
<td>support, assistance, pollution control vessel</td>
<td>alcyon ailette</td>
<td>2,000 tonnes</td>
<td>chartered</td>
</tr>
<tr>
<th>6</th>
<td>none</td>
<td>training ships</td>
<td>vn partisan</td>
<td>2,250 tonnes</td>
<td>chartered</td>
</tr>
<tr>
<th>7</th>
<td>none</td>
<td>training ships</td>
<td>vn rebel</td>
<td>none</td>
<td>chartered</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>ships</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>vn rebel</td>
</tr>
</tbody>
</table> | select ships where note = 'chartered' order by displacement desc limit 1 <table_name> : table | | class | type | ships | displacement | note |
|---:|:--------------|:----------------------------------------------|:----------------------------------|:---------------|:------------------------------------------------------------------|
| 0 | rari class | tug supply vessel | a635 revi | 1,450 tonnes | none |
| 1 | malabar class | ocean going tug | a664 malabar a669 tenace | 1,440 tonnes | ice-breaking capabilities to 2 meters level ice |
| 2 | ut507 class | salvage tug | abeille flandre abeille languedoc | 1,500 tonnes | chartered |
| 3 | ut515 class | salvage tug | abeille bourbon abeille liberte | 4,000 tonnes | chartered |
| 4 | ut710 class | support, assistance, pollution control vessel | argonaute jason | 2,100 tonnes | chartered, configured to accommodate nato submarine rescue system |
| 5 | ut711 class | support, assistance, pollution control vessel | alcyon ailette | 2,000 tonnes | chartered |
| 6 | none | training ships | vn partisan | 2,250 tonnes | chartered |
| 7 | none | training ships | vn rebel | none | chartered | | | | ships |
|---:|:---------|
| 0 | vn rebel | | [
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select year where film = 'arya 2' col : year | film | role | language | notes row 1 : 2004 | kyun! ho gaya na | diya's sister | hindi | none row 2 : 2007 | lakshmi kalyanam | lakshmi | telugu | none row 3 : 2007 | chandamama | mahalakshmi | telugu | none row 4 : 2008 | pourudu | samyukhta | telugu | none row 5 : 2008 | pazhani | deepti | tamil | none row 6 : 2008 | aatadista | sunnanda | telugu | none row 7 : 2008 | saroja | pooja | tamil | cameo appearance row 8 : 2008 | bommalattam | anitha | tamil | none row 9 : 2009 | modhi vilayadu | easwari lakshmiram | tamil | none row 10 : 2009 | magadheera | yuvarani mithravindha devi indira (indu) | telugu | dual role nominated- filmfare award for best actress - telugu row 11 : 2009 | ganesh just ganesh | divya | telugu | none row 12 : 2009 | arya 2 | geethanjali | telugu | none row 13 : 2010 | om shanti | meghana | telugu | none row 14 : 2010 | darling | nandini | telugu | nominated- filmfare award for best actress - telugu row 15 : 2010 | naan mahaan alla | priya sudharsan | tamil | none row 16 : 2010 | brindaavanam | bhoomi | telugu | cinemaa award for best actress (telugu) row 17 : 2011 | mr. perfect | priya | telugu | nominated- filmfare award for best actress - telugu row 18 : 2011 | veera | chitti | telugu | none row 19 : 2011 | singham | kavya bhosle | hindi | nominated- filmfare award for best female debut row 20 : 2011 | dhada | rhea | telugu | none row 21 : 2012 | businessman | chitra | telugu | none row 22 : 2012 | maattrraan | anjali | tamil | none row 23 : 2012 | thuppakki | nisha | tamil | cinemaa award for best actress (tamil) row 24 : 2012 | sarocharu | sandhya | telugu | none row 25 : 2013 | naayak | madhu | telugu | none row 26 : 2013 | special 26 | priya chauhan | hindi | none row 27 : 2013 | baadshah | janaki | telugu | none row 28 : 2013 | all in all azhagu raja | chitra devi priya | tamil | none row 29 : 2014 | jilla | shanthi | tamil | none row 30 : 2014 | yevadu | deepthi | telugu | special appearance row 31 : 2014 | govindudu andarivadele | none | telugu | filming row 32 : 2014 | 'untitled balaji mohan project | none | tamil | pre-production | col : year row 1 : 2009 | select year where film = 'arya 2' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & film & role & language & notes \\
\midrule
0 & 2004 & kyun! ho gaya na & diya's sister & hindi & none \\
1 & 2007 & lakshmi kalyanam & lakshmi & telugu & none \\
2 & 2007 & chandamama & mahalakshmi & telugu & none \\
3 & 2008 & pourudu & samyukhta & telugu & none \\
4 & 2008 & pazhani & deepti & tamil & none \\
5 & 2008 & aatadista & sunnanda & telugu & none \\
6 & 2008 & saroja & pooja & tamil & cameo appearance \\
7 & 2008 & bommalattam & anitha & tamil & none \\
8 & 2009 & modhi vilayadu & easwari lakshmiram & tamil & none \\
9 & 2009 & magadheera & yuvarani mithravindha devi indira (indu) & telugu & dual role nominated- filmfare award for best actress - telugu \\
10 & 2009 & ganesh just ganesh & divya & telugu & none \\
11 & 2009 & arya 2 & geethanjali & telugu & none \\
12 & 2010 & om shanti & meghana & telugu & none \\
13 & 2010 & darling & nandini & telugu & nominated- filmfare award for best actress - telugu \\
14 & 2010 & naan mahaan alla & priya sudharsan & tamil & none \\
15 & 2010 & brindaavanam & bhoomi & telugu & cinemaa award for best actress (telugu) \\
16 & 2011 & mr. perfect & priya & telugu & nominated- filmfare award for best actress - telugu \\
17 & 2011 & veera & chitti & telugu & none \\
18 & 2011 & singham & kavya bhosle & hindi & nominated- filmfare award for best female debut \\
19 & 2011 & dhada & rhea & telugu & none \\
20 & 2012 & businessman & chitra & telugu & none \\
21 & 2012 & maattrraan & anjali & tamil & none \\
22 & 2012 & thuppakki & nisha & tamil & cinemaa award for best actress (tamil) \\
23 & 2012 & sarocharu & sandhya & telugu & none \\
24 & 2013 & naayak & madhu & telugu & none \\
25 & 2013 & special 26 & priya chauhan & hindi & none \\
26 & 2013 & baadshah & janaki & telugu & none \\
27 & 2013 & all in all azhagu raja & chitra devi priya & tamil & none \\
28 & 2014 & jilla & shanthi & tamil & none \\
29 & 2014 & yevadu & deepthi & telugu & special appearance \\
30 & 2014 & govindudu andarivadele & none & telugu & filming \\
31 & 2014 & 'untitled balaji mohan project & none & tamil & pre-production \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 2009 \\
\bottomrule
\end{tabular}
| select year where film = 'arya 2' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>film</th>
<th>role</th>
<th>language</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004</td>
<td>kyun! ho gaya na</td>
<td>diya's sister</td>
<td>hindi</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2007</td>
<td>lakshmi kalyanam</td>
<td>lakshmi</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2007</td>
<td>chandamama</td>
<td>mahalakshmi</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2008</td>
<td>pourudu</td>
<td>samyukhta</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2008</td>
<td>pazhani</td>
<td>deepti</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>aatadista</td>
<td>sunnanda</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2008</td>
<td>saroja</td>
<td>pooja</td>
<td>tamil</td>
<td>cameo appearance</td>
</tr>
<tr>
<th>7</th>
<td>2008</td>
<td>bommalattam</td>
<td>anitha</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2009</td>
<td>modhi vilayadu</td>
<td>easwari lakshmiram</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>2009</td>
<td>magadheera</td>
<td>yuvarani mithravindha devi indira (indu)</td>
<td>telugu</td>
<td>dual role nominated- filmfare award for best actress - telugu</td>
</tr>
<tr>
<th>10</th>
<td>2009</td>
<td>ganesh just ganesh</td>
<td>divya</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>2009</td>
<td>arya 2</td>
<td>geethanjali</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>2010</td>
<td>om shanti</td>
<td>meghana</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>2010</td>
<td>darling</td>
<td>nandini</td>
<td>telugu</td>
<td>nominated- filmfare award for best actress - telugu</td>
</tr>
<tr>
<th>14</th>
<td>2010</td>
<td>naan mahaan alla</td>
<td>priya sudharsan</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>2010</td>
<td>brindaavanam</td>
<td>bhoomi</td>
<td>telugu</td>
<td>cinemaa award for best actress (telugu)</td>
</tr>
<tr>
<th>16</th>
<td>2011</td>
<td>mr. perfect</td>
<td>priya</td>
<td>telugu</td>
<td>nominated- filmfare award for best actress - telugu</td>
</tr>
<tr>
<th>17</th>
<td>2011</td>
<td>veera</td>
<td>chitti</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>2011</td>
<td>singham</td>
<td>kavya bhosle</td>
<td>hindi</td>
<td>nominated- filmfare award for best female debut</td>
</tr>
<tr>
<th>19</th>
<td>2011</td>
<td>dhada</td>
<td>rhea</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>2012</td>
<td>businessman</td>
<td>chitra</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>2012</td>
<td>maattrraan</td>
<td>anjali</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>2012</td>
<td>thuppakki</td>
<td>nisha</td>
<td>tamil</td>
<td>cinemaa award for best actress (tamil)</td>
</tr>
<tr>
<th>23</th>
<td>2012</td>
<td>sarocharu</td>
<td>sandhya</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>2013</td>
<td>naayak</td>
<td>madhu</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>2013</td>
<td>special 26</td>
<td>priya chauhan</td>
<td>hindi</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>2013</td>
<td>baadshah</td>
<td>janaki</td>
<td>telugu</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>2013</td>
<td>all in all azhagu raja</td>
<td>chitra devi priya</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>2014</td>
<td>jilla</td>
<td>shanthi</td>
<td>tamil</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>2014</td>
<td>yevadu</td>
<td>deepthi</td>
<td>telugu</td>
<td>special appearance</td>
</tr>
<tr>
<th>30</th>
<td>2014</td>
<td>govindudu andarivadele</td>
<td>none</td>
<td>telugu</td>
<td>filming</td>
</tr>
<tr>
<th>31</th>
<td>2014</td>
<td>'untitled balaji mohan project</td>
<td>none</td>
<td>tamil</td>
<td>pre-production</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2009</td>
</tr>
</tbody>
</table> | select year where film = 'arya 2' <table_name> : table | | year | film | role | language | notes |
|---:|-------:|:-------------------------------|:-----------------------------------------|:-----------|:--------------------------------------------------------------|
| 0 | 2004 | kyun! ho gaya na | diya's sister | hindi | none |
| 1 | 2007 | lakshmi kalyanam | lakshmi | telugu | none |
| 2 | 2007 | chandamama | mahalakshmi | telugu | none |
| 3 | 2008 | pourudu | samyukhta | telugu | none |
| 4 | 2008 | pazhani | deepti | tamil | none |
| 5 | 2008 | aatadista | sunnanda | telugu | none |
| 6 | 2008 | saroja | pooja | tamil | cameo appearance |
| 7 | 2008 | bommalattam | anitha | tamil | none |
| 8 | 2009 | modhi vilayadu | easwari lakshmiram | tamil | none |
| 9 | 2009 | magadheera | yuvarani mithravindha devi indira (indu) | telugu | dual role nominated- filmfare award for best actress - telugu |
| 10 | 2009 | ganesh just ganesh | divya | telugu | none |
| 11 | 2009 | arya 2 | geethanjali | telugu | none |
| 12 | 2010 | om shanti | meghana | telugu | none |
| 13 | 2010 | darling | nandini | telugu | nominated- filmfare award for best actress - telugu |
| 14 | 2010 | naan mahaan alla | priya sudharsan | tamil | none |
| 15 | 2010 | brindaavanam | bhoomi | telugu | cinemaa award for best actress (telugu) |
| 16 | 2011 | mr. perfect | priya | telugu | nominated- filmfare award for best actress - telugu |
| 17 | 2011 | veera | chitti | telugu | none |
| 18 | 2011 | singham | kavya bhosle | hindi | nominated- filmfare award for best female debut |
| 19 | 2011 | dhada | rhea | telugu | none |
| 20 | 2012 | businessman | chitra | telugu | none |
| 21 | 2012 | maattrraan | anjali | tamil | none |
| 22 | 2012 | thuppakki | nisha | tamil | cinemaa award for best actress (tamil) |
| 23 | 2012 | sarocharu | sandhya | telugu | none |
| 24 | 2013 | naayak | madhu | telugu | none |
| 25 | 2013 | special 26 | priya chauhan | hindi | none |
| 26 | 2013 | baadshah | janaki | telugu | none |
| 27 | 2013 | all in all azhagu raja | chitra devi priya | tamil | none |
| 28 | 2014 | jilla | shanthi | tamil | none |
| 29 | 2014 | yevadu | deepthi | telugu | special appearance |
| 30 | 2014 | govindudu andarivadele | none | telugu | filming |
| 31 | 2014 | 'untitled balaji mohan project | none | tamil | pre-production | | | | year |
|---:|-------:|
| 0 | 2009 | | [
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select count ( * ) where match = 0 and match = 0 col : match | date | venue | opponents | score row 1 : gl-b-1 | 2008 | | | row 2 : gl-b-2 | 2008 | | | row 3 : gl-b-3 | 2008 | | | row 4 : gl-b-4 | 2008 | | | row 5 : gl-b-5 | 2008 | | | row 6 : gl-b-6 | 2008 | | | row 7 : quarterfinals-1 | 2008 | | | row 8 : quarterfinals-2 | 2008 | | | | col : count ( "*" ) row 1 : 0 | select count ( * ) where match = 0 and match = 0 <table_name> : table \begin{tabular}{llllll}
\toprule
& match & date & venue & opponents & score \\
\midrule
0 & gl-b-1 & 2008 & & & \\
1 & gl-b-2 & 2008 & & & \\
2 & gl-b-3 & 2008 & & & \\
3 & gl-b-4 & 2008 & & & \\
4 & gl-b-5 & 2008 & & & \\
5 & gl-b-6 & 2008 & & & \\
6 & quarterfinals-1 & 2008 & & & \\
7 & quarterfinals-2 & 2008 & & | & NaN \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where match = 0 and match = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>match</th>
<th>date</th>
<th>venue</th>
<th>opponents</th>
<th>score</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>gl-b-1</td>
<td>2008</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>1</th>
<td>gl-b-2</td>
<td>2008</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>2</th>
<td>gl-b-3</td>
<td>2008</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>3</th>
<td>gl-b-4</td>
<td>2008</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>4</th>
<td>gl-b-5</td>
<td>2008</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>5</th>
<td>gl-b-6</td>
<td>2008</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>6</th>
<td>quarterfinals-1</td>
<td>2008</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>quarterfinals-2</td>
<td>2008</td>
<td></td>
<td>|</td>
<td>None</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where match = 0 and match = 0 <table_name> : table | | match | date | venue | opponents | score |
|---:|:----------------|-------:|:--------|:------------|:--------|
| 0 | gl-b-1 | 2008 | | | |
| 1 | gl-b-2 | 2008 | | | |
| 2 | gl-b-3 | 2008 | | | |
| 3 | gl-b-4 | 2008 | | | |
| 4 | gl-b-5 | 2008 | | | |
| 5 | gl-b-6 | 2008 | | | |
| 6 | quarterfinals-1 | 2008 | | | |
| 7 | quarterfinals-2 | 2008 | | | | | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select country where rider = 'chris hoy' col : date | competition | location | country | event | placing | rider | nationality row 1 : 2008-10-31 00:00:00 | 2008-09 world cup | manchester | united kingdom | sprint | 1 | victoria pendleton | gbr row 2 : 2008-10-31 00:00:00 | 2008-09 world cup | manchester | united kingdom | keirin | 2 | jason kenny | gbr row 3 : 2008-11-01 00:00:00 | 2008-09 world cup | manchester | united kingdom | sprint | 1 | jason kenny | gbr row 4 : 2008-11-01 00:00:00 | 2008-09 world cup | manchester | united kingdom | 500 m time trial | 1 | victoria pendleton | gbr row 5 : 2008-11-02 00:00:00 | 2008-09 world cup | manchester | united kingdom | team sprint | 1 | ross edgar | gbr row 6 : 2008-11-02 00:00:00 | 2008-09 world cup | manchester | united kingdom | team sprint | 1 | jason kenny | gbr row 7 : 2008-11-02 00:00:00 | 2008-09 world cup | manchester | united kingdom | team sprint | 1 | jamie staff | gbr row 8 : 2008-11-02 00:00:00 | 2008-09 world cup | manchester | united kingdom | keirin | 1 | victoria pendleton | gbr row 9 : 2008-11-02 00:00:00 | 5th international keirin event | manchester | united kingdom | international keirin | 2 | ross edgar | gbr row 10 : 2009-02-13 00:00:00 | 2008-09 world cup | copenhagen | denmark | team sprint | 1 | chris hoy | gbr row 11 : 2009-02-13 00:00:00 | 2008-09 world cup | copenhagen | denmark | team sprint | 1 | jason kenny | gbr row 12 : 2009-02-13 00:00:00 | 2008-09 world cup | copenhagen | denmark | team sprint | 1 | jamie staff | gbr row 13 : 2009-02-13 00:00:00 | 2008-09 world cup | copenhagen | denmark | sprint | 1 | victoria pendleton | gbr row 14 : 2009-10-30 00:00:00 | 2009-10 world cup | manchester | united kingdom | keirin | 1 | chris hoy | gbr row 15 : 2009-10-30 00:00:00 | 2009-10 world cup | manchester | united kingdom | sprint | 1 | victoria pendleton | gbr row 16 : 2009-10-30 00:00:00 | 2009-10 world cup | manchester | united kingdom | sprint | 1 | chris hoy | gbr row 17 : 2009-10-30 00:00:00 | 2009-10 world cup | manchester | united kingdom | 500 m time trial | 2 | victoria pendleton | gbr row 18 : 2009-11-01 00:00:00 | 2009-10 world cup | manchester | united kingdom | team sprint | 1 | ross edgar | gbr row 19 : 2009-11-01 00:00:00 | 2009-10 world cup | manchester | united kingdom | team sprint | 1 | chris hoy | gbr row 20 : 2009-11-01 00:00:00 | 2009-10 world cup | manchester | united kingdom | team sprint | 1 | jamie staff | gbr | col : count ( "country" ) row 1 : 4 | select country where rider = 'chris hoy' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& date & competition & location & country & event & placing & rider & nationality \\
\midrule
0 & 2008-10-31 00:00:00 & 2008-09 world cup & manchester & united kingdom & sprint & 1 & victoria pendleton & gbr \\
1 & 2008-10-31 00:00:00 & 2008-09 world cup & manchester & united kingdom & keirin & 2 & jason kenny & gbr \\
2 & 2008-11-01 00:00:00 & 2008-09 world cup & manchester & united kingdom & sprint & 1 & jason kenny & gbr \\
3 & 2008-11-01 00:00:00 & 2008-09 world cup & manchester & united kingdom & 500 m time trial & 1 & victoria pendleton & gbr \\
4 & 2008-11-02 00:00:00 & 2008-09 world cup & manchester & united kingdom & team sprint & 1 & ross edgar & gbr \\
5 & 2008-11-02 00:00:00 & 2008-09 world cup & manchester & united kingdom & team sprint & 1 & jason kenny & gbr \\
6 & 2008-11-02 00:00:00 & 2008-09 world cup & manchester & united kingdom & team sprint & 1 & jamie staff & gbr \\
7 & 2008-11-02 00:00:00 & 2008-09 world cup & manchester & united kingdom & keirin & 1 & victoria pendleton & gbr \\
8 & 2008-11-02 00:00:00 & 5th international keirin event & manchester & united kingdom & international keirin & 2 & ross edgar & gbr \\
9 & 2009-02-13 00:00:00 & 2008-09 world cup & copenhagen & denmark & team sprint & 1 & chris hoy & gbr \\
10 & 2009-02-13 00:00:00 & 2008-09 world cup & copenhagen & denmark & team sprint & 1 & jason kenny & gbr \\
11 & 2009-02-13 00:00:00 & 2008-09 world cup & copenhagen & denmark & team sprint & 1 & jamie staff & gbr \\
12 & 2009-02-13 00:00:00 & 2008-09 world cup & copenhagen & denmark & sprint & 1 & victoria pendleton & gbr \\
13 & 2009-10-30 00:00:00 & 2009-10 world cup & manchester & united kingdom & keirin & 1 & chris hoy & gbr \\
14 & 2009-10-30 00:00:00 & 2009-10 world cup & manchester & united kingdom & sprint & 1 & victoria pendleton & gbr \\
15 & 2009-10-30 00:00:00 & 2009-10 world cup & manchester & united kingdom & sprint & 1 & chris hoy & gbr \\
16 & 2009-10-30 00:00:00 & 2009-10 world cup & manchester & united kingdom & 500 m time trial & 2 & victoria pendleton & gbr \\
17 & 2009-11-01 00:00:00 & 2009-10 world cup & manchester & united kingdom & team sprint & 1 & ross edgar & gbr \\
18 & 2009-11-01 00:00:00 & 2009-10 world cup & manchester & united kingdom & team sprint & 1 & chris hoy & gbr \\
19 & 2009-11-01 00:00:00 & 2009-10 world cup & manchester & united kingdom & team sprint & 1 & jamie staff & gbr \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "country" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select country where rider = 'chris hoy' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>competition</th>
<th>location</th>
<th>country</th>
<th>event</th>
<th>placing</th>
<th>rider</th>
<th>nationality</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2008-10-31 00:00:00</td>
<td>2008-09 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>sprint</td>
<td>1</td>
<td>victoria pendleton</td>
<td>gbr</td>
</tr>
<tr>
<th>1</th>
<td>2008-10-31 00:00:00</td>
<td>2008-09 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>keirin</td>
<td>2</td>
<td>jason kenny</td>
<td>gbr</td>
</tr>
<tr>
<th>2</th>
<td>2008-11-01 00:00:00</td>
<td>2008-09 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>sprint</td>
<td>1</td>
<td>jason kenny</td>
<td>gbr</td>
</tr>
<tr>
<th>3</th>
<td>2008-11-01 00:00:00</td>
<td>2008-09 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>500 m time trial</td>
<td>1</td>
<td>victoria pendleton</td>
<td>gbr</td>
</tr>
<tr>
<th>4</th>
<td>2008-11-02 00:00:00</td>
<td>2008-09 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>team sprint</td>
<td>1</td>
<td>ross edgar</td>
<td>gbr</td>
</tr>
<tr>
<th>5</th>
<td>2008-11-02 00:00:00</td>
<td>2008-09 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>team sprint</td>
<td>1</td>
<td>jason kenny</td>
<td>gbr</td>
</tr>
<tr>
<th>6</th>
<td>2008-11-02 00:00:00</td>
<td>2008-09 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>team sprint</td>
<td>1</td>
<td>jamie staff</td>
<td>gbr</td>
</tr>
<tr>
<th>7</th>
<td>2008-11-02 00:00:00</td>
<td>2008-09 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>keirin</td>
<td>1</td>
<td>victoria pendleton</td>
<td>gbr</td>
</tr>
<tr>
<th>8</th>
<td>2008-11-02 00:00:00</td>
<td>5th international keirin event</td>
<td>manchester</td>
<td>united kingdom</td>
<td>international keirin</td>
<td>2</td>
<td>ross edgar</td>
<td>gbr</td>
</tr>
<tr>
<th>9</th>
<td>2009-02-13 00:00:00</td>
<td>2008-09 world cup</td>
<td>copenhagen</td>
<td>denmark</td>
<td>team sprint</td>
<td>1</td>
<td>chris hoy</td>
<td>gbr</td>
</tr>
<tr>
<th>10</th>
<td>2009-02-13 00:00:00</td>
<td>2008-09 world cup</td>
<td>copenhagen</td>
<td>denmark</td>
<td>team sprint</td>
<td>1</td>
<td>jason kenny</td>
<td>gbr</td>
</tr>
<tr>
<th>11</th>
<td>2009-02-13 00:00:00</td>
<td>2008-09 world cup</td>
<td>copenhagen</td>
<td>denmark</td>
<td>team sprint</td>
<td>1</td>
<td>jamie staff</td>
<td>gbr</td>
</tr>
<tr>
<th>12</th>
<td>2009-02-13 00:00:00</td>
<td>2008-09 world cup</td>
<td>copenhagen</td>
<td>denmark</td>
<td>sprint</td>
<td>1</td>
<td>victoria pendleton</td>
<td>gbr</td>
</tr>
<tr>
<th>13</th>
<td>2009-10-30 00:00:00</td>
<td>2009-10 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>keirin</td>
<td>1</td>
<td>chris hoy</td>
<td>gbr</td>
</tr>
<tr>
<th>14</th>
<td>2009-10-30 00:00:00</td>
<td>2009-10 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>sprint</td>
<td>1</td>
<td>victoria pendleton</td>
<td>gbr</td>
</tr>
<tr>
<th>15</th>
<td>2009-10-30 00:00:00</td>
<td>2009-10 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>sprint</td>
<td>1</td>
<td>chris hoy</td>
<td>gbr</td>
</tr>
<tr>
<th>16</th>
<td>2009-10-30 00:00:00</td>
<td>2009-10 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>500 m time trial</td>
<td>2</td>
<td>victoria pendleton</td>
<td>gbr</td>
</tr>
<tr>
<th>17</th>
<td>2009-11-01 00:00:00</td>
<td>2009-10 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>team sprint</td>
<td>1</td>
<td>ross edgar</td>
<td>gbr</td>
</tr>
<tr>
<th>18</th>
<td>2009-11-01 00:00:00</td>
<td>2009-10 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>team sprint</td>
<td>1</td>
<td>chris hoy</td>
<td>gbr</td>
</tr>
<tr>
<th>19</th>
<td>2009-11-01 00:00:00</td>
<td>2009-10 world cup</td>
<td>manchester</td>
<td>united kingdom</td>
<td>team sprint</td>
<td>1</td>
<td>jamie staff</td>
<td>gbr</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "country" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select country where rider = 'chris hoy' <table_name> : table | | date | competition | location | country | event | placing | rider | nationality |
|---:|:--------------------|:-------------------------------|:-----------|:---------------|:---------------------|----------:|:-------------------|:--------------|
| 0 | 2008-10-31 00:00:00 | 2008-09 world cup | manchester | united kingdom | sprint | 1 | victoria pendleton | gbr |
| 1 | 2008-10-31 00:00:00 | 2008-09 world cup | manchester | united kingdom | keirin | 2 | jason kenny | gbr |
| 2 | 2008-11-01 00:00:00 | 2008-09 world cup | manchester | united kingdom | sprint | 1 | jason kenny | gbr |
| 3 | 2008-11-01 00:00:00 | 2008-09 world cup | manchester | united kingdom | 500 m time trial | 1 | victoria pendleton | gbr |
| 4 | 2008-11-02 00:00:00 | 2008-09 world cup | manchester | united kingdom | team sprint | 1 | ross edgar | gbr |
| 5 | 2008-11-02 00:00:00 | 2008-09 world cup | manchester | united kingdom | team sprint | 1 | jason kenny | gbr |
| 6 | 2008-11-02 00:00:00 | 2008-09 world cup | manchester | united kingdom | team sprint | 1 | jamie staff | gbr |
| 7 | 2008-11-02 00:00:00 | 2008-09 world cup | manchester | united kingdom | keirin | 1 | victoria pendleton | gbr |
| 8 | 2008-11-02 00:00:00 | 5th international keirin event | manchester | united kingdom | international keirin | 2 | ross edgar | gbr |
| 9 | 2009-02-13 00:00:00 | 2008-09 world cup | copenhagen | denmark | team sprint | 1 | chris hoy | gbr |
| 10 | 2009-02-13 00:00:00 | 2008-09 world cup | copenhagen | denmark | team sprint | 1 | jason kenny | gbr |
| 11 | 2009-02-13 00:00:00 | 2008-09 world cup | copenhagen | denmark | team sprint | 1 | jamie staff | gbr |
| 12 | 2009-02-13 00:00:00 | 2008-09 world cup | copenhagen | denmark | sprint | 1 | victoria pendleton | gbr |
| 13 | 2009-10-30 00:00:00 | 2009-10 world cup | manchester | united kingdom | keirin | 1 | chris hoy | gbr |
| 14 | 2009-10-30 00:00:00 | 2009-10 world cup | manchester | united kingdom | sprint | 1 | victoria pendleton | gbr |
| 15 | 2009-10-30 00:00:00 | 2009-10 world cup | manchester | united kingdom | sprint | 1 | chris hoy | gbr |
| 16 | 2009-10-30 00:00:00 | 2009-10 world cup | manchester | united kingdom | 500 m time trial | 2 | victoria pendleton | gbr |
| 17 | 2009-11-01 00:00:00 | 2009-10 world cup | manchester | united kingdom | team sprint | 1 | ross edgar | gbr |
| 18 | 2009-11-01 00:00:00 | 2009-10 world cup | manchester | united kingdom | team sprint | 1 | chris hoy | gbr |
| 19 | 2009-11-01 00:00:00 | 2009-10 world cup | manchester | united kingdom | team sprint | 1 | jamie staff | gbr | | | | count ( "country" ) |
|---:|----------------------:|
| 0 | 4 | | [
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] |
select percentage - percentage where party = 'uup' col : party | candidate(s) | votes | percentage row 1 : uup | peter weir alan mcfarland roy bradford john shields irene cree | 9270 | 25.6 row 2 : uk unionist | robert mccartney valerie kinghan patricia watson | 7579 | 20.9 row 3 : dup | st clair mcalister ruby cooling cecil noble | 6699 | 18.5 row 4 : alliance | oliver napier brian wilson eileen bell larry thompson jane copeland | 6186 | 17.1 row 5 : sdlp | owen adams john burke | 1798 | 5.0 row 6 : pup | victor ash samuel curry neil mehaffy kenneth sterrit | 1694 | 4.7 row 7 : ulster democratic | james mccullough thomas lindsay | 651 | 1.8 row 8 : ni women's coalition | emma mcguigan ann marie foster jane morrice | 496 | 1.4 row 9 : conservative | ann thompson bruce mulligan | 444 | 1.2 row 10 : independent chambers | alan chambers james arbuthnot robert irvine | 334 | 0.9 row 11 : green (ni) | paddy mcevoy mary ringland | 283 | 0.8 row 12 : sinn fein | mairtin o mulleoir john smith | 275 | 0.8 row 13 : labour coalition | john magennis sean mcgouran | 171 | 0.5 row 14 : independent dup | thomas o'brien william baxter | 97 | 0.3 row 15 : democratic left | daryl armitage tim davis | 95 | 0.3 row 16 : workers' party | dessie o'hagan colum mullan | 60 | 0.2 row 17 : ulster independence | geoffrey watson glenn pollock | 49 | 0.1 row 18 : independent voice | christopher carter fidelma carter | 49 | 0.1 row 19 : natural law | peter mcgowan thomas mullins | 15 | 0.0 | col : "percentage - percentage" row 1 : percentage - percentage | select percentage - percentage where party = 'uup' <table_name> : table \begin{tabular}{lllll}
\toprule
& party & candidate(s) & votes & percentage \\
\midrule
0 & uup & peter weir alan mcfarland roy bradford john shields irene cree & 9270 & 25.6 \\
1 & uk unionist & robert mccartney valerie kinghan patricia watson & 7579 & 20.9 \\
2 & dup & st clair mcalister ruby cooling cecil noble & 6699 & 18.5 \\
3 & alliance & oliver napier brian wilson eileen bell larry thompson jane copeland & 6186 & 17.1 \\
4 & sdlp & owen adams john burke & 1798 & 5.0 \\
5 & pup & victor ash samuel curry neil mehaffy kenneth sterrit & 1694 & 4.7 \\
6 & ulster democratic & james mccullough thomas lindsay & 651 & 1.8 \\
7 & ni women's coalition & emma mcguigan ann marie foster jane morrice & 496 & 1.4 \\
8 & conservative & ann thompson bruce mulligan & 444 & 1.2 \\
9 & independent chambers & alan chambers james arbuthnot robert irvine & 334 & 0.9 \\
10 & green (ni) & paddy mcevoy mary ringland & 283 & 0.8 \\
11 & sinn fein & mairtin o mulleoir john smith & 275 & 0.8 \\
12 & labour coalition & john magennis sean mcgouran & 171 & 0.5 \\
13 & independent dup & thomas o'brien william baxter & 97 & 0.3 \\
14 & democratic left & daryl armitage tim davis & 95 & 0.3 \\
15 & workers' party & dessie o'hagan colum mullan & 60 & 0.2 \\
16 & ulster independence & geoffrey watson glenn pollock & 49 & 0.1 \\
17 & independent voice & christopher carter fidelma carter & 49 & 0.1 \\
18 & natural law & peter mcgowan thomas mullins & 15 & 0.0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "percentage - percentage" \\
\midrule
0 & percentage - percentage \\
\bottomrule
\end{tabular}
| select percentage - percentage where party = 'uup' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
<th>candidate(s)</th>
<th>votes</th>
<th>percentage</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>uup</td>
<td>peter weir alan mcfarland roy bradford john shields irene cree</td>
<td>9270</td>
<td>25.6</td>
</tr>
<tr>
<th>1</th>
<td>uk unionist</td>
<td>robert mccartney valerie kinghan patricia watson</td>
<td>7579</td>
<td>20.9</td>
</tr>
<tr>
<th>2</th>
<td>dup</td>
<td>st clair mcalister ruby cooling cecil noble</td>
<td>6699</td>
<td>18.5</td>
</tr>
<tr>
<th>3</th>
<td>alliance</td>
<td>oliver napier brian wilson eileen bell larry thompson jane copeland</td>
<td>6186</td>
<td>17.1</td>
</tr>
<tr>
<th>4</th>
<td>sdlp</td>
<td>owen adams john burke</td>
<td>1798</td>
<td>5.0</td>
</tr>
<tr>
<th>5</th>
<td>pup</td>
<td>victor ash samuel curry neil mehaffy kenneth sterrit</td>
<td>1694</td>
<td>4.7</td>
</tr>
<tr>
<th>6</th>
<td>ulster democratic</td>
<td>james mccullough thomas lindsay</td>
<td>651</td>
<td>1.8</td>
</tr>
<tr>
<th>7</th>
<td>ni women's coalition</td>
<td>emma mcguigan ann marie foster jane morrice</td>
<td>496</td>
<td>1.4</td>
</tr>
<tr>
<th>8</th>
<td>conservative</td>
<td>ann thompson bruce mulligan</td>
<td>444</td>
<td>1.2</td>
</tr>
<tr>
<th>9</th>
<td>independent chambers</td>
<td>alan chambers james arbuthnot robert irvine</td>
<td>334</td>
<td>0.9</td>
</tr>
<tr>
<th>10</th>
<td>green (ni)</td>
<td>paddy mcevoy mary ringland</td>
<td>283</td>
<td>0.8</td>
</tr>
<tr>
<th>11</th>
<td>sinn fein</td>
<td>mairtin o mulleoir john smith</td>
<td>275</td>
<td>0.8</td>
</tr>
<tr>
<th>12</th>
<td>labour coalition</td>
<td>john magennis sean mcgouran</td>
<td>171</td>
<td>0.5</td>
</tr>
<tr>
<th>13</th>
<td>independent dup</td>
<td>thomas o'brien william baxter</td>
<td>97</td>
<td>0.3</td>
</tr>
<tr>
<th>14</th>
<td>democratic left</td>
<td>daryl armitage tim davis</td>
<td>95</td>
<td>0.3</td>
</tr>
<tr>
<th>15</th>
<td>workers' party</td>
<td>dessie o'hagan colum mullan</td>
<td>60</td>
<td>0.2</td>
</tr>
<tr>
<th>16</th>
<td>ulster independence</td>
<td>geoffrey watson glenn pollock</td>
<td>49</td>
<td>0.1</td>
</tr>
<tr>
<th>17</th>
<td>independent voice</td>
<td>christopher carter fidelma carter</td>
<td>49</td>
<td>0.1</td>
</tr>
<tr>
<th>18</th>
<td>natural law</td>
<td>peter mcgowan thomas mullins</td>
<td>15</td>
<td>0.0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"percentage - percentage"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>percentage - percentage</td>
</tr>
</tbody>
</table> | select percentage - percentage where party = 'uup' <table_name> : table | | party | candidate(s) | votes | percentage |
|---:|:---------------------|:--------------------------------------------------------------------|--------:|-------------:|
| 0 | uup | peter weir alan mcfarland roy bradford john shields irene cree | 9270 | 25.6 |
| 1 | uk unionist | robert mccartney valerie kinghan patricia watson | 7579 | 20.9 |
| 2 | dup | st clair mcalister ruby cooling cecil noble | 6699 | 18.5 |
| 3 | alliance | oliver napier brian wilson eileen bell larry thompson jane copeland | 6186 | 17.1 |
| 4 | sdlp | owen adams john burke | 1798 | 5 |
| 5 | pup | victor ash samuel curry neil mehaffy kenneth sterrit | 1694 | 4.7 |
| 6 | ulster democratic | james mccullough thomas lindsay | 651 | 1.8 |
| 7 | ni women's coalition | emma mcguigan ann marie foster jane morrice | 496 | 1.4 |
| 8 | conservative | ann thompson bruce mulligan | 444 | 1.2 |
| 9 | independent chambers | alan chambers james arbuthnot robert irvine | 334 | 0.9 |
| 10 | green (ni) | paddy mcevoy mary ringland | 283 | 0.8 |
| 11 | sinn fein | mairtin o mulleoir john smith | 275 | 0.8 |
| 12 | labour coalition | john magennis sean mcgouran | 171 | 0.5 |
| 13 | independent dup | thomas o'brien william baxter | 97 | 0.3 |
| 14 | democratic left | daryl armitage tim davis | 95 | 0.3 |
| 15 | workers' party | dessie o'hagan colum mullan | 60 | 0.2 |
| 16 | ulster independence | geoffrey watson glenn pollock | 49 | 0.1 |
| 17 | independent voice | christopher carter fidelma carter | 49 | 0.1 |
| 18 | natural law | peter mcgowan thomas mullins | 15 | 0 | | | | "percentage - percentage" |
|---:|:----------------------------|
| 0 | percentage - percentage | | [
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select name where honours = 'won promotion to the fourth tier' col : name | nationality | from | to | honours | comments row 1 : henrik jensen | denmark | 1 july 2012 | present | none | none row 2 : john 'tune' kristiansen | denmark | 18 june 2012 | 23 june 2012 | none | caretaker for one league match row 3 : peer f. hansen | denmark | 1 january 2012 | 18 june 2012 | won promotion to the third tier | none row 4 : john 'tune' kristiansen | denmark | 27 july 2010 | 30 december 2011 | won promotion to the fourth tier | originally had contract until summer 2012 row 5 : rene heitmann | denmark | 17 july 2010 | 27 july 2010 | none | never coached the team in a match row 6 : christian andersen | denmark | 11 july 2009 | 19 june 2010 | team was relegated to third tier | club went bankrupt after the season row 7 : anders theil | denmark | 7 november 2005 | 7 july 2009 | none | originally had contract until summer 2011 row 8 : ebbe skovdahl | denmark | 11 october 2003 | 6 november 2005 | team was relegated to second tier | originally had contract until summer 2007 row 9 : ole mørk | denmark | 15 october 2001 | 10 october 2003 | won promotion to first tier | originally had contract until end of 2004 row 10 : johnny petersen | denmark | 5 may 1998 | 14 october 2001 | none | originally had contract until end of 2001 row 11 : john 'tune' kristiansen | denmark | 1996 | 4 may 1998 | won promotion to second tier | none | col : name row 1 : john 'tune' kristiansen | select name where honours = 'won promotion to the fourth tier' <table_name> : table \begin{tabular}{lllllll}
\toprule
& name & nationality & from & to & honours & comments \\
\midrule
0 & henrik jensen & denmark & 1 july 2012 & present & none & none \\
1 & john 'tune' kristiansen & denmark & 18 june 2012 & 23 june 2012 & none & caretaker for one league match \\
2 & peer f. hansen & denmark & 1 january 2012 & 18 june 2012 & won promotion to the third tier & none \\
3 & john 'tune' kristiansen & denmark & 27 july 2010 & 30 december 2011 & won promotion to the fourth tier & originally had contract until summer 2012 \\
4 & rene heitmann & denmark & 17 july 2010 & 27 july 2010 & none & never coached the team in a match \\
5 & christian andersen & denmark & 11 july 2009 & 19 june 2010 & team was relegated to third tier & club went bankrupt after the season \\
6 & anders theil & denmark & 7 november 2005 & 7 july 2009 & none & originally had contract until summer 2011 \\
7 & ebbe skovdahl & denmark & 11 october 2003 & 6 november 2005 & team was relegated to second tier & originally had contract until summer 2007 \\
8 & ole mørk & denmark & 15 october 2001 & 10 october 2003 & won promotion to first tier & originally had contract until end of 2004 \\
9 & johnny petersen & denmark & 5 may 1998 & 14 october 2001 & none & originally had contract until end of 2001 \\
10 & john 'tune' kristiansen & denmark & 1996 & 4 may 1998 & won promotion to second tier & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& name \\
\midrule
0 & john 'tune' kristiansen \\
\bottomrule
\end{tabular}
| select name where honours = 'won promotion to the fourth tier' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>nationality</th>
<th>from</th>
<th>to</th>
<th>honours</th>
<th>comments</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>henrik jensen</td>
<td>denmark</td>
<td>1 july 2012</td>
<td>present</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>john 'tune' kristiansen</td>
<td>denmark</td>
<td>18 june 2012</td>
<td>23 june 2012</td>
<td>none</td>
<td>caretaker for one league match</td>
</tr>
<tr>
<th>2</th>
<td>peer f. hansen</td>
<td>denmark</td>
<td>1 january 2012</td>
<td>18 june 2012</td>
<td>won promotion to the third tier</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>john 'tune' kristiansen</td>
<td>denmark</td>
<td>27 july 2010</td>
<td>30 december 2011</td>
<td>won promotion to the fourth tier</td>
<td>originally had contract until summer 2012</td>
</tr>
<tr>
<th>4</th>
<td>rene heitmann</td>
<td>denmark</td>
<td>17 july 2010</td>
<td>27 july 2010</td>
<td>none</td>
<td>never coached the team in a match</td>
</tr>
<tr>
<th>5</th>
<td>christian andersen</td>
<td>denmark</td>
<td>11 july 2009</td>
<td>19 june 2010</td>
<td>team was relegated to third tier</td>
<td>club went bankrupt after the season</td>
</tr>
<tr>
<th>6</th>
<td>anders theil</td>
<td>denmark</td>
<td>7 november 2005</td>
<td>7 july 2009</td>
<td>none</td>
<td>originally had contract until summer 2011</td>
</tr>
<tr>
<th>7</th>
<td>ebbe skovdahl</td>
<td>denmark</td>
<td>11 october 2003</td>
<td>6 november 2005</td>
<td>team was relegated to second tier</td>
<td>originally had contract until summer 2007</td>
</tr>
<tr>
<th>8</th>
<td>ole mørk</td>
<td>denmark</td>
<td>15 october 2001</td>
<td>10 october 2003</td>
<td>won promotion to first tier</td>
<td>originally had contract until end of 2004</td>
</tr>
<tr>
<th>9</th>
<td>johnny petersen</td>
<td>denmark</td>
<td>5 may 1998</td>
<td>14 october 2001</td>
<td>none</td>
<td>originally had contract until end of 2001</td>
</tr>
<tr>
<th>10</th>
<td>john 'tune' kristiansen</td>
<td>denmark</td>
<td>1996</td>
<td>4 may 1998</td>
<td>won promotion to second tier</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>john 'tune' kristiansen</td>
</tr>
</tbody>
</table> | select name where honours = 'won promotion to the fourth tier' <table_name> : table | | name | nationality | from | to | honours | comments |
|---:|:------------------------|:--------------|:----------------|:-----------------|:----------------------------------|:------------------------------------------|
| 0 | henrik jensen | denmark | 1 july 2012 | present | none | none |
| 1 | john 'tune' kristiansen | denmark | 18 june 2012 | 23 june 2012 | none | caretaker for one league match |
| 2 | peer f. hansen | denmark | 1 january 2012 | 18 june 2012 | won promotion to the third tier | none |
| 3 | john 'tune' kristiansen | denmark | 27 july 2010 | 30 december 2011 | won promotion to the fourth tier | originally had contract until summer 2012 |
| 4 | rene heitmann | denmark | 17 july 2010 | 27 july 2010 | none | never coached the team in a match |
| 5 | christian andersen | denmark | 11 july 2009 | 19 june 2010 | team was relegated to third tier | club went bankrupt after the season |
| 6 | anders theil | denmark | 7 november 2005 | 7 july 2009 | none | originally had contract until summer 2011 |
| 7 | ebbe skovdahl | denmark | 11 october 2003 | 6 november 2005 | team was relegated to second tier | originally had contract until summer 2007 |
| 8 | ole mørk | denmark | 15 october 2001 | 10 october 2003 | won promotion to first tier | originally had contract until end of 2004 |
| 9 | johnny petersen | denmark | 5 may 1998 | 14 october 2001 | none | originally had contract until end of 2001 |
| 10 | john 'tune' kristiansen | denmark | 1996 | 4 may 1998 | won promotion to second tier | none | | | | name |
|---:|:------------------------|
| 0 | john 'tune' kristiansen | | [
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] |
select games where games = '1932 winter olympics' order by nations asc limit 1097 col : games | host city | dates | nations | participants | events row 1 : 1904 summer olympics | st. louis, missouri | 1 july - 23 november | 12 | 651 | 91 row 2 : 1932 winter olympics | lake placid, new york | 7 - 15 february | 17 | 252 | 14 row 3 : 1932 summer olympics | los angeles, california | 30 july - 14 august | 37 | 1332 | 117 row 4 : 1960 winter olympics | squaw valley, california | 2 - 20 february | 30 | 665 | 27 row 5 : 1980 winter olympics | lake placid, new york | 13 - 24 february | 37 | 1072 | 38 row 6 : 1984 summer olympics | los angeles, california | 20 july - 18 august | 140 | 6829 | 221 row 7 : 1996 summer olympics | atlanta, georgia | 18 july - 4 august | 197 | 1318 | 271 row 8 : 2002 winter olympics | salt lake city, utah | 8 - 24 february | 77 | 2399 | 78 | col : games row 1 : 1932 winter olympics | select games where games = '1932 winter olympics' order by nations asc limit 1097 <table_name> : table \begin{tabular}{lllllll}
\toprule
& games & host city & dates & nations & participants & events \\
\midrule
0 & 1904 summer olympics & st. louis, missouri & 1 july - 23 november & 12 & 651 & 91 \\
1 & 1932 winter olympics & lake placid, new york & 7 - 15 february & 17 & 252 & 14 \\
2 & 1932 summer olympics & los angeles, california & 30 july - 14 august & 37 & 1332 & 117 \\
3 & 1960 winter olympics & squaw valley, california & 2 - 20 february & 30 & 665 & 27 \\
4 & 1980 winter olympics & lake placid, new york & 13 - 24 february & 37 & 1072 & 38 \\
5 & 1984 summer olympics & los angeles, california & 20 july - 18 august & 140 & 6829 & 221 \\
6 & 1996 summer olympics & atlanta, georgia & 18 july - 4 august & 197 & 1318 & 271 \\
7 & 2002 winter olympics & salt lake city, utah & 8 - 24 february & 77 & 2399 & 78 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& games \\
\midrule
0 & 1932 winter olympics \\
\bottomrule
\end{tabular}
| select games where games = '1932 winter olympics' order by nations asc limit 1097 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>games</th>
<th>host city</th>
<th>dates</th>
<th>nations</th>
<th>participants</th>
<th>events</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1904 summer olympics</td>
<td>st. louis, missouri</td>
<td>1 july - 23 november</td>
<td>12</td>
<td>651</td>
<td>91</td>
</tr>
<tr>
<th>1</th>
<td>1932 winter olympics</td>
<td>lake placid, new york</td>
<td>7 - 15 february</td>
<td>17</td>
<td>252</td>
<td>14</td>
</tr>
<tr>
<th>2</th>
<td>1932 summer olympics</td>
<td>los angeles, california</td>
<td>30 july - 14 august</td>
<td>37</td>
<td>1332</td>
<td>117</td>
</tr>
<tr>
<th>3</th>
<td>1960 winter olympics</td>
<td>squaw valley, california</td>
<td>2 - 20 february</td>
<td>30</td>
<td>665</td>
<td>27</td>
</tr>
<tr>
<th>4</th>
<td>1980 winter olympics</td>
<td>lake placid, new york</td>
<td>13 - 24 february</td>
<td>37</td>
<td>1072</td>
<td>38</td>
</tr>
<tr>
<th>5</th>
<td>1984 summer olympics</td>
<td>los angeles, california</td>
<td>20 july - 18 august</td>
<td>140</td>
<td>6829</td>
<td>221</td>
</tr>
<tr>
<th>6</th>
<td>1996 summer olympics</td>
<td>atlanta, georgia</td>
<td>18 july - 4 august</td>
<td>197</td>
<td>1318</td>
<td>271</td>
</tr>
<tr>
<th>7</th>
<td>2002 winter olympics</td>
<td>salt lake city, utah</td>
<td>8 - 24 february</td>
<td>77</td>
<td>2399</td>
<td>78</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>games</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1932 winter olympics</td>
</tr>
</tbody>
</table> | select games where games = '1932 winter olympics' order by nations asc limit 1097 <table_name> : table | | games | host city | dates | nations | participants | events |
|---:|:---------------------|:-------------------------|:---------------------|----------:|---------------:|---------:|
| 0 | 1904 summer olympics | st. louis, missouri | 1 july - 23 november | 12 | 651 | 91 |
| 1 | 1932 winter olympics | lake placid, new york | 7 - 15 february | 17 | 252 | 14 |
| 2 | 1932 summer olympics | los angeles, california | 30 july - 14 august | 37 | 1332 | 117 |
| 3 | 1960 winter olympics | squaw valley, california | 2 - 20 february | 30 | 665 | 27 |
| 4 | 1980 winter olympics | lake placid, new york | 13 - 24 february | 37 | 1072 | 38 |
| 5 | 1984 summer olympics | los angeles, california | 20 july - 18 august | 140 | 6829 | 221 |
| 6 | 1996 summer olympics | atlanta, georgia | 18 july - 4 august | 197 | 1318 | 271 |
| 7 | 2002 winter olympics | salt lake city, utah | 8 - 24 february | 77 | 2399 | 78 | | | | games |
|---:|:---------------------|
| 0 | 1932 winter olympics | | [
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select n where v2 = '0%' col : category | age (ethnicity) | n | v1 | v2 | v3 | v4 | v5 | v6 row 1 : none | 1 week - 1 y | 210 | 92% | 74% | 27% | 20% | 0.50% | 0% row 2 : none | 1 y - 2 y | 154 | 96% | 85% | 39% | 10% | 0.70% | 0% row 3 : none | 2 y - 5 y | 202 | 98% | 50% | 22% | 7% | 1% | 0% row 4 : none | 5 y - 8 y | 94 | 91% | 25% | 14% | 5% | 1% | 1% row 5 : none | 8 y - 16 y | 90 | 62% | 7% | 2% | 0% | 0% | 0% row 6 : males | 12 y - 13 y | 209 | 47% | 7% | 0% | 0% | 0% | 0% row 7 : males | 13 y - 14 y | 260 | 35% | 4.60% | 0.80% | 0% | 0% | 0% row 8 : males | 16 y - 19 y (whites) | 50 | 32% | 0% | 0% | 0% | 0% | 0% row 9 : males | 16 y - 19 y (blacks) | 310 | 46% | 7% | 2.90% | 1.30% | 0% | 0% row 10 : males | 20 - 30 y (whites) | 285 | 41% | 0% | 0% | 0% | 0% | 0% row 11 : males | 20 - 30 y (blacks) | 295 | 37% | 0% | 0% | 0% | 0% | 0% row 12 : females | 12 y - 13 y | 174 | 69% | 11% | 1.20% | 0% | 0% | 0% row 13 : females | 13 y - 14 y | 154 | 52% | 8.40% | 1.40% | 0% | 0% | 0% row 14 : females | 16 y - 19 y (whites) | 50 | 66% | 0% | 0% | 0% | 0% | 0% row 15 : females | 16 - 19 y (blacks) | 310 | 73% | 9% | 1.30% | 0.60% | 0% | 0% row 16 : females | 20 - 30 y (whites) | 280 | 55% | 0% | 0% | 0% | 0% | 0% row 17 : females | 20 - 30 y (blacks) | 330 | 55% | 2.40% | 1% | 0% | 0% | 0% | col : n row 1 : 50 row 2 : 285 row 3 : 295 row 4 : 50 row 5 : 280 | select n where v2 = '0%' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& category & age (ethnicity) & n & v1 & v2 & v3 & v4 & v5 & v6 \\
\midrule
0 & none & 1 week - 1 y & 210 & 92% & 74% & 27% & 20% & 0.50% & 0% \\
1 & none & 1 y - 2 y & 154 & 96% & 85% & 39% & 10% & 0.70% & 0% \\
2 & none & 2 y - 5 y & 202 & 98% & 50% & 22% & 7% & 1% & 0% \\
3 & none & 5 y - 8 y & 94 & 91% & 25% & 14% & 5% & 1% & 1% \\
4 & none & 8 y - 16 y & 90 & 62% & 7% & 2% & 0% & 0% & 0% \\
5 & males & 12 y - 13 y & 209 & 47% & 7% & 0% & 0% & 0% & 0% \\
6 & males & 13 y - 14 y & 260 & 35% & 4.60% & 0.80% & 0% & 0% & 0% \\
7 & males & 16 y - 19 y (whites) & 50 & 32% & 0% & 0% & 0% & 0% & 0% \\
8 & males & 16 y - 19 y (blacks) & 310 & 46% & 7% & 2.90% & 1.30% & 0% & 0% \\
9 & males & 20 - 30 y (whites) & 285 & 41% & 0% & 0% & 0% & 0% & 0% \\
10 & males & 20 - 30 y (blacks) & 295 & 37% & 0% & 0% & 0% & 0% & 0% \\
11 & females & 12 y - 13 y & 174 & 69% & 11% & 1.20% & 0% & 0% & 0% \\
12 & females & 13 y - 14 y & 154 & 52% & 8.40% & 1.40% & 0% & 0% & 0% \\
13 & females & 16 y - 19 y (whites) & 50 & 66% & 0% & 0% & 0% & 0% & 0% \\
14 & females & 16 - 19 y (blacks) & 310 & 73% & 9% & 1.30% & 0.60% & 0% & 0% \\
15 & females & 20 - 30 y (whites) & 280 & 55% & 0% & 0% & 0% & 0% & 0% \\
16 & females & 20 - 30 y (blacks) & 330 & 55% & 2.40% & 1% & 0% & 0% & 0% \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& n \\
\midrule
0 & 50 \\
1 & 285 \\
2 & 295 \\
3 & 50 \\
4 & 280 \\
\bottomrule
\end{tabular}
| select n where v2 = '0%' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>category</th>
<th>age (ethnicity)</th>
<th>n</th>
<th>v1</th>
<th>v2</th>
<th>v3</th>
<th>v4</th>
<th>v5</th>
<th>v6</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>1 week - 1 y</td>
<td>210</td>
<td>92%</td>
<td>74%</td>
<td>27%</td>
<td>20%</td>
<td>0.50%</td>
<td>0%</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>1 y - 2 y</td>
<td>154</td>
<td>96%</td>
<td>85%</td>
<td>39%</td>
<td>10%</td>
<td>0.70%</td>
<td>0%</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>2 y - 5 y</td>
<td>202</td>
<td>98%</td>
<td>50%</td>
<td>22%</td>
<td>7%</td>
<td>1%</td>
<td>0%</td>
</tr>
<tr>
<th>3</th>
<td>none</td>
<td>5 y - 8 y</td>
<td>94</td>
<td>91%</td>
<td>25%</td>
<td>14%</td>
<td>5%</td>
<td>1%</td>
<td>1%</td>
</tr>
<tr>
<th>4</th>
<td>none</td>
<td>8 y - 16 y</td>
<td>90</td>
<td>62%</td>
<td>7%</td>
<td>2%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>5</th>
<td>males</td>
<td>12 y - 13 y</td>
<td>209</td>
<td>47%</td>
<td>7%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>6</th>
<td>males</td>
<td>13 y - 14 y</td>
<td>260</td>
<td>35%</td>
<td>4.60%</td>
<td>0.80%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>7</th>
<td>males</td>
<td>16 y - 19 y (whites)</td>
<td>50</td>
<td>32%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>8</th>
<td>males</td>
<td>16 y - 19 y (blacks)</td>
<td>310</td>
<td>46%</td>
<td>7%</td>
<td>2.90%</td>
<td>1.30%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>9</th>
<td>males</td>
<td>20 - 30 y (whites)</td>
<td>285</td>
<td>41%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>10</th>
<td>males</td>
<td>20 - 30 y (blacks)</td>
<td>295</td>
<td>37%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>11</th>
<td>females</td>
<td>12 y - 13 y</td>
<td>174</td>
<td>69%</td>
<td>11%</td>
<td>1.20%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>12</th>
<td>females</td>
<td>13 y - 14 y</td>
<td>154</td>
<td>52%</td>
<td>8.40%</td>
<td>1.40%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>13</th>
<td>females</td>
<td>16 y - 19 y (whites)</td>
<td>50</td>
<td>66%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>14</th>
<td>females</td>
<td>16 - 19 y (blacks)</td>
<td>310</td>
<td>73%</td>
<td>9%</td>
<td>1.30%</td>
<td>0.60%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>15</th>
<td>females</td>
<td>20 - 30 y (whites)</td>
<td>280</td>
<td>55%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>16</th>
<td>females</td>
<td>20 - 30 y (blacks)</td>
<td>330</td>
<td>55%</td>
<td>2.40%</td>
<td>1%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>n</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>50</td>
</tr>
<tr>
<th>1</th>
<td>285</td>
</tr>
<tr>
<th>2</th>
<td>295</td>
</tr>
<tr>
<th>3</th>
<td>50</td>
</tr>
<tr>
<th>4</th>
<td>280</td>
</tr>
</tbody>
</table> | select n where v2 = '0%' <table_name> : table | | category | age (ethnicity) | n | v1 | v2 | v3 | v4 | v5 | v6 |
|---:|:-----------|:---------------------|----:|:-----|:------|:------|:------|:------|:-----|
| 0 | none | 1 week - 1 y | 210 | 92% | 74% | 27% | 20% | 0.50% | 0% |
| 1 | none | 1 y - 2 y | 154 | 96% | 85% | 39% | 10% | 0.70% | 0% |
| 2 | none | 2 y - 5 y | 202 | 98% | 50% | 22% | 7% | 1% | 0% |
| 3 | none | 5 y - 8 y | 94 | 91% | 25% | 14% | 5% | 1% | 1% |
| 4 | none | 8 y - 16 y | 90 | 62% | 7% | 2% | 0% | 0% | 0% |
| 5 | males | 12 y - 13 y | 209 | 47% | 7% | 0% | 0% | 0% | 0% |
| 6 | males | 13 y - 14 y | 260 | 35% | 4.60% | 0.80% | 0% | 0% | 0% |
| 7 | males | 16 y - 19 y (whites) | 50 | 32% | 0% | 0% | 0% | 0% | 0% |
| 8 | males | 16 y - 19 y (blacks) | 310 | 46% | 7% | 2.90% | 1.30% | 0% | 0% |
| 9 | males | 20 - 30 y (whites) | 285 | 41% | 0% | 0% | 0% | 0% | 0% |
| 10 | males | 20 - 30 y (blacks) | 295 | 37% | 0% | 0% | 0% | 0% | 0% |
| 11 | females | 12 y - 13 y | 174 | 69% | 11% | 1.20% | 0% | 0% | 0% |
| 12 | females | 13 y - 14 y | 154 | 52% | 8.40% | 1.40% | 0% | 0% | 0% |
| 13 | females | 16 y - 19 y (whites) | 50 | 66% | 0% | 0% | 0% | 0% | 0% |
| 14 | females | 16 - 19 y (blacks) | 310 | 73% | 9% | 1.30% | 0.60% | 0% | 0% |
| 15 | females | 20 - 30 y (whites) | 280 | 55% | 0% | 0% | 0% | 0% | 0% |
| 16 | females | 20 - 30 y (blacks) | 330 | 55% | 2.40% | 1% | 0% | 0% | 0% | | | | n |
|---:|----:|
| 0 | 50 |
| 1 | 285 |
| 2 | 295 |
| 3 | 50 |
| 4 | 280 | | [
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select standard where foundation = 'must be root of forest and domain' col : specifications | foundation | essentials | standard | datacenter row 1 : distribution | oem only | retail, volume licensing, oem | retail, volume licensing, oem | volume licensing and oem row 2 : licensing model | per server | per server | per cpu pair + cal | per cpu pair + cal row 3 : processor chip limit | 1 | 2 | 64 | 64 row 4 : memory limit | 32 gb | 64 gb | 4 tb | 4 tb row 5 : user limit | 15 | 25 | unlimited | unlimited row 6 : file services limits | 1 standalone dfs root | 1 standalone dfs root | unlimited | unlimited row 7 : network policy and access services limits | 50 rras connections and 10 ias connections | 250 rras connections, 50 ias connections, and 2 ias server groups | unlimited | unlimited row 8 : remote desktop services limits | 50 remote desktop services connections | gateway only | unlimited | unlimited row 9 : virtualization rights | none | either in 1 vm or 1 physical server, but not both at once | 2 vms | unlimited row 10 : dhcp role | yes | yes | yes | yes row 11 : dns server role | yes | yes | yes | yes row 12 : fax server role | yes | yes | yes | yes row 13 : uddi services | yes | yes | yes | yes row 14 : print and document services | yes | yes | yes | yes row 15 : web services (internet information services) | yes | yes | yes | yes row 16 : windows deployment services | yes | yes | yes | yes row 17 : windows server update services | no | yes | yes | yes row 18 : active directory lightweight directory services | yes | yes | yes | yes row 19 : active directory rights management services | yes | yes | yes | yes row 20 : application server role | yes | yes | yes | yes row 21 : server manager | yes | yes | yes | yes row 22 : windows powershell | yes | yes | yes | yes row 23 : active directory domain services | must be root of forest and domain | must be root of forest and domain | yes | yes row 24 : active directory certificate services | certificate authorities only | certificate authorities only | yes | yes row 25 : active directory federation services | yes | no | yes | yes row 26 : server core mode | no | no | yes | yes row 27 : hyper-v | no | no | yes | yes | col : standard row 1 : yes | select standard where foundation = 'must be root of forest and domain' <table_name> : table \begin{tabular}{llllll}
\toprule
& specifications & foundation & essentials & standard & datacenter \\
\midrule
0 & distribution & oem only & retail, volume licensing, oem & retail, volume licensing, oem & volume licensing and oem \\
1 & licensing model & per server & per server & per cpu pair + cal & per cpu pair + cal \\
2 & processor chip limit & 1 & 2 & 64 & 64 \\
3 & memory limit & 32 gb & 64 gb & 4 tb & 4 tb \\
4 & user limit & 15 & 25 & unlimited & unlimited \\
5 & file services limits & 1 standalone dfs root & 1 standalone dfs root & unlimited & unlimited \\
6 & network policy and access services limits & 50 rras connections and 10 ias connections & 250 rras connections, 50 ias connections, and 2 ias server groups & unlimited & unlimited \\
7 & remote desktop services limits & 50 remote desktop services connections & gateway only & unlimited & unlimited \\
8 & virtualization rights & none & either in 1 vm or 1 physical server, but not both at once & 2 vms & unlimited \\
9 & dhcp role & yes & yes & yes & yes \\
10 & dns server role & yes & yes & yes & yes \\
11 & fax server role & yes & yes & yes & yes \\
12 & uddi services & yes & yes & yes & yes \\
13 & print and document services & yes & yes & yes & yes \\
14 & web services (internet information services) & yes & yes & yes & yes \\
15 & windows deployment services & yes & yes & yes & yes \\
16 & windows server update services & no & yes & yes & yes \\
17 & active directory lightweight directory services & yes & yes & yes & yes \\
18 & active directory rights management services & yes & yes & yes & yes \\
19 & application server role & yes & yes & yes & yes \\
20 & server manager & yes & yes & yes & yes \\
21 & windows powershell & yes & yes & yes & yes \\
22 & active directory domain services & must be root of forest and domain & must be root of forest and domain & yes & yes \\
23 & active directory certificate services & certificate authorities only & certificate authorities only & yes & yes \\
24 & active directory federation services & yes & no & yes & yes \\
25 & server core mode & no & no & yes & yes \\
26 & hyper-v & no & no & yes & yes \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& standard \\
\midrule
0 & yes \\
\bottomrule
\end{tabular}
| select standard where foundation = 'must be root of forest and domain' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>specifications</th>
<th>foundation</th>
<th>essentials</th>
<th>standard</th>
<th>datacenter</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>distribution</td>
<td>oem only</td>
<td>retail, volume licensing, oem</td>
<td>retail, volume licensing, oem</td>
<td>volume licensing and oem</td>
</tr>
<tr>
<th>1</th>
<td>licensing model</td>
<td>per server</td>
<td>per server</td>
<td>per cpu pair + cal</td>
<td>per cpu pair + cal</td>
</tr>
<tr>
<th>2</th>
<td>processor chip limit</td>
<td>1</td>
<td>2</td>
<td>64</td>
<td>64</td>
</tr>
<tr>
<th>3</th>
<td>memory limit</td>
<td>32 gb</td>
<td>64 gb</td>
<td>4 tb</td>
<td>4 tb</td>
</tr>
<tr>
<th>4</th>
<td>user limit</td>
<td>15</td>
<td>25</td>
<td>unlimited</td>
<td>unlimited</td>
</tr>
<tr>
<th>5</th>
<td>file services limits</td>
<td>1 standalone dfs root</td>
<td>1 standalone dfs root</td>
<td>unlimited</td>
<td>unlimited</td>
</tr>
<tr>
<th>6</th>
<td>network policy and access services limits</td>
<td>50 rras connections and 10 ias connections</td>
<td>250 rras connections, 50 ias connections, and 2 ias server groups</td>
<td>unlimited</td>
<td>unlimited</td>
</tr>
<tr>
<th>7</th>
<td>remote desktop services limits</td>
<td>50 remote desktop services connections</td>
<td>gateway only</td>
<td>unlimited</td>
<td>unlimited</td>
</tr>
<tr>
<th>8</th>
<td>virtualization rights</td>
<td>none</td>
<td>either in 1 vm or 1 physical server, but not both at once</td>
<td>2 vms</td>
<td>unlimited</td>
</tr>
<tr>
<th>9</th>
<td>dhcp role</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>10</th>
<td>dns server role</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>11</th>
<td>fax server role</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>12</th>
<td>uddi services</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>13</th>
<td>print and document services</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>14</th>
<td>web services (internet information services)</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>15</th>
<td>windows deployment services</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>16</th>
<td>windows server update services</td>
<td>no</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>17</th>
<td>active directory lightweight directory services</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>18</th>
<td>active directory rights management services</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>19</th>
<td>application server role</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>20</th>
<td>server manager</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>21</th>
<td>windows powershell</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>22</th>
<td>active directory domain services</td>
<td>must be root of forest and domain</td>
<td>must be root of forest and domain</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>23</th>
<td>active directory certificate services</td>
<td>certificate authorities only</td>
<td>certificate authorities only</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>24</th>
<td>active directory federation services</td>
<td>yes</td>
<td>no</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>25</th>
<td>server core mode</td>
<td>no</td>
<td>no</td>
<td>yes</td>
<td>yes</td>
</tr>
<tr>
<th>26</th>
<td>hyper-v</td>
<td>no</td>
<td>no</td>
<td>yes</td>
<td>yes</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>standard</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>yes</td>
</tr>
</tbody>
</table> | select standard where foundation = 'must be root of forest and domain' <table_name> : table | | specifications | foundation | essentials | standard | datacenter |
|---:|:------------------------------------------------|:-------------------------------------------|:------------------------------------------------------------------|:------------------------------|:-------------------------|
| 0 | distribution | oem only | retail, volume licensing, oem | retail, volume licensing, oem | volume licensing and oem |
| 1 | licensing model | per server | per server | per cpu pair + cal | per cpu pair + cal |
| 2 | processor chip limit | 1 | 2 | 64 | 64 |
| 3 | memory limit | 32 gb | 64 gb | 4 tb | 4 tb |
| 4 | user limit | 15 | 25 | unlimited | unlimited |
| 5 | file services limits | 1 standalone dfs root | 1 standalone dfs root | unlimited | unlimited |
| 6 | network policy and access services limits | 50 rras connections and 10 ias connections | 250 rras connections, 50 ias connections, and 2 ias server groups | unlimited | unlimited |
| 7 | remote desktop services limits | 50 remote desktop services connections | gateway only | unlimited | unlimited |
| 8 | virtualization rights | none | either in 1 vm or 1 physical server, but not both at once | 2 vms | unlimited |
| 9 | dhcp role | yes | yes | yes | yes |
| 10 | dns server role | yes | yes | yes | yes |
| 11 | fax server role | yes | yes | yes | yes |
| 12 | uddi services | yes | yes | yes | yes |
| 13 | print and document services | yes | yes | yes | yes |
| 14 | web services (internet information services) | yes | yes | yes | yes |
| 15 | windows deployment services | yes | yes | yes | yes |
| 16 | windows server update services | no | yes | yes | yes |
| 17 | active directory lightweight directory services | yes | yes | yes | yes |
| 18 | active directory rights management services | yes | yes | yes | yes |
| 19 | application server role | yes | yes | yes | yes |
| 20 | server manager | yes | yes | yes | yes |
| 21 | windows powershell | yes | yes | yes | yes |
| 22 | active directory domain services | must be root of forest and domain | must be root of forest and domain | yes | yes |
| 23 | active directory certificate services | certificate authorities only | certificate authorities only | yes | yes |
| 24 | active directory federation services | yes | no | yes | yes |
| 25 | server core mode | no | no | yes | yes |
| 26 | hyper-v | no | no | yes | yes | | | | standard |
|---:|:-----------|
| 0 | yes | | [
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select count ( * ) where album = 'eleventh hour' col : year | song | us r&b | us rap | album row 1 : 1991 | "mistadobalina" | 55 | 6 | i wish my brother george was here row 2 : 1991 | "sleepin' on my couch" | none | none | i wish my brother george was here row 3 : 1992 | "dr. bombay.." | none | none | i wish my brother george was here row 4 : 1993 | "catch a bad one" | none | none | no need for alarm row 5 : 1994 | "wrong place" | none | 48 | no need for alarm row 6 : 1999 | "phoney phranchise" | none | 47 | both sides of the brain row 7 : 2000 | "if you must" | none | 27 | both sides of the brain row 8 : 2008 | "workin' it" | none | none | eleventh hour row 9 : 2011 | "one out of a million" | none | none | golden era | col : count ( "*" ) row 1 : 1 | select count ( * ) where album = 'eleventh hour' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & song & us r&b & us rap & album \\
\midrule
0 & 1991 & "mistadobalina" & 55 & 6 & i wish my brother george was here \\
1 & 1991 & "sleepin' on my couch" & none & none & i wish my brother george was here \\
2 & 1992 & "dr. bombay.." & none & none & i wish my brother george was here \\
3 & 1993 & "catch a bad one" & none & none & no need for alarm \\
4 & 1994 & "wrong place" & none & 48 & no need for alarm \\
5 & 1999 & "phoney phranchise" & none & 47 & both sides of the brain \\
6 & 2000 & "if you must" & none & 27 & both sides of the brain \\
7 & 2008 & "workin' it" & none & none & eleventh hour \\
8 & 2011 & "one out of a million" & none & none & golden era \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where album = 'eleventh hour' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>song</th>
<th>us r&b</th>
<th>us rap</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1991</td>
<td>"mistadobalina"</td>
<td>55</td>
<td>6</td>
<td>i wish my brother george was here</td>
</tr>
<tr>
<th>1</th>
<td>1991</td>
<td>"sleepin' on my couch"</td>
<td>none</td>
<td>none</td>
<td>i wish my brother george was here</td>
</tr>
<tr>
<th>2</th>
<td>1992</td>
<td>"dr. bombay.."</td>
<td>none</td>
<td>none</td>
<td>i wish my brother george was here</td>
</tr>
<tr>
<th>3</th>
<td>1993</td>
<td>"catch a bad one"</td>
<td>none</td>
<td>none</td>
<td>no need for alarm</td>
</tr>
<tr>
<th>4</th>
<td>1994</td>
<td>"wrong place"</td>
<td>none</td>
<td>48</td>
<td>no need for alarm</td>
</tr>
<tr>
<th>5</th>
<td>1999</td>
<td>"phoney phranchise"</td>
<td>none</td>
<td>47</td>
<td>both sides of the brain</td>
</tr>
<tr>
<th>6</th>
<td>2000</td>
<td>"if you must"</td>
<td>none</td>
<td>27</td>
<td>both sides of the brain</td>
</tr>
<tr>
<th>7</th>
<td>2008</td>
<td>"workin' it"</td>
<td>none</td>
<td>none</td>
<td>eleventh hour</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>"one out of a million"</td>
<td>none</td>
<td>none</td>
<td>golden era</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where album = 'eleventh hour' <table_name> : table | | year | song | us r&b | us rap | album |
|---:|-------:|:-----------------------|:---------|:---------|:----------------------------------|
| 0 | 1991 | "mistadobalina" | 55 | 6 | i wish my brother george was here |
| 1 | 1991 | "sleepin' on my couch" | none | none | i wish my brother george was here |
| 2 | 1992 | "dr. bombay.." | none | none | i wish my brother george was here |
| 3 | 1993 | "catch a bad one" | none | none | no need for alarm |
| 4 | 1994 | "wrong place" | none | 48 | no need for alarm |
| 5 | 1999 | "phoney phranchise" | none | 47 | both sides of the brain |
| 6 | 2000 | "if you must" | none | 27 | both sides of the brain |
| 7 | 2008 | "workin' it" | none | none | eleventh hour |
| 8 | 2011 | "one out of a million" | none | none | golden era | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select nation where bronze = 3 col : rank | nation | gold | silver | bronze | total row 1 : 1 | venezuela | 5 | 2 | 3 | 10 row 2 : 2 | colombia | 4 | 4 | 9 | 17 row 3 : 3 | dominican republic | 4 | 3 | 4 | 11 row 4 : 4 | peru | 3 | 3 | 8 | 14 row 5 : 5 | ecuador | 2 | 3 | 3 | 8 row 6 : 6 | guatemala | 1 | 1 | 1 | 3 row 7 : 7 | chile | 0 | 3 | 2 | 5 row 8 : 8 | panama | 0 | 0 | 3 | 3 row 9 : 9 | bolivia | 0 | 0 | 1 | 1 row 10 : 9 | paraguay | 0 | 0 | 1 | 1 row 11 : total | total | 19 | 19 | 35 | 73 | col : nation row 1 : venezuela row 2 : ecuador row 3 : panama | select nation where bronze = 3 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & venezuela & 5 & 2 & 3 & 10 \\
1 & 2 & colombia & 4 & 4 & 9 & 17 \\
2 & 3 & dominican republic & 4 & 3 & 4 & 11 \\
3 & 4 & peru & 3 & 3 & 8 & 14 \\
4 & 5 & ecuador & 2 & 3 & 3 & 8 \\
5 & 6 & guatemala & 1 & 1 & 1 & 3 \\
6 & 7 & chile & 0 & 3 & 2 & 5 \\
7 & 8 & panama & 0 & 0 & 3 & 3 \\
8 & 9 & bolivia & 0 & 0 & 1 & 1 \\
9 & 9 & paraguay & 0 & 0 & 1 & 1 \\
10 & total & total & 19 & 19 & 35 & 73 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & venezuela \\
1 & ecuador \\
2 & panama \\
\bottomrule
\end{tabular}
| select nation where bronze = 3 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>venezuela</td>
<td>5</td>
<td>2</td>
<td>3</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>colombia</td>
<td>4</td>
<td>4</td>
<td>9</td>
<td>17</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>dominican republic</td>
<td>4</td>
<td>3</td>
<td>4</td>
<td>11</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>peru</td>
<td>3</td>
<td>3</td>
<td>8</td>
<td>14</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>ecuador</td>
<td>2</td>
<td>3</td>
<td>3</td>
<td>8</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>guatemala</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>chile</td>
<td>0</td>
<td>3</td>
<td>2</td>
<td>5</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>panama</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>bolivia</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>paraguay</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>total</td>
<td>total</td>
<td>19</td>
<td>19</td>
<td>35</td>
<td>73</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>venezuela</td>
</tr>
<tr>
<th>1</th>
<td>ecuador</td>
</tr>
<tr>
<th>2</th>
<td>panama</td>
</tr>
</tbody>
</table> | select nation where bronze = 3 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:-------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | venezuela | 5 | 2 | 3 | 10 |
| 1 | 2 | colombia | 4 | 4 | 9 | 17 |
| 2 | 3 | dominican republic | 4 | 3 | 4 | 11 |
| 3 | 4 | peru | 3 | 3 | 8 | 14 |
| 4 | 5 | ecuador | 2 | 3 | 3 | 8 |
| 5 | 6 | guatemala | 1 | 1 | 1 | 3 |
| 6 | 7 | chile | 0 | 3 | 2 | 5 |
| 7 | 8 | panama | 0 | 0 | 3 | 3 |
| 8 | 9 | bolivia | 0 | 0 | 1 | 1 |
| 9 | 9 | paraguay | 0 | 0 | 1 | 1 |
| 10 | total | total | 19 | 19 | 35 | 73 | | | | nation |
|---:|:----------|
| 0 | venezuela |
| 1 | ecuador |
| 2 | panama | | [
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select count ( club ) where position = 7 col : position | club | played | points | wins | draws | losses | goals for | goals against | goal difference row 1 : 1 | malaga cf | 42 | 79 | 22 | 13 | 7 | 72 | 47 | 25 row 2 : 2 | atletico de madrid b 1 | 42 | 74 | 21 | 11 | 10 | 73 | 51 | 22 row 3 : 3 | cd numancia | 42 | 73 | 21 | 10 | 11 | 68 | 40 | 28 row 4 : 4 | sevilla fc | 42 | 71 | 20 | 11 | 11 | 66 | 50 | 16 row 5 : 5 | rayo vallecano | 42 | 71 | 19 | 14 | 9 | 64 | 49 | 15 row 6 : 6 | ud las palmas | 42 | 68 | 17 | 17 | 8 | 57 | 38 | 19 row 7 : 7 | cd toledo | 42 | 65 | 18 | 11 | 13 | 54 | 49 | 5 row 8 : 8 | sd compostela | 42 | 61 | 16 | 13 | 13 | 60 | 53 | 7 row 9 : 9 | sporting de gijon | 42 | 59 | 16 | 11 | 15 | 47 | 47 | 0 row 10 : 10 | cp merida | 42 | 59 | 15 | 14 | 13 | 48 | 41 | 7 row 11 : 11 | ue lleida | 42 | 59 | 15 | 14 | 13 | 52 | 50 | 2 row 12 : 12 | recreativo de huelva | 42 | 58 | 14 | 16 | 12 | 40 | 35 | 5 row 13 : 13 | ca osasuna | 42 | 57 | 15 | 12 | 15 | 44 | 51 | -7 row 14 : 14 | cd badajoz | 42 | 51 | 12 | 15 | 15 | 35 | 39 | -4 row 15 : 15 | albacete | 42 | 50 | 12 | 14 | 16 | 38 | 43 | -5 row 16 : 16 | cd logrones | 42 | 48 | 12 | 12 | 18 | 48 | 57 | -9 row 17 : 17 | cd leganes | 42 | 47 | 10 | 17 | 15 | 36 | 44 | -8 row 18 : 18 | sd eibar | 42 | 47 | 13 | 8 | 21 | 42 | 56 | -14 row 19 : 19 | mallorca b | 42 | 46 | 12 | 10 | 20 | 52 | 64 | -12 row 20 : 20 | barcelona b | 42 | 44 | 13 | 5 | 24 | 51 | 68 | -17 row 21 : 21 | hercules cf | 42 | 40 | 10 | 10 | 22 | 38 | 66 | -28 row 22 : 22 | cd ourense | 42 | 27 | 7 | 6 | 29 | 35 | 82 | -47 | col : count ( "club" ) row 1 : 1 | select count ( club ) where position = 7 <table_name> : table \begin{tabular}{lllllllllll}
\toprule
& position & club & played & points & wins & draws & losses & goals for & goals against & goal difference \\
\midrule
0 & 1 & malaga cf & 42 & 79 & 22 & 13 & 7 & 72 & 47 & 25 \\
1 & 2 & atletico de madrid b 1 & 42 & 74 & 21 & 11 & 10 & 73 & 51 & 22 \\
2 & 3 & cd numancia & 42 & 73 & 21 & 10 & 11 & 68 & 40 & 28 \\
3 & 4 & sevilla fc & 42 & 71 & 20 & 11 & 11 & 66 & 50 & 16 \\
4 & 5 & rayo vallecano & 42 & 71 & 19 & 14 & 9 & 64 & 49 & 15 \\
5 & 6 & ud las palmas & 42 & 68 & 17 & 17 & 8 & 57 & 38 & 19 \\
6 & 7 & cd toledo & 42 & 65 & 18 & 11 & 13 & 54 & 49 & 5 \\
7 & 8 & sd compostela & 42 & 61 & 16 & 13 & 13 & 60 & 53 & 7 \\
8 & 9 & sporting de gijon & 42 & 59 & 16 & 11 & 15 & 47 & 47 & 0 \\
9 & 10 & cp merida & 42 & 59 & 15 & 14 & 13 & 48 & 41 & 7 \\
10 & 11 & ue lleida & 42 & 59 & 15 & 14 & 13 & 52 & 50 & 2 \\
11 & 12 & recreativo de huelva & 42 & 58 & 14 & 16 & 12 & 40 & 35 & 5 \\
12 & 13 & ca osasuna & 42 & 57 & 15 & 12 & 15 & 44 & 51 & -7 \\
13 & 14 & cd badajoz & 42 & 51 & 12 & 15 & 15 & 35 & 39 & -4 \\
14 & 15 & albacete & 42 & 50 & 12 & 14 & 16 & 38 & 43 & -5 \\
15 & 16 & cd logrones & 42 & 48 & 12 & 12 & 18 & 48 & 57 & -9 \\
16 & 17 & cd leganes & 42 & 47 & 10 & 17 & 15 & 36 & 44 & -8 \\
17 & 18 & sd eibar & 42 & 47 & 13 & 8 & 21 & 42 & 56 & -14 \\
18 & 19 & mallorca b & 42 & 46 & 12 & 10 & 20 & 52 & 64 & -12 \\
19 & 20 & barcelona b & 42 & 44 & 13 & 5 & 24 & 51 & 68 & -17 \\
20 & 21 & hercules cf & 42 & 40 & 10 & 10 & 22 & 38 & 66 & -28 \\
21 & 22 & cd ourense & 42 & 27 & 7 & 6 & 29 & 35 & 82 & -47 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "club" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( club ) where position = 7 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>position</th>
<th>club</th>
<th>played</th>
<th>points</th>
<th>wins</th>
<th>draws</th>
<th>losses</th>
<th>goals for</th>
<th>goals against</th>
<th>goal difference</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>malaga cf</td>
<td>42</td>
<td>79</td>
<td>22</td>
<td>13</td>
<td>7</td>
<td>72</td>
<td>47</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>atletico de madrid b 1</td>
<td>42</td>
<td>74</td>
<td>21</td>
<td>11</td>
<td>10</td>
<td>73</td>
<td>51</td>
<td>22</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>cd numancia</td>
<td>42</td>
<td>73</td>
<td>21</td>
<td>10</td>
<td>11</td>
<td>68</td>
<td>40</td>
<td>28</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>sevilla fc</td>
<td>42</td>
<td>71</td>
<td>20</td>
<td>11</td>
<td>11</td>
<td>66</td>
<td>50</td>
<td>16</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>rayo vallecano</td>
<td>42</td>
<td>71</td>
<td>19</td>
<td>14</td>
<td>9</td>
<td>64</td>
<td>49</td>
<td>15</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>ud las palmas</td>
<td>42</td>
<td>68</td>
<td>17</td>
<td>17</td>
<td>8</td>
<td>57</td>
<td>38</td>
<td>19</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>cd toledo</td>
<td>42</td>
<td>65</td>
<td>18</td>
<td>11</td>
<td>13</td>
<td>54</td>
<td>49</td>
<td>5</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>sd compostela</td>
<td>42</td>
<td>61</td>
<td>16</td>
<td>13</td>
<td>13</td>
<td>60</td>
<td>53</td>
<td>7</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>sporting de gijon</td>
<td>42</td>
<td>59</td>
<td>16</td>
<td>11</td>
<td>15</td>
<td>47</td>
<td>47</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>cp merida</td>
<td>42</td>
<td>59</td>
<td>15</td>
<td>14</td>
<td>13</td>
<td>48</td>
<td>41</td>
<td>7</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>ue lleida</td>
<td>42</td>
<td>59</td>
<td>15</td>
<td>14</td>
<td>13</td>
<td>52</td>
<td>50</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>recreativo de huelva</td>
<td>42</td>
<td>58</td>
<td>14</td>
<td>16</td>
<td>12</td>
<td>40</td>
<td>35</td>
<td>5</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>ca osasuna</td>
<td>42</td>
<td>57</td>
<td>15</td>
<td>12</td>
<td>15</td>
<td>44</td>
<td>51</td>
<td>-7</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>cd badajoz</td>
<td>42</td>
<td>51</td>
<td>12</td>
<td>15</td>
<td>15</td>
<td>35</td>
<td>39</td>
<td>-4</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>albacete</td>
<td>42</td>
<td>50</td>
<td>12</td>
<td>14</td>
<td>16</td>
<td>38</td>
<td>43</td>
<td>-5</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>cd logrones</td>
<td>42</td>
<td>48</td>
<td>12</td>
<td>12</td>
<td>18</td>
<td>48</td>
<td>57</td>
<td>-9</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>cd leganes</td>
<td>42</td>
<td>47</td>
<td>10</td>
<td>17</td>
<td>15</td>
<td>36</td>
<td>44</td>
<td>-8</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>sd eibar</td>
<td>42</td>
<td>47</td>
<td>13</td>
<td>8</td>
<td>21</td>
<td>42</td>
<td>56</td>
<td>-14</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>mallorca b</td>
<td>42</td>
<td>46</td>
<td>12</td>
<td>10</td>
<td>20</td>
<td>52</td>
<td>64</td>
<td>-12</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>barcelona b</td>
<td>42</td>
<td>44</td>
<td>13</td>
<td>5</td>
<td>24</td>
<td>51</td>
<td>68</td>
<td>-17</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>hercules cf</td>
<td>42</td>
<td>40</td>
<td>10</td>
<td>10</td>
<td>22</td>
<td>38</td>
<td>66</td>
<td>-28</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>cd ourense</td>
<td>42</td>
<td>27</td>
<td>7</td>
<td>6</td>
<td>29</td>
<td>35</td>
<td>82</td>
<td>-47</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "club" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( club ) where position = 7 <table_name> : table | | position | club | played | points | wins | draws | losses | goals for | goals against | goal difference |
|---:|-----------:|:-----------------------|---------:|---------:|-------:|--------:|---------:|------------:|----------------:|------------------:|
| 0 | 1 | malaga cf | 42 | 79 | 22 | 13 | 7 | 72 | 47 | 25 |
| 1 | 2 | atletico de madrid b 1 | 42 | 74 | 21 | 11 | 10 | 73 | 51 | 22 |
| 2 | 3 | cd numancia | 42 | 73 | 21 | 10 | 11 | 68 | 40 | 28 |
| 3 | 4 | sevilla fc | 42 | 71 | 20 | 11 | 11 | 66 | 50 | 16 |
| 4 | 5 | rayo vallecano | 42 | 71 | 19 | 14 | 9 | 64 | 49 | 15 |
| 5 | 6 | ud las palmas | 42 | 68 | 17 | 17 | 8 | 57 | 38 | 19 |
| 6 | 7 | cd toledo | 42 | 65 | 18 | 11 | 13 | 54 | 49 | 5 |
| 7 | 8 | sd compostela | 42 | 61 | 16 | 13 | 13 | 60 | 53 | 7 |
| 8 | 9 | sporting de gijon | 42 | 59 | 16 | 11 | 15 | 47 | 47 | 0 |
| 9 | 10 | cp merida | 42 | 59 | 15 | 14 | 13 | 48 | 41 | 7 |
| 10 | 11 | ue lleida | 42 | 59 | 15 | 14 | 13 | 52 | 50 | 2 |
| 11 | 12 | recreativo de huelva | 42 | 58 | 14 | 16 | 12 | 40 | 35 | 5 |
| 12 | 13 | ca osasuna | 42 | 57 | 15 | 12 | 15 | 44 | 51 | -7 |
| 13 | 14 | cd badajoz | 42 | 51 | 12 | 15 | 15 | 35 | 39 | -4 |
| 14 | 15 | albacete | 42 | 50 | 12 | 14 | 16 | 38 | 43 | -5 |
| 15 | 16 | cd logrones | 42 | 48 | 12 | 12 | 18 | 48 | 57 | -9 |
| 16 | 17 | cd leganes | 42 | 47 | 10 | 17 | 15 | 36 | 44 | -8 |
| 17 | 18 | sd eibar | 42 | 47 | 13 | 8 | 21 | 42 | 56 | -14 |
| 18 | 19 | mallorca b | 42 | 46 | 12 | 10 | 20 | 52 | 64 | -12 |
| 19 | 20 | barcelona b | 42 | 44 | 13 | 5 | 24 | 51 | 68 | -17 |
| 20 | 21 | hercules cf | 42 | 40 | 10 | 10 | 22 | 38 | 66 | -28 |
| 21 | 22 | cd ourense | 42 | 27 | 7 | 6 | 29 | 35 | 82 | -47 | | | | count ( "club" ) |
|---:|-------------------:|
| 0 | 1 | | [
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select draw where artist = 'rolf junior' col : draw | country | language | artist | song | english translation | national final | place | points row 1 : 1 | malta | english | claudia faniello | "caravaggio" | none | 2nd | 13 | 53 row 2 : 2 | israel | hebrew | bo'az ma'uda & oshrat papin | "parparim" | butterflies | 3rd | 8 | 90 row 3 : 3 | russia | english | sergey lazarev | "flyer" | none | 4th | 7 | 119 row 4 : 4 | estonia | english | rolf junior | "one on one" | none | 4th | 21 | 0 row 5 : 5 | belgium | english | sandrine | "i feel the same way" | none | 2nd | 10 | 64 row 6 : 6 | macedonia | macedonian | risto samardziev | "dojdi do mene" | come to me | 3rd | 19 | 7 row 7 : 7 | poland | english | man meadow | "viva la musica" | hail to the music | 3rd | 3 | 155 row 8 : 8 | finland | finnish | mikael konttinen | "milloin" | when | none | 14 | 46 row 9 : 9 | germany | german | carolin fortenbacher | "hinterm ozean" | beyond the ocean | 2nd | 6 | 129 row 10 : 10 | denmark | english | kendra lou | "until we're satisfied" | none | 4th | 18 | 21 row 11 : 11 | greece | english | kostas martakis | "always and forever" | none | 2nd | 4 | 140 row 12 : 12 | serbia | serbian | beauty queens | "zavet" | a pledge | 3rd | 9 | 68 row 13 : 13 | croatia | croatian | emilija kokic | "andjeo" | angel | 6th | 15 | 31 row 14 : 14 | lithuania | english | aiste pilvelyte | "troy on fire" | none | 2nd | 17 | 26 row 15 : 15 | ireland | english | leona daly | "not crazy after all" | none | none | 12 | 56 row 16 : 16 | united kingdom | english | the revelations | "it's you" | none | 3rd | 16 | 29 row 17 : 17 | portugal | portuguese | lisboa nao sejas francesa | "porto de encontro" | meeting harbour | 9th | 20 | 6 row 18 : 18 | sweden | english | sanna nielsen | "empty room" | none | 2nd | 1 | 269 row 19 : 19 | norway | english | veronica akselsen | "am i supposed to love again" | none | 4th | 5 | 139 row 20 : 20 | slovenia | slovene | brigita suler | "samara" | none | 3rd | 11 | 57 row 21 : 21 | spain | spanish | coral | "todo esta en tu mente" | everything is in your mind | 2nd | 2 | 178 | col : draw row 1 : 4 | select draw where artist = 'rolf junior' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& draw & country & language & artist & song & english translation & national final & place & points \\
\midrule
0 & 1 & malta & english & claudia faniello & "caravaggio" & none & 2nd & 13 & 53 \\
1 & 2 & israel & hebrew & bo'az ma'uda & oshrat papin & "parparim" & butterflies & 3rd & 8 & 90 \\
2 & 3 & russia & english & sergey lazarev & "flyer" & none & 4th & 7 & 119 \\
3 & 4 & estonia & english & rolf junior & "one on one" & none & 4th & 21 & 0 \\
4 & 5 & belgium & english & sandrine & "i feel the same way" & none & 2nd & 10 & 64 \\
5 & 6 & macedonia & macedonian & risto samardziev & "dojdi do mene" & come to me & 3rd & 19 & 7 \\
6 & 7 & poland & english & man meadow & "viva la musica" & hail to the music & 3rd & 3 & 155 \\
7 & 8 & finland & finnish & mikael konttinen & "milloin" & when & none & 14 & 46 \\
8 & 9 & germany & german & carolin fortenbacher & "hinterm ozean" & beyond the ocean & 2nd & 6 & 129 \\
9 & 10 & denmark & english & kendra lou & "until we're satisfied" & none & 4th & 18 & 21 \\
10 & 11 & greece & english & kostas martakis & "always and forever" & none & 2nd & 4 & 140 \\
11 & 12 & serbia & serbian & beauty queens & "zavet" & a pledge & 3rd & 9 & 68 \\
12 & 13 & croatia & croatian & emilija kokic & "andjeo" & angel & 6th & 15 & 31 \\
13 & 14 & lithuania & english & aiste pilvelyte & "troy on fire" & none & 2nd & 17 & 26 \\
14 & 15 & ireland & english & leona daly & "not crazy after all" & none & none & 12 & 56 \\
15 & 16 & united kingdom & english & the revelations & "it's you" & none & 3rd & 16 & 29 \\
16 & 17 & portugal & portuguese & lisboa nao sejas francesa & "porto de encontro" & meeting harbour & 9th & 20 & 6 \\
17 & 18 & sweden & english & sanna nielsen & "empty room" & none & 2nd & 1 & 269 \\
18 & 19 & norway & english & veronica akselsen & "am i supposed to love again" & none & 4th & 5 & 139 \\
19 & 20 & slovenia & slovene & brigita suler & "samara" & none & 3rd & 11 & 57 \\
20 & 21 & spain & spanish & coral & "todo esta en tu mente" & everything is in your mind & 2nd & 2 & 178 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& draw \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select draw where artist = 'rolf junior' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>draw</th>
<th>country</th>
<th>language</th>
<th>artist</th>
<th>song</th>
<th>english translation</th>
<th>national final</th>
<th>place</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>malta</td>
<td>english</td>
<td>claudia faniello</td>
<td>"caravaggio"</td>
<td>none</td>
<td>2nd</td>
<td>13</td>
<td>53</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>israel</td>
<td>hebrew</td>
<td>bo'az ma'uda & oshrat papin</td>
<td>"parparim"</td>
<td>butterflies</td>
<td>3rd</td>
<td>8</td>
<td>90</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>russia</td>
<td>english</td>
<td>sergey lazarev</td>
<td>"flyer"</td>
<td>none</td>
<td>4th</td>
<td>7</td>
<td>119</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>estonia</td>
<td>english</td>
<td>rolf junior</td>
<td>"one on one"</td>
<td>none</td>
<td>4th</td>
<td>21</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>belgium</td>
<td>english</td>
<td>sandrine</td>
<td>"i feel the same way"</td>
<td>none</td>
<td>2nd</td>
<td>10</td>
<td>64</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>macedonia</td>
<td>macedonian</td>
<td>risto samardziev</td>
<td>"dojdi do mene"</td>
<td>come to me</td>
<td>3rd</td>
<td>19</td>
<td>7</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>poland</td>
<td>english</td>
<td>man meadow</td>
<td>"viva la musica"</td>
<td>hail to the music</td>
<td>3rd</td>
<td>3</td>
<td>155</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>finland</td>
<td>finnish</td>
<td>mikael konttinen</td>
<td>"milloin"</td>
<td>when</td>
<td>none</td>
<td>14</td>
<td>46</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>germany</td>
<td>german</td>
<td>carolin fortenbacher</td>
<td>"hinterm ozean"</td>
<td>beyond the ocean</td>
<td>2nd</td>
<td>6</td>
<td>129</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>denmark</td>
<td>english</td>
<td>kendra lou</td>
<td>"until we're satisfied"</td>
<td>none</td>
<td>4th</td>
<td>18</td>
<td>21</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>greece</td>
<td>english</td>
<td>kostas martakis</td>
<td>"always and forever"</td>
<td>none</td>
<td>2nd</td>
<td>4</td>
<td>140</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>serbia</td>
<td>serbian</td>
<td>beauty queens</td>
<td>"zavet"</td>
<td>a pledge</td>
<td>3rd</td>
<td>9</td>
<td>68</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>croatia</td>
<td>croatian</td>
<td>emilija kokic</td>
<td>"andjeo"</td>
<td>angel</td>
<td>6th</td>
<td>15</td>
<td>31</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>lithuania</td>
<td>english</td>
<td>aiste pilvelyte</td>
<td>"troy on fire"</td>
<td>none</td>
<td>2nd</td>
<td>17</td>
<td>26</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>ireland</td>
<td>english</td>
<td>leona daly</td>
<td>"not crazy after all"</td>
<td>none</td>
<td>none</td>
<td>12</td>
<td>56</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>united kingdom</td>
<td>english</td>
<td>the revelations</td>
<td>"it's you"</td>
<td>none</td>
<td>3rd</td>
<td>16</td>
<td>29</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>portugal</td>
<td>portuguese</td>
<td>lisboa nao sejas francesa</td>
<td>"porto de encontro"</td>
<td>meeting harbour</td>
<td>9th</td>
<td>20</td>
<td>6</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>sweden</td>
<td>english</td>
<td>sanna nielsen</td>
<td>"empty room"</td>
<td>none</td>
<td>2nd</td>
<td>1</td>
<td>269</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>norway</td>
<td>english</td>
<td>veronica akselsen</td>
<td>"am i supposed to love again"</td>
<td>none</td>
<td>4th</td>
<td>5</td>
<td>139</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>slovenia</td>
<td>slovene</td>
<td>brigita suler</td>
<td>"samara"</td>
<td>none</td>
<td>3rd</td>
<td>11</td>
<td>57</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>spain</td>
<td>spanish</td>
<td>coral</td>
<td>"todo esta en tu mente"</td>
<td>everything is in your mind</td>
<td>2nd</td>
<td>2</td>
<td>178</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>draw</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select draw where artist = 'rolf junior' <table_name> : table | | draw | country | language | artist | song | english translation | national final | place | points |
|---:|-------:|:---------------|:-----------|:----------------------------|:------------------------------|:---------------------------|:-----------------|--------:|---------:|
| 0 | 1 | malta | english | claudia faniello | "caravaggio" | none | 2nd | 13 | 53 |
| 1 | 2 | israel | hebrew | bo'az ma'uda & oshrat papin | "parparim" | butterflies | 3rd | 8 | 90 |
| 2 | 3 | russia | english | sergey lazarev | "flyer" | none | 4th | 7 | 119 |
| 3 | 4 | estonia | english | rolf junior | "one on one" | none | 4th | 21 | 0 |
| 4 | 5 | belgium | english | sandrine | "i feel the same way" | none | 2nd | 10 | 64 |
| 5 | 6 | macedonia | macedonian | risto samardziev | "dojdi do mene" | come to me | 3rd | 19 | 7 |
| 6 | 7 | poland | english | man meadow | "viva la musica" | hail to the music | 3rd | 3 | 155 |
| 7 | 8 | finland | finnish | mikael konttinen | "milloin" | when | none | 14 | 46 |
| 8 | 9 | germany | german | carolin fortenbacher | "hinterm ozean" | beyond the ocean | 2nd | 6 | 129 |
| 9 | 10 | denmark | english | kendra lou | "until we're satisfied" | none | 4th | 18 | 21 |
| 10 | 11 | greece | english | kostas martakis | "always and forever" | none | 2nd | 4 | 140 |
| 11 | 12 | serbia | serbian | beauty queens | "zavet" | a pledge | 3rd | 9 | 68 |
| 12 | 13 | croatia | croatian | emilija kokic | "andjeo" | angel | 6th | 15 | 31 |
| 13 | 14 | lithuania | english | aiste pilvelyte | "troy on fire" | none | 2nd | 17 | 26 |
| 14 | 15 | ireland | english | leona daly | "not crazy after all" | none | none | 12 | 56 |
| 15 | 16 | united kingdom | english | the revelations | "it's you" | none | 3rd | 16 | 29 |
| 16 | 17 | portugal | portuguese | lisboa nao sejas francesa | "porto de encontro" | meeting harbour | 9th | 20 | 6 |
| 17 | 18 | sweden | english | sanna nielsen | "empty room" | none | 2nd | 1 | 269 |
| 18 | 19 | norway | english | veronica akselsen | "am i supposed to love again" | none | 4th | 5 | 139 |
| 19 | 20 | slovenia | slovene | brigita suler | "samara" | none | 3rd | 11 | 57 |
| 20 | 21 | spain | spanish | coral | "todo esta en tu mente" | everything is in your mind | 2nd | 2 | 178 | | | | draw |
|---:|-------:|
| 0 | 4 | | [
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select # where result = '3-0' col : # | date | venue | opponent | score | result | competition row 1 : 1 | 1999-03-27 00:00:00 | mestalla, valencia, spain | austria | 3-0 | 9-0 | euro 2000 qualifying row 2 : 2 | 1999-03-27 00:00:00 | mestalla, valencia, spain | austria | 5-0 | 9-0 | euro 2000 qualifying row 3 : 3 | 1999-03-31 00:00:00 | olimpico, serravalle, san marino | san marino | 0-3 | 0-6 | euro 2000 qualifying row 4 : 4 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 1-0 | 8-0 | euro 2000 qualifying row 5 : 5 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 2-0 | 8-0 | euro 2000 qualifying row 6 : 6 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 4-0 | 8-0 | euro 2000 qualifying row 7 : 7 | 2000-01-26 00:00:00 | cartagonova, cartagena, spain | poland | 2-0 | 3-0 | friendly row 8 : 8 | 2000-01-26 00:00:00 | cartagonova, cartagena, spain | poland | 3-0 | 3-0 | friendly | col : # row 1 : 7 row 2 : 8 | select # where result = '3-0' <table_name> : table \begin{tabular}{llllllll}
\toprule
& # & date & venue & opponent & score & result & competition \\
\midrule
0 & 1 & 1999-03-27 00:00:00 & mestalla, valencia, spain & austria & 3-0 & 9-0 & euro 2000 qualifying \\
1 & 2 & 1999-03-27 00:00:00 & mestalla, valencia, spain & austria & 5-0 & 9-0 & euro 2000 qualifying \\
2 & 3 & 1999-03-31 00:00:00 & olimpico, serravalle, san marino & san marino & 0-3 & 0-6 & euro 2000 qualifying \\
3 & 4 & 1999-09-08 00:00:00 & vivero, badajoz, spain & cyprus & 1-0 & 8-0 & euro 2000 qualifying \\
4 & 5 & 1999-09-08 00:00:00 & vivero, badajoz, spain & cyprus & 2-0 & 8-0 & euro 2000 qualifying \\
5 & 6 & 1999-09-08 00:00:00 & vivero, badajoz, spain & cyprus & 4-0 & 8-0 & euro 2000 qualifying \\
6 & 7 & 2000-01-26 00:00:00 & cartagonova, cartagena, spain & poland & 2-0 & 3-0 & friendly \\
7 & 8 & 2000-01-26 00:00:00 & cartagonova, cartagena, spain & poland & 3-0 & 3-0 & friendly \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& # \\
\midrule
0 & 7 \\
1 & 8 \\
\bottomrule
\end{tabular}
| select # where result = '3-0' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>date</th>
<th>venue</th>
<th>opponent</th>
<th>score</th>
<th>result</th>
<th>competition</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1999-03-27 00:00:00</td>
<td>mestalla, valencia, spain</td>
<td>austria</td>
<td>3-0</td>
<td>9-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1999-03-27 00:00:00</td>
<td>mestalla, valencia, spain</td>
<td>austria</td>
<td>5-0</td>
<td>9-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1999-03-31 00:00:00</td>
<td>olimpico, serravalle, san marino</td>
<td>san marino</td>
<td>0-3</td>
<td>0-6</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1999-09-08 00:00:00</td>
<td>vivero, badajoz, spain</td>
<td>cyprus</td>
<td>1-0</td>
<td>8-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1999-09-08 00:00:00</td>
<td>vivero, badajoz, spain</td>
<td>cyprus</td>
<td>2-0</td>
<td>8-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>1999-09-08 00:00:00</td>
<td>vivero, badajoz, spain</td>
<td>cyprus</td>
<td>4-0</td>
<td>8-0</td>
<td>euro 2000 qualifying</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2000-01-26 00:00:00</td>
<td>cartagonova, cartagena, spain</td>
<td>poland</td>
<td>2-0</td>
<td>3-0</td>
<td>friendly</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2000-01-26 00:00:00</td>
<td>cartagonova, cartagena, spain</td>
<td>poland</td>
<td>3-0</td>
<td>3-0</td>
<td>friendly</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
<tr>
<th>1</th>
<td>8</td>
</tr>
</tbody>
</table> | select # where result = '3-0' <table_name> : table | | # | date | venue | opponent | score | result | competition |
|---:|----:|:--------------------|:---------------------------------|:-----------|:--------|:---------|:---------------------|
| 0 | 1 | 1999-03-27 00:00:00 | mestalla, valencia, spain | austria | 3-0 | 9-0 | euro 2000 qualifying |
| 1 | 2 | 1999-03-27 00:00:00 | mestalla, valencia, spain | austria | 5-0 | 9-0 | euro 2000 qualifying |
| 2 | 3 | 1999-03-31 00:00:00 | olimpico, serravalle, san marino | san marino | 0-3 | 0-6 | euro 2000 qualifying |
| 3 | 4 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 1-0 | 8-0 | euro 2000 qualifying |
| 4 | 5 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 2-0 | 8-0 | euro 2000 qualifying |
| 5 | 6 | 1999-09-08 00:00:00 | vivero, badajoz, spain | cyprus | 4-0 | 8-0 | euro 2000 qualifying |
| 6 | 7 | 2000-01-26 00:00:00 | cartagonova, cartagena, spain | poland | 2-0 | 3-0 | friendly |
| 7 | 8 | 2000-01-26 00:00:00 | cartagonova, cartagena, spain | poland | 3-0 | 3-0 | friendly | | | | # |
|---:|----:|
| 0 | 7 |
| 1 | 8 | | [
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select driver where driver = 'neel jani' col : pos | no | driver | team | laps | time/retired | grid | points row 1 : 1 | 14 | robert doornbos | minardi team usa | 107 | 1:45:07.617 | 15 | 31 row 2 : 2 | 21 | neel jani | pkv racing | 107 | +6.1 secs | 5 | 27 row 3 : 3 | 3 | oriol servia | forsythe racing | 107 | +6.9 secs | 4 | 26 row 4 : 4 | 5 | will power | team australia | 107 | +7.5 secs | 12 | 23 row 5 : 5 | 1 | sebastien bourdais | n/h/l racing | 107 | +8.0 secs | 2 | 21 row 6 : 6 | 2 | graham rahal | n/h/l racing | 107 | +9.6 secs | 6 | 19 row 7 : 7 | 19 | bruno junqueira | dale coyne racing | 107 | +14.0 secs | 10 | 17 row 8 : 8 | 22 | tristan gommendy | pkv racing | 107 | +19.2 secs | 8 | 15 row 9 : 9 | 42 | jan heylen | conquest racing | 107 | +28.5 secs | 13 | 13 row 10 : 10 | 15 | simon pagenaud | team australia | 107 | +48.4 secs | 9 | 11 row 11 : 11 | 3 | paul tracy | forsythe championship racing | 105 | + 2 laps | 11 | 10 row 12 : 12 | 28 | mario dominguez | pacific coast motorsports | 104 | + 3 laps | 14 | 12 row 13 : 13 | 22 | justin wilson | rsports | 87 | + 20 laps | 1 | 8 row 14 : 14 | 29 | alex figge | pacific coast motorsports | 34 | contact | 0 | 7 row 15 : 15 | 11 | alex tagliani | rsports | 83 | mechanical | 8 | 6 row 16 : 16 | 11 | katherine legge | dale coyne racing | 13 | contact | 16 | 5 row 17 : 17 | 4 | dan clarke | minardi team usa | 3 | contact | 3 | 4 | col : driver row 1 : neel jani | select driver where driver = 'neel jani' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & team & laps & time/retired & grid & points \\
\midrule
0 & 1 & 14 & robert doornbos & minardi team usa & 107 & 1:45:07.617 & 15 & 31 \\
1 & 2 & 21 & neel jani & pkv racing & 107 & +6.1 secs & 5 & 27 \\
2 & 3 & 3 & oriol servia & forsythe racing & 107 & +6.9 secs & 4 & 26 \\
3 & 4 & 5 & will power & team australia & 107 & +7.5 secs & 12 & 23 \\
4 & 5 & 1 & sebastien bourdais & n/h/l racing & 107 & +8.0 secs & 2 & 21 \\
5 & 6 & 2 & graham rahal & n/h/l racing & 107 & +9.6 secs & 6 & 19 \\
6 & 7 & 19 & bruno junqueira & dale coyne racing & 107 & +14.0 secs & 10 & 17 \\
7 & 8 & 22 & tristan gommendy & pkv racing & 107 & +19.2 secs & 8 & 15 \\
8 & 9 & 42 & jan heylen & conquest racing & 107 & +28.5 secs & 13 & 13 \\
9 & 10 & 15 & simon pagenaud & team australia & 107 & +48.4 secs & 9 & 11 \\
10 & 11 & 3 & paul tracy & forsythe championship racing & 105 & + 2 laps & 11 & 10 \\
11 & 12 & 28 & mario dominguez & pacific coast motorsports & 104 & + 3 laps & 14 & 12 \\
12 & 13 & 22 & justin wilson & rsports & 87 & + 20 laps & 1 & 8 \\
13 & 14 & 29 & alex figge & pacific coast motorsports & 34 & contact & 0 & 7 \\
14 & 15 & 11 & alex tagliani & rsports & 83 & mechanical & 8 & 6 \\
15 & 16 & 11 & katherine legge & dale coyne racing & 13 & contact & 16 & 5 \\
16 & 17 & 4 & dan clarke & minardi team usa & 3 & contact & 3 & 4 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& driver \\
\midrule
0 & neel jani \\
\bottomrule
\end{tabular}
| select driver where driver = 'neel jani' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>no</th>
<th>driver</th>
<th>team</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>14</td>
<td>robert doornbos</td>
<td>minardi team usa</td>
<td>107</td>
<td>1:45:07.617</td>
<td>15</td>
<td>31</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>21</td>
<td>neel jani</td>
<td>pkv racing</td>
<td>107</td>
<td>+6.1 secs</td>
<td>5</td>
<td>27</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>3</td>
<td>oriol servia</td>
<td>forsythe racing</td>
<td>107</td>
<td>+6.9 secs</td>
<td>4</td>
<td>26</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>5</td>
<td>will power</td>
<td>team australia</td>
<td>107</td>
<td>+7.5 secs</td>
<td>12</td>
<td>23</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1</td>
<td>sebastien bourdais</td>
<td>n/h/l racing</td>
<td>107</td>
<td>+8.0 secs</td>
<td>2</td>
<td>21</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2</td>
<td>graham rahal</td>
<td>n/h/l racing</td>
<td>107</td>
<td>+9.6 secs</td>
<td>6</td>
<td>19</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>19</td>
<td>bruno junqueira</td>
<td>dale coyne racing</td>
<td>107</td>
<td>+14.0 secs</td>
<td>10</td>
<td>17</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>22</td>
<td>tristan gommendy</td>
<td>pkv racing</td>
<td>107</td>
<td>+19.2 secs</td>
<td>8</td>
<td>15</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>42</td>
<td>jan heylen</td>
<td>conquest racing</td>
<td>107</td>
<td>+28.5 secs</td>
<td>13</td>
<td>13</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>15</td>
<td>simon pagenaud</td>
<td>team australia</td>
<td>107</td>
<td>+48.4 secs</td>
<td>9</td>
<td>11</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>3</td>
<td>paul tracy</td>
<td>forsythe championship racing</td>
<td>105</td>
<td>+ 2 laps</td>
<td>11</td>
<td>10</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>28</td>
<td>mario dominguez</td>
<td>pacific coast motorsports</td>
<td>104</td>
<td>+ 3 laps</td>
<td>14</td>
<td>12</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>22</td>
<td>justin wilson</td>
<td>rsports</td>
<td>87</td>
<td>+ 20 laps</td>
<td>1</td>
<td>8</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>29</td>
<td>alex figge</td>
<td>pacific coast motorsports</td>
<td>34</td>
<td>contact</td>
<td>0</td>
<td>7</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>11</td>
<td>alex tagliani</td>
<td>rsports</td>
<td>83</td>
<td>mechanical</td>
<td>8</td>
<td>6</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>11</td>
<td>katherine legge</td>
<td>dale coyne racing</td>
<td>13</td>
<td>contact</td>
<td>16</td>
<td>5</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>4</td>
<td>dan clarke</td>
<td>minardi team usa</td>
<td>3</td>
<td>contact</td>
<td>3</td>
<td>4</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>driver</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>neel jani</td>
</tr>
</tbody>
</table> | select driver where driver = 'neel jani' <table_name> : table | | pos | no | driver | team | laps | time/retired | grid | points |
|---:|------:|-----:|:-------------------|:-----------------------------|-------:|:---------------|-------:|---------:|
| 0 | 1 | 14 | robert doornbos | minardi team usa | 107 | 1:45:07.617 | 15 | 31 |
| 1 | 2 | 21 | neel jani | pkv racing | 107 | +6.1 secs | 5 | 27 |
| 2 | 3 | 3 | oriol servia | forsythe racing | 107 | +6.9 secs | 4 | 26 |
| 3 | 4 | 5 | will power | team australia | 107 | +7.5 secs | 12 | 23 |
| 4 | 5 | 1 | sebastien bourdais | n/h/l racing | 107 | +8.0 secs | 2 | 21 |
| 5 | 6 | 2 | graham rahal | n/h/l racing | 107 | +9.6 secs | 6 | 19 |
| 6 | 7 | 19 | bruno junqueira | dale coyne racing | 107 | +14.0 secs | 10 | 17 |
| 7 | 8 | 22 | tristan gommendy | pkv racing | 107 | +19.2 secs | 8 | 15 |
| 8 | 9 | 42 | jan heylen | conquest racing | 107 | +28.5 secs | 13 | 13 |
| 9 | 10 | 15 | simon pagenaud | team australia | 107 | +48.4 secs | 9 | 11 |
| 10 | 11 | 3 | paul tracy | forsythe championship racing | 105 | + 2 laps | 11 | 10 |
| 11 | 12 | 28 | mario dominguez | pacific coast motorsports | 104 | + 3 laps | 14 | 12 |
| 12 | 13 | 22 | justin wilson | rsports | 87 | + 20 laps | 1 | 8 |
| 13 | 14 | 29 | alex figge | pacific coast motorsports | 34 | contact | 0 | 7 |
| 14 | 15 | 11 | alex tagliani | rsports | 83 | mechanical | 8 | 6 |
| 15 | 16 | 11 | katherine legge | dale coyne racing | 13 | contact | 16 | 5 |
| 16 | 17 | 4 | dan clarke | minardi team usa | 3 | contact | 3 | 4 | | | | driver |
|---:|:----------|
| 0 | neel jani | | [
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select count ( * ) where locomotive < 266 col : locomotive | name | serial no | entered service | livery row 1 : 9001 | ernest henry | 1373/918266-3 | may 94 | freightcorp row 2 : 9002 | michael wendon | 1374/918266-2 | may 94 | freightcorp row 3 : 9003 | matthew ryan | 1375/918266-1 | aug 94 | freightcorp row 4 : 9004 | kevin nichols | 1376/918266-4 | may 94 | freightcorp row 5 : 9005 | kevin barry | 1377/918266-5 | may 94 | freightcorp row 6 : 9006 | murray rose | 1378/918266-6 | may 94 | freightcorp row 7 : 9007 | dunc gray | 1379/918266-7 | may 94 | freightcorp row 8 : 9008 | ralph doubell | 1380/918266-8 | aug 94 | freightcorp row 9 : 9009 | lionel cox | 1381/918266-9 | jul 94 | freightcorp row 10 : 9010 | john devitt | 1382/918266-10 | jul 94 | freightcorp row 11 : 9011 | kevan gosper | 1383/918266-11 | jul 94 | freightcorp row 12 : 9012 | neil brooks/peter evans/ mark kerry/mark tonelli | 1384/918266-12 | jun 94 | freightcorp row 13 : 9013 | michael diamond | 1385/918266-13 | jun 94 | freightcorp row 14 : 9014 | peter antonie/stephen hawkins | 1386/918266-14 | jul 94 | freightcorp row 15 : 9015 | duncan armstrong | 1387/918266-15 | jul 94 | freightcorp row 16 : 9016 | herb elliott | 1388/918266-16 | jul 94 | freightcorp row 17 : 9017 | andrew cooper/nicholas green/ michael mckay/james tomkins | 1389/918266-17 | jun 94 | freightcorp row 18 : 9018 | john konrads | 1390/918266-18 | jul 94 | freightcorp row 19 : 9019 | dean lukin | 1391/918266-19 | jul 94 | freightcorp row 20 : 9020 | russell mark | 1392/918266-20 | jun 94 | freightcorp row 21 : 9021 | ian o'brien | 1393/918266-21 | aug 94 | freightcorp row 22 : 9022 | clint robinson | 1394/918266-22 | aug 94 | freightcorp row 23 : 9023 | robert windle | 1395/918266-23 | oct 94 | freightcorp row 24 : 9024 | john winter | 1396/918266-24 | aug 94 | freightcorp row 25 : 9025 | todd woodbridge/mark woodforde | 1397/918266-25 | aug 94 | freightcorp row 26 : 9026 | david theile | 1398/918266-26 | oct 94 | freightcorp row 27 : 9027 | none | 1399/918266-27 | aug 94 | freightcorp row 28 : 9028 | none | 1400/918266/28 | aug 94 | freightcorp row 29 : 9029 | none | 1401/918266/29 | aug 94 | freightcorp row 30 : 9030 | australian men's hockey team | 1402/918266-30 | aug 94 | freightcorp row 31 : 9031 | none | 1403/918266/31 | aug 94 | freightcorp row 32 : 9032 | none | 05-1692 | nov 05 | pacific national row 33 : 9033 | none | 05-1693 | nov 05 | pacific national row 34 : 9034 | none | 05-1694 | nov 05 | pacific national row 35 : 9035 | none | 05-1695 | nov 05 | pacific national | col : count ( "*" ) row 1 : 0 | select count ( * ) where locomotive < 266 <table_name> : table \begin{tabular}{llllll}
\toprule
& locomotive & name & serial no & entered service & livery \\
\midrule
0 & 9001 & ernest henry & 1373/918266-3 & may 94 & freightcorp \\
1 & 9002 & michael wendon & 1374/918266-2 & may 94 & freightcorp \\
2 & 9003 & matthew ryan & 1375/918266-1 & aug 94 & freightcorp \\
3 & 9004 & kevin nichols & 1376/918266-4 & may 94 & freightcorp \\
4 & 9005 & kevin barry & 1377/918266-5 & may 94 & freightcorp \\
5 & 9006 & murray rose & 1378/918266-6 & may 94 & freightcorp \\
6 & 9007 & dunc gray & 1379/918266-7 & may 94 & freightcorp \\
7 & 9008 & ralph doubell & 1380/918266-8 & aug 94 & freightcorp \\
8 & 9009 & lionel cox & 1381/918266-9 & jul 94 & freightcorp \\
9 & 9010 & john devitt & 1382/918266-10 & jul 94 & freightcorp \\
10 & 9011 & kevan gosper & 1383/918266-11 & jul 94 & freightcorp \\
11 & 9012 & neil brooks/peter evans/ mark kerry/mark tonelli & 1384/918266-12 & jun 94 & freightcorp \\
12 & 9013 & michael diamond & 1385/918266-13 & jun 94 & freightcorp \\
13 & 9014 & peter antonie/stephen hawkins & 1386/918266-14 & jul 94 & freightcorp \\
14 & 9015 & duncan armstrong & 1387/918266-15 & jul 94 & freightcorp \\
15 & 9016 & herb elliott & 1388/918266-16 & jul 94 & freightcorp \\
16 & 9017 & andrew cooper/nicholas green/ michael mckay/james tomkins & 1389/918266-17 & jun 94 & freightcorp \\
17 & 9018 & john konrads & 1390/918266-18 & jul 94 & freightcorp \\
18 & 9019 & dean lukin & 1391/918266-19 & jul 94 & freightcorp \\
19 & 9020 & russell mark & 1392/918266-20 & jun 94 & freightcorp \\
20 & 9021 & ian o'brien & 1393/918266-21 & aug 94 & freightcorp \\
21 & 9022 & clint robinson & 1394/918266-22 & aug 94 & freightcorp \\
22 & 9023 & robert windle & 1395/918266-23 & oct 94 & freightcorp \\
23 & 9024 & john winter & 1396/918266-24 & aug 94 & freightcorp \\
24 & 9025 & todd woodbridge/mark woodforde & 1397/918266-25 & aug 94 & freightcorp \\
25 & 9026 & david theile & 1398/918266-26 & oct 94 & freightcorp \\
26 & 9027 & none & 1399/918266-27 & aug 94 & freightcorp \\
27 & 9028 & none & 1400/918266/28 & aug 94 & freightcorp \\
28 & 9029 & none & 1401/918266/29 & aug 94 & freightcorp \\
29 & 9030 & australian men's hockey team & 1402/918266-30 & aug 94 & freightcorp \\
30 & 9031 & none & 1403/918266/31 & aug 94 & freightcorp \\
31 & 9032 & none & 05-1692 & nov 05 & pacific national \\
32 & 9033 & none & 05-1693 & nov 05 & pacific national \\
33 & 9034 & none & 05-1694 & nov 05 & pacific national \\
34 & 9035 & none & 05-1695 & nov 05 & pacific national \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where locomotive < 266 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>locomotive</th>
<th>name</th>
<th>serial no</th>
<th>entered service</th>
<th>livery</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9001</td>
<td>ernest henry</td>
<td>1373/918266-3</td>
<td>may 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>1</th>
<td>9002</td>
<td>michael wendon</td>
<td>1374/918266-2</td>
<td>may 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>2</th>
<td>9003</td>
<td>matthew ryan</td>
<td>1375/918266-1</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>3</th>
<td>9004</td>
<td>kevin nichols</td>
<td>1376/918266-4</td>
<td>may 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>4</th>
<td>9005</td>
<td>kevin barry</td>
<td>1377/918266-5</td>
<td>may 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>5</th>
<td>9006</td>
<td>murray rose</td>
<td>1378/918266-6</td>
<td>may 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>6</th>
<td>9007</td>
<td>dunc gray</td>
<td>1379/918266-7</td>
<td>may 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>7</th>
<td>9008</td>
<td>ralph doubell</td>
<td>1380/918266-8</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>8</th>
<td>9009</td>
<td>lionel cox</td>
<td>1381/918266-9</td>
<td>jul 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>9</th>
<td>9010</td>
<td>john devitt</td>
<td>1382/918266-10</td>
<td>jul 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>10</th>
<td>9011</td>
<td>kevan gosper</td>
<td>1383/918266-11</td>
<td>jul 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>11</th>
<td>9012</td>
<td>neil brooks/peter evans/ mark kerry/mark tonelli</td>
<td>1384/918266-12</td>
<td>jun 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>12</th>
<td>9013</td>
<td>michael diamond</td>
<td>1385/918266-13</td>
<td>jun 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>13</th>
<td>9014</td>
<td>peter antonie/stephen hawkins</td>
<td>1386/918266-14</td>
<td>jul 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>14</th>
<td>9015</td>
<td>duncan armstrong</td>
<td>1387/918266-15</td>
<td>jul 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>15</th>
<td>9016</td>
<td>herb elliott</td>
<td>1388/918266-16</td>
<td>jul 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>16</th>
<td>9017</td>
<td>andrew cooper/nicholas green/ michael mckay/james tomkins</td>
<td>1389/918266-17</td>
<td>jun 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>17</th>
<td>9018</td>
<td>john konrads</td>
<td>1390/918266-18</td>
<td>jul 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>18</th>
<td>9019</td>
<td>dean lukin</td>
<td>1391/918266-19</td>
<td>jul 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>19</th>
<td>9020</td>
<td>russell mark</td>
<td>1392/918266-20</td>
<td>jun 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>20</th>
<td>9021</td>
<td>ian o'brien</td>
<td>1393/918266-21</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>21</th>
<td>9022</td>
<td>clint robinson</td>
<td>1394/918266-22</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>22</th>
<td>9023</td>
<td>robert windle</td>
<td>1395/918266-23</td>
<td>oct 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>23</th>
<td>9024</td>
<td>john winter</td>
<td>1396/918266-24</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>24</th>
<td>9025</td>
<td>todd woodbridge/mark woodforde</td>
<td>1397/918266-25</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>25</th>
<td>9026</td>
<td>david theile</td>
<td>1398/918266-26</td>
<td>oct 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>26</th>
<td>9027</td>
<td>none</td>
<td>1399/918266-27</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>27</th>
<td>9028</td>
<td>none</td>
<td>1400/918266/28</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>28</th>
<td>9029</td>
<td>none</td>
<td>1401/918266/29</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>29</th>
<td>9030</td>
<td>australian men's hockey team</td>
<td>1402/918266-30</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>30</th>
<td>9031</td>
<td>none</td>
<td>1403/918266/31</td>
<td>aug 94</td>
<td>freightcorp</td>
</tr>
<tr>
<th>31</th>
<td>9032</td>
<td>none</td>
<td>05-1692</td>
<td>nov 05</td>
<td>pacific national</td>
</tr>
<tr>
<th>32</th>
<td>9033</td>
<td>none</td>
<td>05-1693</td>
<td>nov 05</td>
<td>pacific national</td>
</tr>
<tr>
<th>33</th>
<td>9034</td>
<td>none</td>
<td>05-1694</td>
<td>nov 05</td>
<td>pacific national</td>
</tr>
<tr>
<th>34</th>
<td>9035</td>
<td>none</td>
<td>05-1695</td>
<td>nov 05</td>
<td>pacific national</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where locomotive < 266 <table_name> : table | | locomotive | name | serial no | entered service | livery |
|---:|-------------:|:----------------------------------------------------------|:---------------|:------------------|:-----------------|
| 0 | 9001 | ernest henry | 1373/918266-3 | may 94 | freightcorp |
| 1 | 9002 | michael wendon | 1374/918266-2 | may 94 | freightcorp |
| 2 | 9003 | matthew ryan | 1375/918266-1 | aug 94 | freightcorp |
| 3 | 9004 | kevin nichols | 1376/918266-4 | may 94 | freightcorp |
| 4 | 9005 | kevin barry | 1377/918266-5 | may 94 | freightcorp |
| 5 | 9006 | murray rose | 1378/918266-6 | may 94 | freightcorp |
| 6 | 9007 | dunc gray | 1379/918266-7 | may 94 | freightcorp |
| 7 | 9008 | ralph doubell | 1380/918266-8 | aug 94 | freightcorp |
| 8 | 9009 | lionel cox | 1381/918266-9 | jul 94 | freightcorp |
| 9 | 9010 | john devitt | 1382/918266-10 | jul 94 | freightcorp |
| 10 | 9011 | kevan gosper | 1383/918266-11 | jul 94 | freightcorp |
| 11 | 9012 | neil brooks/peter evans/ mark kerry/mark tonelli | 1384/918266-12 | jun 94 | freightcorp |
| 12 | 9013 | michael diamond | 1385/918266-13 | jun 94 | freightcorp |
| 13 | 9014 | peter antonie/stephen hawkins | 1386/918266-14 | jul 94 | freightcorp |
| 14 | 9015 | duncan armstrong | 1387/918266-15 | jul 94 | freightcorp |
| 15 | 9016 | herb elliott | 1388/918266-16 | jul 94 | freightcorp |
| 16 | 9017 | andrew cooper/nicholas green/ michael mckay/james tomkins | 1389/918266-17 | jun 94 | freightcorp |
| 17 | 9018 | john konrads | 1390/918266-18 | jul 94 | freightcorp |
| 18 | 9019 | dean lukin | 1391/918266-19 | jul 94 | freightcorp |
| 19 | 9020 | russell mark | 1392/918266-20 | jun 94 | freightcorp |
| 20 | 9021 | ian o'brien | 1393/918266-21 | aug 94 | freightcorp |
| 21 | 9022 | clint robinson | 1394/918266-22 | aug 94 | freightcorp |
| 22 | 9023 | robert windle | 1395/918266-23 | oct 94 | freightcorp |
| 23 | 9024 | john winter | 1396/918266-24 | aug 94 | freightcorp |
| 24 | 9025 | todd woodbridge/mark woodforde | 1397/918266-25 | aug 94 | freightcorp |
| 25 | 9026 | david theile | 1398/918266-26 | oct 94 | freightcorp |
| 26 | 9027 | none | 1399/918266-27 | aug 94 | freightcorp |
| 27 | 9028 | none | 1400/918266/28 | aug 94 | freightcorp |
| 28 | 9029 | none | 1401/918266/29 | aug 94 | freightcorp |
| 29 | 9030 | australian men's hockey team | 1402/918266-30 | aug 94 | freightcorp |
| 30 | 9031 | none | 1403/918266/31 | aug 94 | freightcorp |
| 31 | 9032 | none | 05-1692 | nov 05 | pacific national |
| 32 | 9033 | none | 05-1693 | nov 05 | pacific national |
| 33 | 9034 | none | 05-1694 | nov 05 | pacific national |
| 34 | 9035 | none | 05-1695 | nov 05 | pacific national | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( * ) where name = 'maria' col : # | name | strike tone (st-1/16) | weight (kg) | diameter (mm) | inscription row 1 : 1 | maria | g0 +8 | 6045 | 2075 | + o mater alma christi carissima-suscipe pia laudum praecamina. (o dearest nourishing mother of christ, raise praise for our pious hymn) gegossen 1535 + zerstoert 1656 + erneuert 1659 + zerborsten 1818 + umgegossen 1881 + zerschlagen 1942 + wiederum erneuert 1958 (cast 1535 + destroyed 1656 + restored 1659 + destroyed 1818 + recast 1881 + obliterated 1942 + restored again 1958) row 2 : 2 | carolus | h0 +7 | 2900 | 1628 | honor et cultus, quem regalis ecclesia aquen: sanctissimo imperatori patrono ac fundatori suo carolo virtute, merito, imperio vere magno debet et defert mihi nomen dedit anno 1 6 5 9 (the honour and devotion, which the royal church of aachen owes and renders to its most sacred emperor, patron and benefactor: charles, truly great in virtue, merit and rule, gave this name to me in the year 1659) row 3 : 3 | johannes evangelista | d1 +8 | 1400 | 1367 | nascentes inter socias mecum ordine ponor tertia, sed cum quinta tono appellata johannes(i am placed fourth in order among the friends born with me, but i call to john with the fifth tone) row 4 : 4 | johannes baptista | e1 +7 | 1225 | 1217 | johannes baptista ora pro nobis. in ludo haud in agro florens nos curia fecit sed longo sub argo fudit nos ipse decano. an o. 1 6 5 6 (john the baptist pray for us. flourishing in play not in toil, he made us with care, but poured us under a vigilant supervisor. 1656) row 5 : 5 | leopardus | fis1 +3 | 850 | 1078 | sancte leoparde ora pro nobis anno 1 6 5 9 (saint leopardus pray for us. made 1659.) row 6 : 6 | stephanus | g1 +8 | 715 | 1027 | sancte stephane ora pro nobis anno 1 6 5 9 (st stephen pray for us. made 1659.) row 7 : 7 | petrus | a1 +1 | 425 | 894 | sancte petre ora pro nobis anno 1 6 5 9 (st. peter pray for us. made 1659.) row 8 : 8 | simeon | h1 +8 | 290 | 793 | sancte simeon juste et timorate ora pro nobis (st simon, just and devout, pray for us) | col : count ( "*" ) row 1 : 1 | select count ( * ) where name = 'maria' <table_name> : table \begin{tabular}{lllllll}
\toprule
& # & name & strike tone (st-1/16) & weight (kg) & diameter (mm) & inscription \\
\midrule
0 & 1 & maria & g0 +8 & 6045 & 2075 & + o mater alma christi carissima-suscipe pia laudum praecamina. (o dearest nourishing mother of christ, raise praise for our pious hymn) gegossen 1535 + zerstoert 1656 + erneuert 1659 + zerborsten 1818 + umgegossen 1881 + zerschlagen 1942 + wiederum erneuert 1958 (cast 1535 + destroyed 1656 + restored 1659 + destroyed 1818 + recast 1881 + obliterated 1942 + restored again 1958) \\
1 & 2 & carolus & h0 +7 & 2900 & 1628 & honor et cultus, quem regalis ecclesia aquen: sanctissimo imperatori patrono ac fundatori suo carolo virtute, merito, imperio vere magno debet et defert mihi nomen dedit anno 1 6 5 9 (the honour and devotion, which the royal church of aachen owes and renders to its most sacred emperor, patron and benefactor: charles, truly great in virtue, merit and rule, gave this name to me in the year 1659) \\
2 & 3 & johannes evangelista & d1 +8 & 1400 & 1367 & nascentes inter socias mecum ordine ponor tertia, sed cum quinta tono appellata johannes(i am placed fourth in order among the friends born with me, but i call to john with the fifth tone) \\
3 & 4 & johannes baptista & e1 +7 & 1225 & 1217 & johannes baptista ora pro nobis. in ludo haud in agro florens nos curia fecit sed longo sub argo fudit nos ipse decano. an o. 1 6 5 6 (john the baptist pray for us. flourishing in play not in toil, he made us with care, but poured us under a vigilant supervisor. 1656) \\
4 & 5 & leopardus & fis1 +3 & 850 & 1078 & sancte leoparde ora pro nobis anno 1 6 5 9 (saint leopardus pray for us. made 1659.) \\
5 & 6 & stephanus & g1 +8 & 715 & 1027 & sancte stephane ora pro nobis anno 1 6 5 9 (st stephen pray for us. made 1659.) \\
6 & 7 & petrus & a1 +1 & 425 & 894 & sancte petre ora pro nobis anno 1 6 5 9 (st. peter pray for us. made 1659.) \\
7 & 8 & simeon & h1 +8 & 290 & 793 & sancte simeon juste et timorate ora pro nobis (st simon, just and devout, pray for us) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where name = 'maria' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>name</th>
<th>strike tone (st-1/16)</th>
<th>weight (kg)</th>
<th>diameter (mm)</th>
<th>inscription</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>maria</td>
<td>g0 +8</td>
<td>6045</td>
<td>2075</td>
<td>+ o mater alma christi carissima-suscipe pia laudum praecamina. (o dearest nourishing mother of christ, raise praise for our pious hymn) gegossen 1535 + zerstoert 1656 + erneuert 1659 + zerborsten 1818 + umgegossen 1881 + zerschlagen 1942 + wiederum erneuert 1958 (cast 1535 + destroyed 1656 + restored 1659 + destroyed 1818 + recast 1881 + obliterated 1942 + restored again 1958)</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>carolus</td>
<td>h0 +7</td>
<td>2900</td>
<td>1628</td>
<td>honor et cultus, quem regalis ecclesia aquen: sanctissimo imperatori patrono ac fundatori suo carolo virtute, merito, imperio vere magno debet et defert mihi nomen dedit anno 1 6 5 9 (the honour and devotion, which the royal church of aachen owes and renders to its most sacred emperor, patron and benefactor: charles, truly great in virtue, merit and rule, gave this name to me in the year 1659)</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>johannes evangelista</td>
<td>d1 +8</td>
<td>1400</td>
<td>1367</td>
<td>nascentes inter socias mecum ordine ponor tertia, sed cum quinta tono appellata johannes(i am placed fourth in order among the friends born with me, but i call to john with the fifth tone)</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>johannes baptista</td>
<td>e1 +7</td>
<td>1225</td>
<td>1217</td>
<td>johannes baptista ora pro nobis. in ludo haud in agro florens nos curia fecit sed longo sub argo fudit nos ipse decano. an o. 1 6 5 6 (john the baptist pray for us. flourishing in play not in toil, he made us with care, but poured us under a vigilant supervisor. 1656)</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>leopardus</td>
<td>fis1 +3</td>
<td>850</td>
<td>1078</td>
<td>sancte leoparde ora pro nobis anno 1 6 5 9 (saint leopardus pray for us. made 1659.)</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>stephanus</td>
<td>g1 +8</td>
<td>715</td>
<td>1027</td>
<td>sancte stephane ora pro nobis anno 1 6 5 9 (st stephen pray for us. made 1659.)</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>petrus</td>
<td>a1 +1</td>
<td>425</td>
<td>894</td>
<td>sancte petre ora pro nobis anno 1 6 5 9 (st. peter pray for us. made 1659.)</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>simeon</td>
<td>h1 +8</td>
<td>290</td>
<td>793</td>
<td>sancte simeon juste et timorate ora pro nobis (st simon, just and devout, pray for us)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where name = 'maria' <table_name> : table | | # | name | strike tone (st-1/16) | weight (kg) | diameter (mm) | inscription |
|---:|----:|:---------------------|:------------------------|--------------:|----------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 1 | maria | g0 +8 | 6045 | 2075 | + o mater alma christi carissima-suscipe pia laudum praecamina. (o dearest nourishing mother of christ, raise praise for our pious hymn) gegossen 1535 + zerstoert 1656 + erneuert 1659 + zerborsten 1818 + umgegossen 1881 + zerschlagen 1942 + wiederum erneuert 1958 (cast 1535 + destroyed 1656 + restored 1659 + destroyed 1818 + recast 1881 + obliterated 1942 + restored again 1958) |
| 1 | 2 | carolus | h0 +7 | 2900 | 1628 | honor et cultus, quem regalis ecclesia aquen: sanctissimo imperatori patrono ac fundatori suo carolo virtute, merito, imperio vere magno debet et defert mihi nomen dedit anno 1 6 5 9 (the honour and devotion, which the royal church of aachen owes and renders to its most sacred emperor, patron and benefactor: charles, truly great in virtue, merit and rule, gave this name to me in the year 1659) |
| 2 | 3 | johannes evangelista | d1 +8 | 1400 | 1367 | nascentes inter socias mecum ordine ponor tertia, sed cum quinta tono appellata johannes(i am placed fourth in order among the friends born with me, but i call to john with the fifth tone) |
| 3 | 4 | johannes baptista | e1 +7 | 1225 | 1217 | johannes baptista ora pro nobis. in ludo haud in agro florens nos curia fecit sed longo sub argo fudit nos ipse decano. an o. 1 6 5 6 (john the baptist pray for us. flourishing in play not in toil, he made us with care, but poured us under a vigilant supervisor. 1656) |
| 4 | 5 | leopardus | fis1 +3 | 850 | 1078 | sancte leoparde ora pro nobis anno 1 6 5 9 (saint leopardus pray for us. made 1659.) |
| 5 | 6 | stephanus | g1 +8 | 715 | 1027 | sancte stephane ora pro nobis anno 1 6 5 9 (st stephen pray for us. made 1659.) |
| 6 | 7 | petrus | a1 +1 | 425 | 894 | sancte petre ora pro nobis anno 1 6 5 9 (st. peter pray for us. made 1659.) |
| 7 | 8 | simeon | h1 +8 | 290 | 793 | sancte simeon juste et timorate ora pro nobis (st simon, just and devout, pray for us) | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where pakistan captain = 'nasir ali' col : year | matches | winner | results | pakistan captain | pakistan coach | india captain | india coach row 1 : 1978 | 4 | pakistan win | 3 - 1 | islahuddin siddique | sayad a. hussain | v. j. philips | r. s. gentle row 2 : 1981 | 4 | pakistan win | 2 - 1 | akhtar rasool | zakauddin | surjeet singh | harmeek singh row 3 : 1986 | 7 | india win | 3 - 2 | hassan sardar | anwar ahmad khan | mohmmad shaheed | m. p. ganesh row 4 : 1988 | 6 | draw | 2 - 2 | nasir ali | manzoor-ul-hasan | m. m. somaya | m. p. ganesh row 5 : 1998 | 8 | pakistan win | 4 - 3 | tahir zaman | islahuddin siddique | dhanraj pillay | v bhaskaran row 6 : 1999 | 9 | pakistan win | 5 - 3 | atif bashir | shahnaz shaikh | anil aldrin | v bhaskaran row 7 : 2004 | 8 | pakistan win | 4 - 2 | waseem ahmad | roelant oltmans | dileep tirkey | gehard rach row 8 : 2006 | 6 | pakistan win | 3 - 1 | mohammad saqlain | asif bajwa | ignace tirkey | rajinder singh jr row 9 : 2013 | none | none | none | none | none | none | none | col : count ( "*" ) row 1 : 1 | select count ( * ) where pakistan captain = 'nasir ali' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& year & matches & winner & results & pakistan captain & pakistan coach & india captain & india coach \\
\midrule
0 & 1978 & 4 & pakistan win & 3 - 1 & islahuddin siddique & sayad a. hussain & v. j. philips & r. s. gentle \\
1 & 1981 & 4 & pakistan win & 2 - 1 & akhtar rasool & zakauddin & surjeet singh & harmeek singh \\
2 & 1986 & 7 & india win & 3 - 2 & hassan sardar & anwar ahmad khan & mohmmad shaheed & m. p. ganesh \\
3 & 1988 & 6 & draw & 2 - 2 & nasir ali & manzoor-ul-hasan & m. m. somaya & m. p. ganesh \\
4 & 1998 & 8 & pakistan win & 4 - 3 & tahir zaman & islahuddin siddique & dhanraj pillay & v bhaskaran \\
5 & 1999 & 9 & pakistan win & 5 - 3 & atif bashir & shahnaz shaikh & anil aldrin & v bhaskaran \\
6 & 2004 & 8 & pakistan win & 4 - 2 & waseem ahmad & roelant oltmans & dileep tirkey & gehard rach \\
7 & 2006 & 6 & pakistan win & 3 - 1 & mohammad saqlain & asif bajwa & ignace tirkey & rajinder singh jr \\
8 & 2013 & none & none & none & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where pakistan captain = 'nasir ali' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>matches</th>
<th>winner</th>
<th>results</th>
<th>pakistan captain</th>
<th>pakistan coach</th>
<th>india captain</th>
<th>india coach</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1978</td>
<td>4</td>
<td>pakistan win</td>
<td>3 - 1</td>
<td>islahuddin siddique</td>
<td>sayad a. hussain</td>
<td>v. j. philips</td>
<td>r. s. gentle</td>
</tr>
<tr>
<th>1</th>
<td>1981</td>
<td>4</td>
<td>pakistan win</td>
<td>2 - 1</td>
<td>akhtar rasool</td>
<td>zakauddin</td>
<td>surjeet singh</td>
<td>harmeek singh</td>
</tr>
<tr>
<th>2</th>
<td>1986</td>
<td>7</td>
<td>india win</td>
<td>3 - 2</td>
<td>hassan sardar</td>
<td>anwar ahmad khan</td>
<td>mohmmad shaheed</td>
<td>m. p. ganesh</td>
</tr>
<tr>
<th>3</th>
<td>1988</td>
<td>6</td>
<td>draw</td>
<td>2 - 2</td>
<td>nasir ali</td>
<td>manzoor-ul-hasan</td>
<td>m. m. somaya</td>
<td>m. p. ganesh</td>
</tr>
<tr>
<th>4</th>
<td>1998</td>
<td>8</td>
<td>pakistan win</td>
<td>4 - 3</td>
<td>tahir zaman</td>
<td>islahuddin siddique</td>
<td>dhanraj pillay</td>
<td>v bhaskaran</td>
</tr>
<tr>
<th>5</th>
<td>1999</td>
<td>9</td>
<td>pakistan win</td>
<td>5 - 3</td>
<td>atif bashir</td>
<td>shahnaz shaikh</td>
<td>anil aldrin</td>
<td>v bhaskaran</td>
</tr>
<tr>
<th>6</th>
<td>2004</td>
<td>8</td>
<td>pakistan win</td>
<td>4 - 2</td>
<td>waseem ahmad</td>
<td>roelant oltmans</td>
<td>dileep tirkey</td>
<td>gehard rach</td>
</tr>
<tr>
<th>7</th>
<td>2006</td>
<td>6</td>
<td>pakistan win</td>
<td>3 - 1</td>
<td>mohammad saqlain</td>
<td>asif bajwa</td>
<td>ignace tirkey</td>
<td>rajinder singh jr</td>
</tr>
<tr>
<th>8</th>
<td>2013</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where pakistan captain = 'nasir ali' <table_name> : table | | year | matches | winner | results | pakistan captain | pakistan coach | india captain | india coach |
|---:|-------:|:----------|:-------------|:----------|:--------------------|:--------------------|:----------------|:------------------|
| 0 | 1978 | 4 | pakistan win | 3 - 1 | islahuddin siddique | sayad a. hussain | v. j. philips | r. s. gentle |
| 1 | 1981 | 4 | pakistan win | 2 - 1 | akhtar rasool | zakauddin | surjeet singh | harmeek singh |
| 2 | 1986 | 7 | india win | 3 - 2 | hassan sardar | anwar ahmad khan | mohmmad shaheed | m. p. ganesh |
| 3 | 1988 | 6 | draw | 2 - 2 | nasir ali | manzoor-ul-hasan | m. m. somaya | m. p. ganesh |
| 4 | 1998 | 8 | pakistan win | 4 - 3 | tahir zaman | islahuddin siddique | dhanraj pillay | v bhaskaran |
| 5 | 1999 | 9 | pakistan win | 5 - 3 | atif bashir | shahnaz shaikh | anil aldrin | v bhaskaran |
| 6 | 2004 | 8 | pakistan win | 4 - 2 | waseem ahmad | roelant oltmans | dileep tirkey | gehard rach |
| 7 | 2006 | 6 | pakistan win | 3 - 1 | mohammad saqlain | asif bajwa | ignace tirkey | rajinder singh jr |
| 8 | 2013 | none | none | none | none | none | none | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select march 9 120 where december 25-26 122 = 152 col : may 20-21 118 | march 9 120 | december 25-26 122 | october 13-14 124 | august 1-2 126 row 1 : may 21, 1993 | march 9, 1997 | december 25, 2000 | october 14, 2004 | august 1, 2008 row 2 : 128 | 130 | 132 | 134 | 136 row 3 : may 20, 2012 | march 9, 2016 | december 26, 2019 | october 14, 2023 | august 2, 2027 row 4 : 138 | 140 | 142 | 144 | 146 row 5 : may 21, 2031 | march 9, 2035 | december 26, 2038 | october 14, 2042 | august 2, 2046 row 6 : 148 | 150 | 152 | 154 | 156 row 7 : may 20, 2050 | march 9, 2054 | december 26, 2057 | october 13, 2061 | august 2, 2065 | col : march 9 120 row 1 : 150 | select march 9 120 where december 25-26 122 = 152 <table_name> : table \begin{tabular}{llllll}
\toprule
& may 20-21 118 & march 9 120 & december 25-26 122 & october 13-14 124 & august 1-2 126 \\
\midrule
0 & may 21, 1993 & march 9, 1997 & december 25, 2000 & october 14, 2004 & august 1, 2008 \\
1 & 128 & 130 & 132 & 134 & 136 \\
2 & may 20, 2012 & march 9, 2016 & december 26, 2019 & october 14, 2023 & august 2, 2027 \\
3 & 138 & 140 & 142 & 144 & 146 \\
4 & may 21, 2031 & march 9, 2035 & december 26, 2038 & october 14, 2042 & august 2, 2046 \\
5 & 148 & 150 & 152 & 154 & 156 \\
6 & may 20, 2050 & march 9, 2054 & december 26, 2057 & october 13, 2061 & august 2, 2065 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& march 9 120 \\
\midrule
0 & 150 \\
\bottomrule
\end{tabular}
| select march 9 120 where december 25-26 122 = 152 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>may 20-21 118</th>
<th>march 9 120</th>
<th>december 25-26 122</th>
<th>october 13-14 124</th>
<th>august 1-2 126</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>may 21, 1993</td>
<td>march 9, 1997</td>
<td>december 25, 2000</td>
<td>october 14, 2004</td>
<td>august 1, 2008</td>
</tr>
<tr>
<th>1</th>
<td>128</td>
<td>130</td>
<td>132</td>
<td>134</td>
<td>136</td>
</tr>
<tr>
<th>2</th>
<td>may 20, 2012</td>
<td>march 9, 2016</td>
<td>december 26, 2019</td>
<td>october 14, 2023</td>
<td>august 2, 2027</td>
</tr>
<tr>
<th>3</th>
<td>138</td>
<td>140</td>
<td>142</td>
<td>144</td>
<td>146</td>
</tr>
<tr>
<th>4</th>
<td>may 21, 2031</td>
<td>march 9, 2035</td>
<td>december 26, 2038</td>
<td>october 14, 2042</td>
<td>august 2, 2046</td>
</tr>
<tr>
<th>5</th>
<td>148</td>
<td>150</td>
<td>152</td>
<td>154</td>
<td>156</td>
</tr>
<tr>
<th>6</th>
<td>may 20, 2050</td>
<td>march 9, 2054</td>
<td>december 26, 2057</td>
<td>october 13, 2061</td>
<td>august 2, 2065</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>march 9 120</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>150</td>
</tr>
</tbody>
</table> | select march 9 120 where december 25-26 122 = 152 <table_name> : table | | may 20-21 118 | march 9 120 | december 25-26 122 | october 13-14 124 | august 1-2 126 |
|---:|:----------------|:--------------|:---------------------|:--------------------|:-----------------|
| 0 | may 21, 1993 | march 9, 1997 | december 25, 2000 | october 14, 2004 | august 1, 2008 |
| 1 | 128 | 130 | 132 | 134 | 136 |
| 2 | may 20, 2012 | march 9, 2016 | december 26, 2019 | october 14, 2023 | august 2, 2027 |
| 3 | 138 | 140 | 142 | 144 | 146 |
| 4 | may 21, 2031 | march 9, 2035 | december 26, 2038 | october 14, 2042 | august 2, 2046 |
| 5 | 148 | 150 | 152 | 154 | 156 |
| 6 | may 20, 2050 | march 9, 2054 | december 26, 2057 | october 13, 2061 | august 2, 2065 | | | | march 9 120 |
|---:|--------------:|
| 0 | 150 | | [
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select count ( * ) where notes = 'a-1234 1234-a ab-123 a123b' col : first issued | design | slogan | serial format | serials issued | notes row 1 : 1957-65 (odd years only) | embossed white on forest green with uncolored border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right | see embossed in same letters as vermont, at lower left | 12345 (rounded numbers) | none | alternated with white plates from 1957 to 1966 row 2 : 1958-66 (even years only) | embossed forest green on white with uncolored border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right | see embossed in same letters as vermont, at lower left | 12345 (rounded numbers) a1234 (1962 only) | none | alternated with forest green plates from 1957 to 1966 row 3 : 1967 | embossed white on green with border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right | none | 1234 a-1234 1234-a | none | color changed from forest green to the kelly green used today row 4 : 1969 | embossed white on green with border line; vermont embossed in plain block letters centered below numbers; registration sticker at bottom right corner | see embossed in lower left corner | 1234 a-1234 1234-a | none | see returned to plate row 5 : 1972 | embossed white on green with border line; vermont embossed in plain block letters centered above numbers; registration sticker at bottom left corner | see embossed in top left corner | a-1234 1234-a ab-123 a123b | none | none row 6 : 1976 | embossed white on green with border line; vermont embossed in plain block letters centered below numbers; white circle embossed to lower left; registration sticker at lower right | green mountains embossed in thin block letters centered above numbers | a-1234 1234-a ab123 123ab | none | none row 7 : 1977 | embossed white on green with beveled edge and white rectangular box around numbers; vermont in white stylized font screened above white box, with white sugar maple in upper left corner; registration sticker at lower right corner | green mountain state screened in white plain serifed font centered below white box | 123a4 (rounded numbers) | none | none row 8 : 1985 | embossed white on green with beveled edge and white rectangular box around numbers; vermont in white stylized font screened above white box, with white sugar maple in upper left corner; registration sticker at lower right corner | green mountain state screened in white plain serifed font centered below white box | 1a234 123a4 1ab23 12ab3 abc 123 123a456 (more rectangular numbers than previous set) | 1a100 to 9y999 100a1 to 999y9 1aa00 to ?f?99 00aa1 to 99??9 aab 100 to present 100a100 to present | the "1aa" series never reached 1ga currently, the letters i, j, o, q, u, v and z are not in regular use. the "100a100" series are new truck plates issued starting in mid-2009 | col : count ( "*" ) row 1 : 0 | select count ( * ) where notes = 'a-1234 1234-a ab-123 a123b' <table_name> : table \begin{tabular}{lllllll}
\toprule
& first issued & design & slogan & serial format & serials issued & notes \\
\midrule
0 & 1957-65 (odd years only) & embossed white on forest green with uncolored border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right & see embossed in same letters as vermont, at lower left & 12345 (rounded numbers) & none & alternated with white plates from 1957 to 1966 \\
1 & 1958-66 (even years only) & embossed forest green on white with uncolored border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right & see embossed in same letters as vermont, at lower left & 12345 (rounded numbers) a1234 (1962 only) & none & alternated with forest green plates from 1957 to 1966 \\
2 & 1967 & embossed white on green with border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right & none & 1234 a-1234 1234-a & none & color changed from forest green to the kelly green used today \\
3 & 1969 & embossed white on green with border line; vermont embossed in plain block letters centered below numbers; registration sticker at bottom right corner & see embossed in lower left corner & 1234 a-1234 1234-a & none & see returned to plate \\
4 & 1972 & embossed white on green with border line; vermont embossed in plain block letters centered above numbers; registration sticker at bottom left corner & see embossed in top left corner & a-1234 1234-a ab-123 a123b & none & none \\
5 & 1976 & embossed white on green with border line; vermont embossed in plain block letters centered below numbers; white circle embossed to lower left; registration sticker at lower right & green mountains embossed in thin block letters centered above numbers & a-1234 1234-a ab123 123ab & none & none \\
6 & 1977 & embossed white on green with beveled edge and white rectangular box around numbers; vermont in white stylized font screened above white box, with white sugar maple in upper left corner; registration sticker at lower right corner & green mountain state screened in white plain serifed font centered below white box & 123a4 (rounded numbers) & none & none \\
7 & 1985 & embossed white on green with beveled edge and white rectangular box around numbers; vermont in white stylized font screened above white box, with white sugar maple in upper left corner; registration sticker at lower right corner & green mountain state screened in white plain serifed font centered below white box & 1a234 123a4 1ab23 12ab3 abc 123 123a456 (more rectangular numbers than previous set) & 1a100 to 9y999 100a1 to 999y9 1aa00 to ?f?99 00aa1 to 99??9 aab 100 to present 100a100 to present & the "1aa" series never reached 1ga currently, the letters i, j, o, q, u, v and z are not in regular use. the "100a100" series are new truck plates issued starting in mid-2009 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where notes = 'a-1234 1234-a ab-123 a123b' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>first issued</th>
<th>design</th>
<th>slogan</th>
<th>serial format</th>
<th>serials issued</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1957-65 (odd years only)</td>
<td>embossed white on forest green with uncolored border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right</td>
<td>see embossed in same letters as vermont, at lower left</td>
<td>12345 (rounded numbers)</td>
<td>none</td>
<td>alternated with white plates from 1957 to 1966</td>
</tr>
<tr>
<th>1</th>
<td>1958-66 (even years only)</td>
<td>embossed forest green on white with uncolored border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right</td>
<td>see embossed in same letters as vermont, at lower left</td>
<td>12345 (rounded numbers) a1234 (1962 only)</td>
<td>none</td>
<td>alternated with forest green plates from 1957 to 1966</td>
</tr>
<tr>
<th>2</th>
<td>1967</td>
<td>embossed white on green with border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right</td>
<td>none</td>
<td>1234 a-1234 1234-a</td>
<td>none</td>
<td>color changed from forest green to the kelly green used today</td>
</tr>
<tr>
<th>3</th>
<td>1969</td>
<td>embossed white on green with border line; vermont embossed in plain block letters centered below numbers; registration sticker at bottom right corner</td>
<td>see embossed in lower left corner</td>
<td>1234 a-1234 1234-a</td>
<td>none</td>
<td>see returned to plate</td>
</tr>
<tr>
<th>4</th>
<td>1972</td>
<td>embossed white on green with border line; vermont embossed in plain block letters centered above numbers; registration sticker at bottom left corner</td>
<td>see embossed in top left corner</td>
<td>a-1234 1234-a ab-123 a123b</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1976</td>
<td>embossed white on green with border line; vermont embossed in plain block letters centered below numbers; white circle embossed to lower left; registration sticker at lower right</td>
<td>green mountains embossed in thin block letters centered above numbers</td>
<td>a-1234 1234-a ab123 123ab</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1977</td>
<td>embossed white on green with beveled edge and white rectangular box around numbers; vermont in white stylized font screened above white box, with white sugar maple in upper left corner; registration sticker at lower right corner</td>
<td>green mountain state screened in white plain serifed font centered below white box</td>
<td>123a4 (rounded numbers)</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1985</td>
<td>embossed white on green with beveled edge and white rectangular box around numbers; vermont in white stylized font screened above white box, with white sugar maple in upper left corner; registration sticker at lower right corner</td>
<td>green mountain state screened in white plain serifed font centered below white box</td>
<td>1a234 123a4 1ab23 12ab3 abc 123 123a456 (more rectangular numbers than previous set)</td>
<td>1a100 to 9y999 100a1 to 999y9 1aa00 to ?f?99 00aa1 to 99??9 aab 100 to present 100a100 to present</td>
<td>the "1aa" series never reached 1ga currently, the letters i, j, o, q, u, v and z are not in regular use. the "100a100" series are new truck plates issued starting in mid-2009</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where notes = 'a-1234 1234-a ab-123 a123b' <table_name> : table | | first issued | design | slogan | serial format | serials issued | notes |
|---:|:--------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 1957-65 (odd years only) | embossed white on forest green with uncolored border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right | see embossed in same letters as vermont, at lower left | 12345 (rounded numbers) | none | alternated with white plates from 1957 to 1966 |
| 1 | 1958-66 (even years only) | embossed forest green on white with uncolored border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right | see embossed in same letters as vermont, at lower left | 12345 (rounded numbers) a1234 (1962 only) | none | alternated with forest green plates from 1957 to 1966 |
| 2 | 1967 | embossed white on green with border line; vermont embossed in plain block letters centered below numbers, with last two digits of registration year in similar font at bottom right | none | 1234 a-1234 1234-a | none | color changed from forest green to the kelly green used today |
| 3 | 1969 | embossed white on green with border line; vermont embossed in plain block letters centered below numbers; registration sticker at bottom right corner | see embossed in lower left corner | 1234 a-1234 1234-a | none | see returned to plate |
| 4 | 1972 | embossed white on green with border line; vermont embossed in plain block letters centered above numbers; registration sticker at bottom left corner | see embossed in top left corner | a-1234 1234-a ab-123 a123b | none | none |
| 5 | 1976 | embossed white on green with border line; vermont embossed in plain block letters centered below numbers; white circle embossed to lower left; registration sticker at lower right | green mountains embossed in thin block letters centered above numbers | a-1234 1234-a ab123 123ab | none | none |
| 6 | 1977 | embossed white on green with beveled edge and white rectangular box around numbers; vermont in white stylized font screened above white box, with white sugar maple in upper left corner; registration sticker at lower right corner | green mountain state screened in white plain serifed font centered below white box | 123a4 (rounded numbers) | none | none |
| 7 | 1985 | embossed white on green with beveled edge and white rectangular box around numbers; vermont in white stylized font screened above white box, with white sugar maple in upper left corner; registration sticker at lower right corner | green mountain state screened in white plain serifed font centered below white box | 1a234 123a4 1ab23 12ab3 abc 123 123a456 (more rectangular numbers than previous set) | 1a100 to 9y999 100a1 to 999y9 1aa00 to ?f?99 00aa1 to 99??9 aab 100 to present 100a100 to present | the "1aa" series never reached 1ga currently, the letters i, j, o, q, u, v and z are not in regular use. the "100a100" series are new truck plates issued starting in mid-2009 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( treaty ) where signed = ( select min ( signed ) ) col : treaty | organization | introduced | signed | ratified row 1 : convention on the prevention and punishment of the crime of genocide | united nations | 1948 | none | 1958 row 2 : international convention on the elimination of all forms of racial discrimination | united nations | 1966 | 1967 | 1970 row 3 : international covenant on economic, social and cultural rights | united nations | 1966 | 1977 | 1979 row 4 : international covenant on civil and political rights | united nations | 1966 | 1977 | 1979 row 5 : first optional protocol to the international covenant on civil and political rights | united nations | 1966 | none | none row 6 : convention on the non-applicability of statutory limitations to war crimes and crimes against humanity | united nations | 1968 | none | none row 7 : international convention on the suppression and punishment of the crime of apartheid | united nations | 1973 | none | none row 8 : convention on the elimination of all forms of discrimination against women | united nations | 1979 | none | 1993 row 9 : convention against torture and other cruel, inhuman or degrading treatment or punishment | united nations | 1984 | 1986 | 1993 row 10 : convention on the rights of the child | united nations | 1989 | 1990 | 1993 row 11 : second optional protocol to the international covenant on civil and political rights, aiming at the abolition of the death penalty | united nations | 1989 | none | none row 12 : international convention on the protection of the rights of all migrant workers and members of their families | united nations | 1990 | 1991 | 1993 row 13 : optional protocol to the convention on the elimination of all forms of discrimination against women | united nations | 1999 | none | none row 14 : optional protocol to the convention on the rights of the child on the involvement of children in armed conflict | united nations | 2000 | 2000 | 2002 row 15 : optional protocol to the convention on the rights of the child on the sale of children, child prostitution and child pornography | united nations | 2000 | 2000 | 2001 row 16 : convention on the rights of persons with disabilities | united nations | 2006 | 2007 | 2009 row 17 : optional protocol to the convention on the rights of persons with disabilities | united nations | 2006 | none | 2009 row 18 : international convention for the protection of all persons from enforced disappearance | united nations | 2006 | 2007 | 2013 row 19 : optional protocol to the international covenant on economic, social and cultural rights | united nations | 2008 | none | none row 20 : optional protocol to the convention on the rights of the child on a communications procedure | united nations | 2011 | 2012 | none | col : count ( "treaty" ) row 1 : 0 | select count ( treaty ) where signed = ( select min ( signed ) ) <table_name> : table \begin{tabular}{llllll}
\toprule
& treaty & organization & introduced & signed & ratified \\
\midrule
0 & convention on the prevention and punishment of the crime of genocide & united nations & 1948 & none & 1958 \\
1 & international convention on the elimination of all forms of racial discrimination & united nations & 1966 & 1967 & 1970 \\
2 & international covenant on economic, social and cultural rights & united nations & 1966 & 1977 & 1979 \\
3 & international covenant on civil and political rights & united nations & 1966 & 1977 & 1979 \\
4 & first optional protocol to the international covenant on civil and political rights & united nations & 1966 & none & none \\
5 & convention on the non-applicability of statutory limitations to war crimes and crimes against humanity & united nations & 1968 & none & none \\
6 & international convention on the suppression and punishment of the crime of apartheid & united nations & 1973 & none & none \\
7 & convention on the elimination of all forms of discrimination against women & united nations & 1979 & none & 1993 \\
8 & convention against torture and other cruel, inhuman or degrading treatment or punishment & united nations & 1984 & 1986 & 1993 \\
9 & convention on the rights of the child & united nations & 1989 & 1990 & 1993 \\
10 & second optional protocol to the international covenant on civil and political rights, aiming at the abolition of the death penalty & united nations & 1989 & none & none \\
11 & international convention on the protection of the rights of all migrant workers and members of their families & united nations & 1990 & 1991 & 1993 \\
12 & optional protocol to the convention on the elimination of all forms of discrimination against women & united nations & 1999 & none & none \\
13 & optional protocol to the convention on the rights of the child on the involvement of children in armed conflict & united nations & 2000 & 2000 & 2002 \\
14 & optional protocol to the convention on the rights of the child on the sale of children, child prostitution and child pornography & united nations & 2000 & 2000 & 2001 \\
15 & convention on the rights of persons with disabilities & united nations & 2006 & 2007 & 2009 \\
16 & optional protocol to the convention on the rights of persons with disabilities & united nations & 2006 & none & 2009 \\
17 & international convention for the protection of all persons from enforced disappearance & united nations & 2006 & 2007 & 2013 \\
18 & optional protocol to the international covenant on economic, social and cultural rights & united nations & 2008 & none & none \\
19 & optional protocol to the convention on the rights of the child on a communications procedure & united nations & 2011 & 2012 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "treaty" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( treaty ) where signed = ( select min ( signed ) ) <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>treaty</th>
<th>organization</th>
<th>introduced</th>
<th>signed</th>
<th>ratified</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>convention on the prevention and punishment of the crime of genocide</td>
<td>united nations</td>
<td>1948</td>
<td>none</td>
<td>1958</td>
</tr>
<tr>
<th>1</th>
<td>international convention on the elimination of all forms of racial discrimination</td>
<td>united nations</td>
<td>1966</td>
<td>1967</td>
<td>1970</td>
</tr>
<tr>
<th>2</th>
<td>international covenant on economic, social and cultural rights</td>
<td>united nations</td>
<td>1966</td>
<td>1977</td>
<td>1979</td>
</tr>
<tr>
<th>3</th>
<td>international covenant on civil and political rights</td>
<td>united nations</td>
<td>1966</td>
<td>1977</td>
<td>1979</td>
</tr>
<tr>
<th>4</th>
<td>first optional protocol to the international covenant on civil and political rights</td>
<td>united nations</td>
<td>1966</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>convention on the non-applicability of statutory limitations to war crimes and crimes against humanity</td>
<td>united nations</td>
<td>1968</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>international convention on the suppression and punishment of the crime of apartheid</td>
<td>united nations</td>
<td>1973</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>convention on the elimination of all forms of discrimination against women</td>
<td>united nations</td>
<td>1979</td>
<td>none</td>
<td>1993</td>
</tr>
<tr>
<th>8</th>
<td>convention against torture and other cruel, inhuman or degrading treatment or punishment</td>
<td>united nations</td>
<td>1984</td>
<td>1986</td>
<td>1993</td>
</tr>
<tr>
<th>9</th>
<td>convention on the rights of the child</td>
<td>united nations</td>
<td>1989</td>
<td>1990</td>
<td>1993</td>
</tr>
<tr>
<th>10</th>
<td>second optional protocol to the international covenant on civil and political rights, aiming at the abolition of the death penalty</td>
<td>united nations</td>
<td>1989</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>international convention on the protection of the rights of all migrant workers and members of their families</td>
<td>united nations</td>
<td>1990</td>
<td>1991</td>
<td>1993</td>
</tr>
<tr>
<th>12</th>
<td>optional protocol to the convention on the elimination of all forms of discrimination against women</td>
<td>united nations</td>
<td>1999</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>optional protocol to the convention on the rights of the child on the involvement of children in armed conflict</td>
<td>united nations</td>
<td>2000</td>
<td>2000</td>
<td>2002</td>
</tr>
<tr>
<th>14</th>
<td>optional protocol to the convention on the rights of the child on the sale of children, child prostitution and child pornography</td>
<td>united nations</td>
<td>2000</td>
<td>2000</td>
<td>2001</td>
</tr>
<tr>
<th>15</th>
<td>convention on the rights of persons with disabilities</td>
<td>united nations</td>
<td>2006</td>
<td>2007</td>
<td>2009</td>
</tr>
<tr>
<th>16</th>
<td>optional protocol to the convention on the rights of persons with disabilities</td>
<td>united nations</td>
<td>2006</td>
<td>none</td>
<td>2009</td>
</tr>
<tr>
<th>17</th>
<td>international convention for the protection of all persons from enforced disappearance</td>
<td>united nations</td>
<td>2006</td>
<td>2007</td>
<td>2013</td>
</tr>
<tr>
<th>18</th>
<td>optional protocol to the international covenant on economic, social and cultural rights</td>
<td>united nations</td>
<td>2008</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>optional protocol to the convention on the rights of the child on a communications procedure</td>
<td>united nations</td>
<td>2011</td>
<td>2012</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "treaty" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( treaty ) where signed = ( select min ( signed ) ) <table_name> : table | | treaty | organization | introduced | signed | ratified |
|---:|:-----------------------------------------------------------------------------------------------------------------------------------|:---------------|-------------:|:---------|:-----------|
| 0 | convention on the prevention and punishment of the crime of genocide | united nations | 1948 | none | 1958 |
| 1 | international convention on the elimination of all forms of racial discrimination | united nations | 1966 | 1967 | 1970 |
| 2 | international covenant on economic, social and cultural rights | united nations | 1966 | 1977 | 1979 |
| 3 | international covenant on civil and political rights | united nations | 1966 | 1977 | 1979 |
| 4 | first optional protocol to the international covenant on civil and political rights | united nations | 1966 | none | none |
| 5 | convention on the non-applicability of statutory limitations to war crimes and crimes against humanity | united nations | 1968 | none | none |
| 6 | international convention on the suppression and punishment of the crime of apartheid | united nations | 1973 | none | none |
| 7 | convention on the elimination of all forms of discrimination against women | united nations | 1979 | none | 1993 |
| 8 | convention against torture and other cruel, inhuman or degrading treatment or punishment | united nations | 1984 | 1986 | 1993 |
| 9 | convention on the rights of the child | united nations | 1989 | 1990 | 1993 |
| 10 | second optional protocol to the international covenant on civil and political rights, aiming at the abolition of the death penalty | united nations | 1989 | none | none |
| 11 | international convention on the protection of the rights of all migrant workers and members of their families | united nations | 1990 | 1991 | 1993 |
| 12 | optional protocol to the convention on the elimination of all forms of discrimination against women | united nations | 1999 | none | none |
| 13 | optional protocol to the convention on the rights of the child on the involvement of children in armed conflict | united nations | 2000 | 2000 | 2002 |
| 14 | optional protocol to the convention on the rights of the child on the sale of children, child prostitution and child pornography | united nations | 2000 | 2000 | 2001 |
| 15 | convention on the rights of persons with disabilities | united nations | 2006 | 2007 | 2009 |
| 16 | optional protocol to the convention on the rights of persons with disabilities | united nations | 2006 | none | 2009 |
| 17 | international convention for the protection of all persons from enforced disappearance | united nations | 2006 | 2007 | 2013 |
| 18 | optional protocol to the international covenant on economic, social and cultural rights | united nations | 2008 | none | none |
| 19 | optional protocol to the convention on the rights of the child on a communications procedure | united nations | 2011 | 2012 | none | | | | count ( "treaty" ) |
|---:|---------------------:|
| 0 | 0 | | [
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select team where team = 'gb' col : year | team | games | carries | yards | yards per carry | longest carry | touchdowns | first downs | fumbles | fumbles lost row 1 : 2002 | gb | 8 | 39 | 184 | 4.7 | 43 | 1 | 8 | 1 | 1 row 2 : 2003 | gb | 15 | 77 | 420 | 5.5 | 76 | 2 | 18 | 4 | 1 row 3 : 2004 | gb | 11 | 71 | 359 | 5.1 | 40 | 2 | 16 | 0 | 0 row 4 : 2005 | gb | 5 | 30 | 105 | 3.5 | 24 | 2 | 9 | 1 | 0 row 5 : 2006 | pit | 13 | 60 | 221 | 3.7 | 48 | 1 | 9 | 1 | 0 row 6 : 2007 | pit | 15 | 107 | 499 | 4.7 | 45 | 5 | 37 | 1 | 0 row 7 : 2008 | pit | 4 | 2 | 5 | 2.5 | 3 | 0 | 2 | 0 | 0 row 8 : 2008 | ind | 2 | 8 | 26 | 3.3 | 8 | 0 | 1 | 0 | 0 row 9 : career | none | 73 | 394 | 1819 | 4.6 | 76 | 13 | 100 | 8 | 2 | col : team row 1 : gb row 2 : gb row 3 : gb row 4 : gb | select team where team = 'gb' <table_name> : table \begin{tabular}{llllllllllll}
\toprule
& year & team & games & carries & yards & yards per carry & longest carry & touchdowns & first downs & fumbles & fumbles lost \\
\midrule
0 & 2002 & gb & 8 & 39 & 184 & 4.7 & 43 & 1 & 8 & 1 & 1 \\
1 & 2003 & gb & 15 & 77 & 420 & 5.5 & 76 & 2 & 18 & 4 & 1 \\
2 & 2004 & gb & 11 & 71 & 359 & 5.1 & 40 & 2 & 16 & 0 & 0 \\
3 & 2005 & gb & 5 & 30 & 105 & 3.5 & 24 & 2 & 9 & 1 & 0 \\
4 & 2006 & pit & 13 & 60 & 221 & 3.7 & 48 & 1 & 9 & 1 & 0 \\
5 & 2007 & pit & 15 & 107 & 499 & 4.7 & 45 & 5 & 37 & 1 & 0 \\
6 & 2008 & pit & 4 & 2 & 5 & 2.5 & 3 & 0 & 2 & 0 & 0 \\
7 & 2008 & ind & 2 & 8 & 26 & 3.3 & 8 & 0 & 1 & 0 & 0 \\
8 & career & none & 73 & 394 & 1819 & 4.6 & 76 & 13 & 100 & 8 & 2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& team \\
\midrule
0 & gb \\
1 & gb \\
2 & gb \\
3 & gb \\
\bottomrule
\end{tabular}
| select team where team = 'gb' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>team</th>
<th>games</th>
<th>carries</th>
<th>yards</th>
<th>yards per carry</th>
<th>longest carry</th>
<th>touchdowns</th>
<th>first downs</th>
<th>fumbles</th>
<th>fumbles lost</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2002</td>
<td>gb</td>
<td>8</td>
<td>39</td>
<td>184</td>
<td>4.7</td>
<td>43</td>
<td>1</td>
<td>8</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>1</th>
<td>2003</td>
<td>gb</td>
<td>15</td>
<td>77</td>
<td>420</td>
<td>5.5</td>
<td>76</td>
<td>2</td>
<td>18</td>
<td>4</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>2004</td>
<td>gb</td>
<td>11</td>
<td>71</td>
<td>359</td>
<td>5.1</td>
<td>40</td>
<td>2</td>
<td>16</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>2005</td>
<td>gb</td>
<td>5</td>
<td>30</td>
<td>105</td>
<td>3.5</td>
<td>24</td>
<td>2</td>
<td>9</td>
<td>1</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>2006</td>
<td>pit</td>
<td>13</td>
<td>60</td>
<td>221</td>
<td>3.7</td>
<td>48</td>
<td>1</td>
<td>9</td>
<td>1</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>2007</td>
<td>pit</td>
<td>15</td>
<td>107</td>
<td>499</td>
<td>4.7</td>
<td>45</td>
<td>5</td>
<td>37</td>
<td>1</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>2008</td>
<td>pit</td>
<td>4</td>
<td>2</td>
<td>5</td>
<td>2.5</td>
<td>3</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>2008</td>
<td>ind</td>
<td>2</td>
<td>8</td>
<td>26</td>
<td>3.3</td>
<td>8</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>8</th>
<td>career</td>
<td>none</td>
<td>73</td>
<td>394</td>
<td>1819</td>
<td>4.6</td>
<td>76</td>
<td>13</td>
<td>100</td>
<td>8</td>
<td>2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>gb</td>
</tr>
<tr>
<th>1</th>
<td>gb</td>
</tr>
<tr>
<th>2</th>
<td>gb</td>
</tr>
<tr>
<th>3</th>
<td>gb</td>
</tr>
</tbody>
</table> | select team where team = 'gb' <table_name> : table | | year | team | games | carries | yards | yards per carry | longest carry | touchdowns | first downs | fumbles | fumbles lost |
|---:|:-------|:-------|--------:|----------:|--------:|------------------:|----------------:|-------------:|--------------:|----------:|---------------:|
| 0 | 2002 | gb | 8 | 39 | 184 | 4.7 | 43 | 1 | 8 | 1 | 1 |
| 1 | 2003 | gb | 15 | 77 | 420 | 5.5 | 76 | 2 | 18 | 4 | 1 |
| 2 | 2004 | gb | 11 | 71 | 359 | 5.1 | 40 | 2 | 16 | 0 | 0 |
| 3 | 2005 | gb | 5 | 30 | 105 | 3.5 | 24 | 2 | 9 | 1 | 0 |
| 4 | 2006 | pit | 13 | 60 | 221 | 3.7 | 48 | 1 | 9 | 1 | 0 |
| 5 | 2007 | pit | 15 | 107 | 499 | 4.7 | 45 | 5 | 37 | 1 | 0 |
| 6 | 2008 | pit | 4 | 2 | 5 | 2.5 | 3 | 0 | 2 | 0 | 0 |
| 7 | 2008 | ind | 2 | 8 | 26 | 3.3 | 8 | 0 | 1 | 0 | 0 |
| 8 | career | none | 73 | 394 | 1819 | 4.6 | 76 | 13 | 100 | 8 | 2 | | | | team |
|---:|:-------|
| 0 | gb |
| 1 | gb |
| 2 | gb |
| 3 | gb | | [
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select count ( * ) where pollutant = 'nox' col : pollutant | units | emission standard | coal-fired | petroleum coke-fired row 1 : so2 | lb/mmbtu | ≤ 0.15 | 0.0-0.04 | 0.03-0.13 row 2 : nox | lb/mmbtu | ≤ 0.09 | 0.04-0.06 | 0.02 row 3 : solid particulate | lb/mmbtu | ≤ 0.011 | 0.004 | 0.007 row 4 : pm10 | lb/mmbtu | ≤ 0.011 | 0.006 | 0.004 row 5 : so3 | lb/hour | ≤ 1.1 | 0.43 | 0 row 6 : fluoride | lb/mmbtu | ≤ 1.57×10-4 | 1.06×10-4 | 0.95×10-4 row 7 : lead | lb/mmbtu | ≤ 2.6×10-5 | 0.56×10-5 | 0.59×10-5 row 8 : mercury | lb/mmbtu | ≤ 1.05×10-5 | 0.095×10-5 | 0.028×10-5 | col : count ( "*" ) row 1 : 1 | select count ( * ) where pollutant = 'nox' <table_name> : table \begin{tabular}{llllll}
\toprule
& pollutant & units & emission standard & coal-fired & petroleum coke-fired \\
\midrule
0 & so2 & lb/mmbtu & ≤ 0.15 & 0.0-0.04 & 0.03-0.13 \\
1 & nox & lb/mmbtu & ≤ 0.09 & 0.04-0.06 & 0.02 \\
2 & solid particulate & lb/mmbtu & ≤ 0.011 & 0.004 & 0.007 \\
3 & pm10 & lb/mmbtu & ≤ 0.011 & 0.006 & 0.004 \\
4 & so3 & lb/hour & ≤ 1.1 & 0.43 & 0 \\
5 & fluoride & lb/mmbtu & ≤ 1.57×10-4 & 1.06×10-4 & 0.95×10-4 \\
6 & lead & lb/mmbtu & ≤ 2.6×10-5 & 0.56×10-5 & 0.59×10-5 \\
7 & mercury & lb/mmbtu & ≤ 1.05×10-5 & 0.095×10-5 & 0.028×10-5 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where pollutant = 'nox' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pollutant</th>
<th>units</th>
<th>emission standard</th>
<th>coal-fired</th>
<th>petroleum coke-fired</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>so2</td>
<td>lb/mmbtu</td>
<td>≤ 0.15</td>
<td>0.0-0.04</td>
<td>0.03-0.13</td>
</tr>
<tr>
<th>1</th>
<td>nox</td>
<td>lb/mmbtu</td>
<td>≤ 0.09</td>
<td>0.04-0.06</td>
<td>0.02</td>
</tr>
<tr>
<th>2</th>
<td>solid particulate</td>
<td>lb/mmbtu</td>
<td>≤ 0.011</td>
<td>0.004</td>
<td>0.007</td>
</tr>
<tr>
<th>3</th>
<td>pm10</td>
<td>lb/mmbtu</td>
<td>≤ 0.011</td>
<td>0.006</td>
<td>0.004</td>
</tr>
<tr>
<th>4</th>
<td>so3</td>
<td>lb/hour</td>
<td>≤ 1.1</td>
<td>0.43</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>fluoride</td>
<td>lb/mmbtu</td>
<td>≤ 1.57×10-4</td>
<td>1.06×10-4</td>
<td>0.95×10-4</td>
</tr>
<tr>
<th>6</th>
<td>lead</td>
<td>lb/mmbtu</td>
<td>≤ 2.6×10-5</td>
<td>0.56×10-5</td>
<td>0.59×10-5</td>
</tr>
<tr>
<th>7</th>
<td>mercury</td>
<td>lb/mmbtu</td>
<td>≤ 1.05×10-5</td>
<td>0.095×10-5</td>
<td>0.028×10-5</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where pollutant = 'nox' <table_name> : table | | pollutant | units | emission standard | coal-fired | petroleum coke-fired |
|---:|:------------------|:---------|:--------------------|:-------------|:-----------------------|
| 0 | so2 | lb/mmbtu | ≤ 0.15 | 0.0-0.04 | 0.03-0.13 |
| 1 | nox | lb/mmbtu | ≤ 0.09 | 0.04-0.06 | 0.02 |
| 2 | solid particulate | lb/mmbtu | ≤ 0.011 | 0.004 | 0.007 |
| 3 | pm10 | lb/mmbtu | ≤ 0.011 | 0.006 | 0.004 |
| 4 | so3 | lb/hour | ≤ 1.1 | 0.43 | 0 |
| 5 | fluoride | lb/mmbtu | ≤ 1.57×10-4 | 1.06×10-4 | 0.95×10-4 |
| 6 | lead | lb/mmbtu | ≤ 2.6×10-5 | 0.56×10-5 | 0.59×10-5 |
| 7 | mercury | lb/mmbtu | ≤ 1.05×10-5 | 0.095×10-5 | 0.028×10-5 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select record where pct. = '0.882' col : tenure | coach | years | record | pct. row 1 : 1892 | shelby fletcher | 1 | 1-0 | 1.0 row 2 : 1893 | w. m. walker | 1 | 4-6-1 | 0.409 row 3 : 1894 | j. h. lyons | 1 | 10-3 | 0.769 row 4 : 1895 | j. f. jenkins | 1 | 9-3 | 0.75 row 5 : 1896 | eli abbott | 1 | 5-5 | 0.5 row 6 : 1897 | "kid" peeples | 1 | 10-0 | 1.0 row 7 : 1898 | joseph black | 1 | 2-3 | 0.4 row 8 : 1899 | f. c. owen | 1 | 3-6 | 0.333 row 9 : 1900 | ardis smith | 1 | 9-3 | 0.75 row 10 : 1901-1905 | thomas stouch | 5 | 49-25-1 | 0.66 row 11 : 1906 | schwartz | 1 | 4-16-1 | 0.214 row 12 : 1907-1910 | j. w. h. pollard | 4 | 66-22-1 | 0.747 row 13 : 1911 | guy lowman | 1 | 12-5 | 0.706 row 14 : 1912-1915 | d. v. graves | 4 | 66-30-1 | 0.686 row 15 : 1916-1919 | b. l. noojin | 4 | 55-18 | 0.753 row 16 : 1920 | gordon w. lewis | 1 | 15-2 | 0.882 row 17 : 1921-1923 | charles bernier | 3 | 28-35-4 | 0.448 row 18 : 1924-1927 | wallace wade | 4 | 61-32-2 | 0.653 row 19 : 1928 | hank crisp | 1 | 12-7-2 | 0.619 row 20 : 1929-1930 | jess neely | 2 | 28-15-2 | 0.644 row 21 : 1931-1932 | sam hinton | 2 | 23-7-2 | 0.75 row 22 : 1933-1934 | jennings b. whitworth | 2 | 21-11 | 0.656 row 23 : 1943 | paul burnham | 1 | 12-6 | 0.667 row 24 : 1946 | dixie howell | 1 | 13-7 | 0.65 row 25 : 1935-1942 1947-1963 | tilden campbell | 25 | 355-168-4 | 0.677 row 26 : 1964-1969 | joe sewell | 6 | 106-79 | 0.573 row 27 : 1970-1979 | hayden riley | 10 | 236-206-1 | 0.533 row 28 : 1980-1994 | barry shollenberger | 15 | 487-334-1 | 0.593 row 29 : 1995-2009 | jim wells | 15 | 625-322 | 0.656 row 30 : 2010-present | mitch gaspard | 4 | 133-115 | 0.536 row 31 : totals | 30 coaches | 121 seasons | 2,461-1,490-23 | 0.623 | col : record row 1 : 15-2 | select record where pct. = '0.882' <table_name> : table \begin{tabular}{llllll}
\toprule
& tenure & coach & years & record & pct. \\
\midrule
0 & 1892 & shelby fletcher & 1 & 1-0 & 1.0 \\
1 & 1893 & w. m. walker & 1 & 4-6-1 & 0.409 \\
2 & 1894 & j. h. lyons & 1 & 10-3 & 0.769 \\
3 & 1895 & j. f. jenkins & 1 & 9-3 & 0.75 \\
4 & 1896 & eli abbott & 1 & 5-5 & 0.5 \\
5 & 1897 & "kid" peeples & 1 & 10-0 & 1.0 \\
6 & 1898 & joseph black & 1 & 2-3 & 0.4 \\
7 & 1899 & f. c. owen & 1 & 3-6 & 0.333 \\
8 & 1900 & ardis smith & 1 & 9-3 & 0.75 \\
9 & 1901-1905 & thomas stouch & 5 & 49-25-1 & 0.66 \\
10 & 1906 & schwartz & 1 & 4-16-1 & 0.214 \\
11 & 1907-1910 & j. w. h. pollard & 4 & 66-22-1 & 0.747 \\
12 & 1911 & guy lowman & 1 & 12-5 & 0.706 \\
13 & 1912-1915 & d. v. graves & 4 & 66-30-1 & 0.686 \\
14 & 1916-1919 & b. l. noojin & 4 & 55-18 & 0.753 \\
15 & 1920 & gordon w. lewis & 1 & 15-2 & 0.882 \\
16 & 1921-1923 & charles bernier & 3 & 28-35-4 & 0.448 \\
17 & 1924-1927 & wallace wade & 4 & 61-32-2 & 0.653 \\
18 & 1928 & hank crisp & 1 & 12-7-2 & 0.619 \\
19 & 1929-1930 & jess neely & 2 & 28-15-2 & 0.644 \\
20 & 1931-1932 & sam hinton & 2 & 23-7-2 & 0.75 \\
21 & 1933-1934 & jennings b. whitworth & 2 & 21-11 & 0.656 \\
22 & 1943 & paul burnham & 1 & 12-6 & 0.667 \\
23 & 1946 & dixie howell & 1 & 13-7 & 0.65 \\
24 & 1935-1942 1947-1963 & tilden campbell & 25 & 355-168-4 & 0.677 \\
25 & 1964-1969 & joe sewell & 6 & 106-79 & 0.573 \\
26 & 1970-1979 & hayden riley & 10 & 236-206-1 & 0.533 \\
27 & 1980-1994 & barry shollenberger & 15 & 487-334-1 & 0.593 \\
28 & 1995-2009 & jim wells & 15 & 625-322 & 0.656 \\
29 & 2010-present & mitch gaspard & 4 & 133-115 & 0.536 \\
30 & totals & 30 coaches & 121 seasons & 2,461-1,490-23 & 0.623 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& record \\
\midrule
0 & 15-2 \\
\bottomrule
\end{tabular}
| select record where pct. = '0.882' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>tenure</th>
<th>coach</th>
<th>years</th>
<th>record</th>
<th>pct.</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1892</td>
<td>shelby fletcher</td>
<td>1</td>
<td>1-0</td>
<td>1.0</td>
</tr>
<tr>
<th>1</th>
<td>1893</td>
<td>w. m. walker</td>
<td>1</td>
<td>4-6-1</td>
<td>0.409</td>
</tr>
<tr>
<th>2</th>
<td>1894</td>
<td>j. h. lyons</td>
<td>1</td>
<td>10-3</td>
<td>0.769</td>
</tr>
<tr>
<th>3</th>
<td>1895</td>
<td>j. f. jenkins</td>
<td>1</td>
<td>9-3</td>
<td>0.75</td>
</tr>
<tr>
<th>4</th>
<td>1896</td>
<td>eli abbott</td>
<td>1</td>
<td>5-5</td>
<td>0.5</td>
</tr>
<tr>
<th>5</th>
<td>1897</td>
<td>"kid" peeples</td>
<td>1</td>
<td>10-0</td>
<td>1.0</td>
</tr>
<tr>
<th>6</th>
<td>1898</td>
<td>joseph black</td>
<td>1</td>
<td>2-3</td>
<td>0.4</td>
</tr>
<tr>
<th>7</th>
<td>1899</td>
<td>f. c. owen</td>
<td>1</td>
<td>3-6</td>
<td>0.333</td>
</tr>
<tr>
<th>8</th>
<td>1900</td>
<td>ardis smith</td>
<td>1</td>
<td>9-3</td>
<td>0.75</td>
</tr>
<tr>
<th>9</th>
<td>1901-1905</td>
<td>thomas stouch</td>
<td>5</td>
<td>49-25-1</td>
<td>0.66</td>
</tr>
<tr>
<th>10</th>
<td>1906</td>
<td>schwartz</td>
<td>1</td>
<td>4-16-1</td>
<td>0.214</td>
</tr>
<tr>
<th>11</th>
<td>1907-1910</td>
<td>j. w. h. pollard</td>
<td>4</td>
<td>66-22-1</td>
<td>0.747</td>
</tr>
<tr>
<th>12</th>
<td>1911</td>
<td>guy lowman</td>
<td>1</td>
<td>12-5</td>
<td>0.706</td>
</tr>
<tr>
<th>13</th>
<td>1912-1915</td>
<td>d. v. graves</td>
<td>4</td>
<td>66-30-1</td>
<td>0.686</td>
</tr>
<tr>
<th>14</th>
<td>1916-1919</td>
<td>b. l. noojin</td>
<td>4</td>
<td>55-18</td>
<td>0.753</td>
</tr>
<tr>
<th>15</th>
<td>1920</td>
<td>gordon w. lewis</td>
<td>1</td>
<td>15-2</td>
<td>0.882</td>
</tr>
<tr>
<th>16</th>
<td>1921-1923</td>
<td>charles bernier</td>
<td>3</td>
<td>28-35-4</td>
<td>0.448</td>
</tr>
<tr>
<th>17</th>
<td>1924-1927</td>
<td>wallace wade</td>
<td>4</td>
<td>61-32-2</td>
<td>0.653</td>
</tr>
<tr>
<th>18</th>
<td>1928</td>
<td>hank crisp</td>
<td>1</td>
<td>12-7-2</td>
<td>0.619</td>
</tr>
<tr>
<th>19</th>
<td>1929-1930</td>
<td>jess neely</td>
<td>2</td>
<td>28-15-2</td>
<td>0.644</td>
</tr>
<tr>
<th>20</th>
<td>1931-1932</td>
<td>sam hinton</td>
<td>2</td>
<td>23-7-2</td>
<td>0.75</td>
</tr>
<tr>
<th>21</th>
<td>1933-1934</td>
<td>jennings b. whitworth</td>
<td>2</td>
<td>21-11</td>
<td>0.656</td>
</tr>
<tr>
<th>22</th>
<td>1943</td>
<td>paul burnham</td>
<td>1</td>
<td>12-6</td>
<td>0.667</td>
</tr>
<tr>
<th>23</th>
<td>1946</td>
<td>dixie howell</td>
<td>1</td>
<td>13-7</td>
<td>0.65</td>
</tr>
<tr>
<th>24</th>
<td>1935-1942 1947-1963</td>
<td>tilden campbell</td>
<td>25</td>
<td>355-168-4</td>
<td>0.677</td>
</tr>
<tr>
<th>25</th>
<td>1964-1969</td>
<td>joe sewell</td>
<td>6</td>
<td>106-79</td>
<td>0.573</td>
</tr>
<tr>
<th>26</th>
<td>1970-1979</td>
<td>hayden riley</td>
<td>10</td>
<td>236-206-1</td>
<td>0.533</td>
</tr>
<tr>
<th>27</th>
<td>1980-1994</td>
<td>barry shollenberger</td>
<td>15</td>
<td>487-334-1</td>
<td>0.593</td>
</tr>
<tr>
<th>28</th>
<td>1995-2009</td>
<td>jim wells</td>
<td>15</td>
<td>625-322</td>
<td>0.656</td>
</tr>
<tr>
<th>29</th>
<td>2010-present</td>
<td>mitch gaspard</td>
<td>4</td>
<td>133-115</td>
<td>0.536</td>
</tr>
<tr>
<th>30</th>
<td>totals</td>
<td>30 coaches</td>
<td>121 seasons</td>
<td>2,461-1,490-23</td>
<td>0.623</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>15-2</td>
</tr>
</tbody>
</table> | select record where pct. = '0.882' <table_name> : table | | tenure | coach | years | record | pct. |
|---:|:--------------------|:----------------------|:------------|:---------------|-------:|
| 0 | 1892 | shelby fletcher | 1 | 1-0 | 1 |
| 1 | 1893 | w. m. walker | 1 | 4-6-1 | 0.409 |
| 2 | 1894 | j. h. lyons | 1 | 10-3 | 0.769 |
| 3 | 1895 | j. f. jenkins | 1 | 9-3 | 0.75 |
| 4 | 1896 | eli abbott | 1 | 5-5 | 0.5 |
| 5 | 1897 | "kid" peeples | 1 | 10-0 | 1 |
| 6 | 1898 | joseph black | 1 | 2-3 | 0.4 |
| 7 | 1899 | f. c. owen | 1 | 3-6 | 0.333 |
| 8 | 1900 | ardis smith | 1 | 9-3 | 0.75 |
| 9 | 1901-1905 | thomas stouch | 5 | 49-25-1 | 0.66 |
| 10 | 1906 | schwartz | 1 | 4-16-1 | 0.214 |
| 11 | 1907-1910 | j. w. h. pollard | 4 | 66-22-1 | 0.747 |
| 12 | 1911 | guy lowman | 1 | 12-5 | 0.706 |
| 13 | 1912-1915 | d. v. graves | 4 | 66-30-1 | 0.686 |
| 14 | 1916-1919 | b. l. noojin | 4 | 55-18 | 0.753 |
| 15 | 1920 | gordon w. lewis | 1 | 15-2 | 0.882 |
| 16 | 1921-1923 | charles bernier | 3 | 28-35-4 | 0.448 |
| 17 | 1924-1927 | wallace wade | 4 | 61-32-2 | 0.653 |
| 18 | 1928 | hank crisp | 1 | 12-7-2 | 0.619 |
| 19 | 1929-1930 | jess neely | 2 | 28-15-2 | 0.644 |
| 20 | 1931-1932 | sam hinton | 2 | 23-7-2 | 0.75 |
| 21 | 1933-1934 | jennings b. whitworth | 2 | 21-11 | 0.656 |
| 22 | 1943 | paul burnham | 1 | 12-6 | 0.667 |
| 23 | 1946 | dixie howell | 1 | 13-7 | 0.65 |
| 24 | 1935-1942 1947-1963 | tilden campbell | 25 | 355-168-4 | 0.677 |
| 25 | 1964-1969 | joe sewell | 6 | 106-79 | 0.573 |
| 26 | 1970-1979 | hayden riley | 10 | 236-206-1 | 0.533 |
| 27 | 1980-1994 | barry shollenberger | 15 | 487-334-1 | 0.593 |
| 28 | 1995-2009 | jim wells | 15 | 625-322 | 0.656 |
| 29 | 2010-present | mitch gaspard | 4 | 133-115 | 0.536 |
| 30 | totals | 30 coaches | 121 seasons | 2,461-1,490-23 | 0.623 | | | | record |
|---:|:---------|
| 0 | 15-2 | | [
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select count ( score ) where opponent in the final = 8 col : no. | date | tournament | surface | partnering | opponent in the final | score row 1 : 1 | 2010-09-13 00:00:00 | ecuador f2 | hard | roberto quiroz | peter aarts christopher racz | 6-4, 6-4 row 2 : 2 | 2011-04-04 00:00:00 | chile f2 | clay | sergio galdos | guillermo hormazabal rodrigo perez | 5-7, 7-6(5), [10-5] row 3 : 3 | 2011-04-11 00:00:00 | chile f3 | clay | roberto quiroz | luis david martinez miguel angel reyes-varela | 6-4, 7-5 row 4 : 4 | 2011-08-08 00:00:00 | peru f1 | clay | sergio galdos | martin cuevas guido pella | 6-4, 6-0 row 5 : 5 | 2012-08-05 00:00:00 | manta | hard | renzo olivo | victor estrella joao souza | 6-3, 6-0 row 6 : 6 | 2012-08-20 00:00:00 | colombia f2 | clay | ariel behar | nicolas barrientos michael quintero | 2-1 ret row 7 : 7 | 2012-08-26 00:00:00 | ecuador f3 | clay | sergio galdos | mauricio echazu guillermo rivera-aranguiz | 6-2, 6-1 row 8 : 8 | 2012-10-08 00:00:00 | chile f8 | clay | gustavo sterin | cristobal saavedra-corvalan guillermo rivera-aranguiz | 6-4, 7-5 row 9 : 9 | 2013-05-13 00:00:00 | argentina f6 | clay | sergio galdos | franco agamenone jose angel carrizo | 4-6, 6-4, [10-1] row 10 : 10 | 2013-05-27 00:00:00 | argentina f8 | clay | sergio galdos | daniel dutra da silva pablo galdon | 6-0, 7-5 | col : count ( "score" ) row 1 : 0 | select count ( score ) where opponent in the final = 8 <table_name> : table \begin{tabular}{llllllll}
\toprule
& no. & date & tournament & surface & partnering & opponent in the final & score \\
\midrule
0 & 1 & 2010-09-13 00:00:00 & ecuador f2 & hard & roberto quiroz & peter aarts christopher racz & 6-4, 6-4 \\
1 & 2 & 2011-04-04 00:00:00 & chile f2 & clay & sergio galdos & guillermo hormazabal rodrigo perez & 5-7, 7-6(5), [10-5] \\
2 & 3 & 2011-04-11 00:00:00 & chile f3 & clay & roberto quiroz & luis david martinez miguel angel reyes-varela & 6-4, 7-5 \\
3 & 4 & 2011-08-08 00:00:00 & peru f1 & clay & sergio galdos & martin cuevas guido pella & 6-4, 6-0 \\
4 & 5 & 2012-08-05 00:00:00 & manta & hard & renzo olivo & victor estrella joao souza & 6-3, 6-0 \\
5 & 6 & 2012-08-20 00:00:00 & colombia f2 & clay & ariel behar & nicolas barrientos michael quintero & 2-1 ret \\
6 & 7 & 2012-08-26 00:00:00 & ecuador f3 & clay & sergio galdos & mauricio echazu guillermo rivera-aranguiz & 6-2, 6-1 \\
7 & 8 & 2012-10-08 00:00:00 & chile f8 & clay & gustavo sterin & cristobal saavedra-corvalan guillermo rivera-aranguiz & 6-4, 7-5 \\
8 & 9 & 2013-05-13 00:00:00 & argentina f6 & clay & sergio galdos & franco agamenone jose angel carrizo & 4-6, 6-4, [10-1] \\
9 & 10 & 2013-05-27 00:00:00 & argentina f8 & clay & sergio galdos & daniel dutra da silva pablo galdon & 6-0, 7-5 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "score" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( score ) where opponent in the final = 8 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no.</th>
<th>date</th>
<th>tournament</th>
<th>surface</th>
<th>partnering</th>
<th>opponent in the final</th>
<th>score</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2010-09-13 00:00:00</td>
<td>ecuador f2</td>
<td>hard</td>
<td>roberto quiroz</td>
<td>peter aarts christopher racz</td>
<td>6-4, 6-4</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2011-04-04 00:00:00</td>
<td>chile f2</td>
<td>clay</td>
<td>sergio galdos</td>
<td>guillermo hormazabal rodrigo perez</td>
<td>5-7, 7-6(5), [10-5]</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2011-04-11 00:00:00</td>
<td>chile f3</td>
<td>clay</td>
<td>roberto quiroz</td>
<td>luis david martinez miguel angel reyes-varela</td>
<td>6-4, 7-5</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2011-08-08 00:00:00</td>
<td>peru f1</td>
<td>clay</td>
<td>sergio galdos</td>
<td>martin cuevas guido pella</td>
<td>6-4, 6-0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2012-08-05 00:00:00</td>
<td>manta</td>
<td>hard</td>
<td>renzo olivo</td>
<td>victor estrella joao souza</td>
<td>6-3, 6-0</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2012-08-20 00:00:00</td>
<td>colombia f2</td>
<td>clay</td>
<td>ariel behar</td>
<td>nicolas barrientos michael quintero</td>
<td>2-1 ret</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2012-08-26 00:00:00</td>
<td>ecuador f3</td>
<td>clay</td>
<td>sergio galdos</td>
<td>mauricio echazu guillermo rivera-aranguiz</td>
<td>6-2, 6-1</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2012-10-08 00:00:00</td>
<td>chile f8</td>
<td>clay</td>
<td>gustavo sterin</td>
<td>cristobal saavedra-corvalan guillermo rivera-aranguiz</td>
<td>6-4, 7-5</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2013-05-13 00:00:00</td>
<td>argentina f6</td>
<td>clay</td>
<td>sergio galdos</td>
<td>franco agamenone jose angel carrizo</td>
<td>4-6, 6-4, [10-1]</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2013-05-27 00:00:00</td>
<td>argentina f8</td>
<td>clay</td>
<td>sergio galdos</td>
<td>daniel dutra da silva pablo galdon</td>
<td>6-0, 7-5</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "score" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( score ) where opponent in the final = 8 <table_name> : table | | no. | date | tournament | surface | partnering | opponent in the final | score |
|---:|------:|:--------------------|:-------------|:----------|:---------------|:------------------------------------------------------|:--------------------|
| 0 | 1 | 2010-09-13 00:00:00 | ecuador f2 | hard | roberto quiroz | peter aarts christopher racz | 6-4, 6-4 |
| 1 | 2 | 2011-04-04 00:00:00 | chile f2 | clay | sergio galdos | guillermo hormazabal rodrigo perez | 5-7, 7-6(5), [10-5] |
| 2 | 3 | 2011-04-11 00:00:00 | chile f3 | clay | roberto quiroz | luis david martinez miguel angel reyes-varela | 6-4, 7-5 |
| 3 | 4 | 2011-08-08 00:00:00 | peru f1 | clay | sergio galdos | martin cuevas guido pella | 6-4, 6-0 |
| 4 | 5 | 2012-08-05 00:00:00 | manta | hard | renzo olivo | victor estrella joao souza | 6-3, 6-0 |
| 5 | 6 | 2012-08-20 00:00:00 | colombia f2 | clay | ariel behar | nicolas barrientos michael quintero | 2-1 ret |
| 6 | 7 | 2012-08-26 00:00:00 | ecuador f3 | clay | sergio galdos | mauricio echazu guillermo rivera-aranguiz | 6-2, 6-1 |
| 7 | 8 | 2012-10-08 00:00:00 | chile f8 | clay | gustavo sterin | cristobal saavedra-corvalan guillermo rivera-aranguiz | 6-4, 7-5 |
| 8 | 9 | 2013-05-13 00:00:00 | argentina f6 | clay | sergio galdos | franco agamenone jose angel carrizo | 4-6, 6-4, [10-1] |
| 9 | 10 | 2013-05-27 00:00:00 | argentina f8 | clay | sergio galdos | daniel dutra da silva pablo galdon | 6-0, 7-5 | | | | count ( "score" ) |
|---:|--------------------:|
| 0 | 0 | | [
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select ( select count ( * ) where bronze < 6 ) > ( select count ( * ) where bronze > 6 ) col : rank | nation | gold | silver | bronze | total row 1 : 1 | soviet union | 7 | 3 | 6 | 16 row 2 : 2 | austria | 4 | 3 | 4 | 11 row 3 : 3 | finland | 3 | 3 | 1 | 7 row 4 : 4 | switzerland | 3 | 2 | 1 | 6 row 5 : 5 | sweden | 2 | 4 | 4 | 10 row 6 : 6 | united states | 2 | 3 | 2 | 7 row 7 : 7 | norway | 2 | 1 | 1 | 4 row 8 : 8 | italy | 1 | 2 | 0 | 3 row 9 : 9 | germany | 1 | 0 | 1 | 2 row 10 : 10 | canada | 0 | 1 | 2 | 3 | col : count ( "select count ( *" ) row 1 : 10 | select ( select count ( * ) where bronze < 6 ) > ( select count ( * ) where bronze > 6 ) <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & soviet union & 7 & 3 & 6 & 16 \\
1 & 2 & austria & 4 & 3 & 4 & 11 \\
2 & 3 & finland & 3 & 3 & 1 & 7 \\
3 & 4 & switzerland & 3 & 2 & 1 & 6 \\
4 & 5 & sweden & 2 & 4 & 4 & 10 \\
5 & 6 & united states & 2 & 3 & 2 & 7 \\
6 & 7 & norway & 2 & 1 & 1 & 4 \\
7 & 8 & italy & 1 & 2 & 0 & 3 \\
8 & 9 & germany & 1 & 0 & 1 & 2 \\
9 & 10 & canada & 0 & 1 & 2 & 3 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "select count ( *" ) \\
\midrule
0 & 10 \\
\bottomrule
\end{tabular}
| select ( select count ( * ) where bronze < 6 ) > ( select count ( * ) where bronze > 6 ) <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>soviet union</td>
<td>7</td>
<td>3</td>
<td>6</td>
<td>16</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>austria</td>
<td>4</td>
<td>3</td>
<td>4</td>
<td>11</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>finland</td>
<td>3</td>
<td>3</td>
<td>1</td>
<td>7</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>switzerland</td>
<td>3</td>
<td>2</td>
<td>1</td>
<td>6</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>sweden</td>
<td>2</td>
<td>4</td>
<td>4</td>
<td>10</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>united states</td>
<td>2</td>
<td>3</td>
<td>2</td>
<td>7</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>norway</td>
<td>2</td>
<td>1</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>italy</td>
<td>1</td>
<td>2</td>
<td>0</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>germany</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>canada</td>
<td>0</td>
<td>1</td>
<td>2</td>
<td>3</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "select count ( *" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>10</td>
</tr>
</tbody>
</table> | select ( select count ( * ) where bronze < 6 ) > ( select count ( * ) where bronze > 6 ) <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|-------:|:--------------|-------:|---------:|---------:|--------:|
| 0 | 1 | soviet union | 7 | 3 | 6 | 16 |
| 1 | 2 | austria | 4 | 3 | 4 | 11 |
| 2 | 3 | finland | 3 | 3 | 1 | 7 |
| 3 | 4 | switzerland | 3 | 2 | 1 | 6 |
| 4 | 5 | sweden | 2 | 4 | 4 | 10 |
| 5 | 6 | united states | 2 | 3 | 2 | 7 |
| 6 | 7 | norway | 2 | 1 | 1 | 4 |
| 7 | 8 | italy | 1 | 2 | 0 | 3 |
| 8 | 9 | germany | 1 | 0 | 1 | 2 |
| 9 | 10 | canada | 0 | 1 | 2 | 3 | | | | count ( "select count ( *" ) |
|---:|-------------------------------:|
| 0 | 10 | | [
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select count ( team ) where team = 'phi' col : year | team | games | combined tackles | tackles | assisted tackles | sacks | forced fumbles | fumble recoveries | fumble return yards | interceptions | interception return yards | yards per interception return | longest interception return | interceptions returned for touchdown | passes defended row 1 : 2004 | hou | 16 | 63 | 51 | 12 | 4.0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 4 row 2 : 2005 | hou | 12 | 35 | 24 | 11 | 4.0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 row 3 : 2006 | hou | 15 | 26 | 19 | 7 | 5.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 row 4 : 2008 | kc | 7 | 31 | 25 | 6 | 2.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 5 : 2008 | sea | 2 | 1 | 1 | 0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 6 : 2009 | phi | 12 | 16 | 11 | 5 | 2.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 7 : 2010 | ten | 16 | 58 | 44 | 14 | 12.5 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 8 : 2011 | phi | 16 | 40 | 35 | 5 | 18.0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 row 9 : 2012 | phi | 11 | 26 | 21 | 5 | 5.5 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 row 10 : 2012 | jax | 5 | 11 | 7 | 4 | 1.5 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 11 : 2013 | jax | 16 | 40 | 31 | 9 | 7.5 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 row 12 : career | none | 128 | 347 | 269 | 78 | 62.5 | 14 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | col : count ( "team" ) row 1 : 3 | select count ( team ) where team = 'phi' <table_name> : table \begin{tabular}{lllllllllllllllll}
\toprule
& year & team & games & combined tackles & tackles & assisted tackles & sacks & forced fumbles & fumble recoveries & fumble return yards & interceptions & interception return yards & yards per interception return & longest interception return & interceptions returned for touchdown & passes defended \\
\midrule
0 & 2004 & hou & 16 & 63 & 51 & 12 & 4.0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 4 \\
1 & 2005 & hou & 12 & 35 & 24 & 11 & 4.0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 \\
2 & 2006 & hou & 15 & 26 & 19 & 7 & 5.0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 \\
3 & 2008 & kc & 7 & 31 & 25 & 6 & 2.0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
4 & 2008 & sea & 2 & 1 & 1 & 0 & 0.0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
5 & 2009 & phi & 12 & 16 & 11 & 5 & 2.5 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
6 & 2010 & ten & 16 & 58 & 44 & 14 & 12.5 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
7 & 2011 & phi & 16 & 40 & 35 & 5 & 18.0 & 3 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\
8 & 2012 & phi & 11 & 26 & 21 & 5 & 5.5 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\
9 & 2012 & jax & 5 & 11 & 7 & 4 & 1.5 & 2 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
10 & 2013 & jax & 16 & 40 & 31 & 9 & 7.5 & 3 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
11 & career & none & 128 & 347 & 269 & 78 & 62.5 & 14 & 3 & 0 & 0 & 0 & 0 & 0 & 0 & 9 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "team" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( team ) where team = 'phi' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>team</th>
<th>games</th>
<th>combined tackles</th>
<th>tackles</th>
<th>assisted tackles</th>
<th>sacks</th>
<th>forced fumbles</th>
<th>fumble recoveries</th>
<th>fumble return yards</th>
<th>interceptions</th>
<th>interception return yards</th>
<th>yards per interception return</th>
<th>longest interception return</th>
<th>interceptions returned for touchdown</th>
<th>passes defended</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004</td>
<td>hou</td>
<td>16</td>
<td>63</td>
<td>51</td>
<td>12</td>
<td>4.0</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>4</td>
</tr>
<tr>
<th>1</th>
<td>2005</td>
<td>hou</td>
<td>12</td>
<td>35</td>
<td>24</td>
<td>11</td>
<td>4.0</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>2</th>
<td>2006</td>
<td>hou</td>
<td>15</td>
<td>26</td>
<td>19</td>
<td>7</td>
<td>5.0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>3</th>
<td>2008</td>
<td>kc</td>
<td>7</td>
<td>31</td>
<td>25</td>
<td>6</td>
<td>2.0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>2008</td>
<td>sea</td>
<td>2</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>0.0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>2009</td>
<td>phi</td>
<td>12</td>
<td>16</td>
<td>11</td>
<td>5</td>
<td>2.5</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>2010</td>
<td>ten</td>
<td>16</td>
<td>58</td>
<td>44</td>
<td>14</td>
<td>12.5</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>2011</td>
<td>phi</td>
<td>16</td>
<td>40</td>
<td>35</td>
<td>5</td>
<td>18.0</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>2012</td>
<td>phi</td>
<td>11</td>
<td>26</td>
<td>21</td>
<td>5</td>
<td>5.5</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>2012</td>
<td>jax</td>
<td>5</td>
<td>11</td>
<td>7</td>
<td>4</td>
<td>1.5</td>
<td>2</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>10</th>
<td>2013</td>
<td>jax</td>
<td>16</td>
<td>40</td>
<td>31</td>
<td>9</td>
<td>7.5</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>11</th>
<td>career</td>
<td>none</td>
<td>128</td>
<td>347</td>
<td>269</td>
<td>78</td>
<td>62.5</td>
<td>14</td>
<td>3</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>0</td>
<td>9</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "team" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( team ) where team = 'phi' <table_name> : table | | year | team | games | combined tackles | tackles | assisted tackles | sacks | forced fumbles | fumble recoveries | fumble return yards | interceptions | interception return yards | yards per interception return | longest interception return | interceptions returned for touchdown | passes defended |
|---:|:-------|:-------|--------:|-------------------:|----------:|-------------------:|--------:|-----------------:|--------------------:|----------------------:|----------------:|----------------------------:|--------------------------------:|------------------------------:|---------------------------------------:|------------------:|
| 0 | 2004 | hou | 16 | 63 | 51 | 12 | 4 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
| 1 | 2005 | hou | 12 | 35 | 24 | 11 | 4 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
| 2 | 2006 | hou | 15 | 26 | 19 | 7 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
| 3 | 2008 | kc | 7 | 31 | 25 | 6 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4 | 2008 | sea | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 5 | 2009 | phi | 12 | 16 | 11 | 5 | 2.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 6 | 2010 | ten | 16 | 58 | 44 | 14 | 12.5 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 7 | 2011 | phi | 16 | 40 | 35 | 5 | 18 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 8 | 2012 | phi | 11 | 26 | 21 | 5 | 5.5 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 9 | 2012 | jax | 5 | 11 | 7 | 4 | 1.5 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 10 | 2013 | jax | 16 | 40 | 31 | 9 | 7.5 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 11 | career | none | 128 | 347 | 269 | 78 | 62.5 | 14 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | | | | count ( "team" ) |
|---:|-------------------:|
| 0 | 3 | | [
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] |
select count ( * ) where division = 'regional' col : season | tier | division | place row 1 : 1981/82 | 4 | 3a | 17th row 2 : 1982/83 | 5 | regional | none row 3 : 1983/84 | 4 | 3a | 1st row 4 : 1984/85 | 4 | 3a | 2nd row 5 : 1985/86 | 4 | 3a | 1st row 6 : 1986/87 | 3 | 2ab | 10th row 7 : 1987/88 | 3 | 2ab | 1st row 8 : 1988/89 | 2 | 2a | 18th row 9 : 1989/90 | 3 | 2ab | 7th row 10 : 1990/91 | 3 | 2ab | 8th row 11 : 1991/92 | 3 | 2ab | 20th row 12 : 1992/93 | 4 | 3a | 14th row 13 : 1993/94 | 4 | 3a | 19th row 14 : 1994/95 | 5 | reg. pref | 9th row 15 : 1995/96 | 5 | reg. pref | 4th row 16 : 1996/97 | 5 | reg. pref | 1st row 17 : 1997/98 | 5 | reg. pref | 2nd | col : count ( "*" ) row 1 : 1 | select count ( * ) where division = 'regional' <table_name> : table \begin{tabular}{lllll}
\toprule
& season & tier & division & place \\
\midrule
0 & 1981/82 & 4 & 3a & 17th \\
1 & 1982/83 & 5 & regional & none \\
2 & 1983/84 & 4 & 3a & 1st \\
3 & 1984/85 & 4 & 3a & 2nd \\
4 & 1985/86 & 4 & 3a & 1st \\
5 & 1986/87 & 3 & 2ab & 10th \\
6 & 1987/88 & 3 & 2ab & 1st \\
7 & 1988/89 & 2 & 2a & 18th \\
8 & 1989/90 & 3 & 2ab & 7th \\
9 & 1990/91 & 3 & 2ab & 8th \\
10 & 1991/92 & 3 & 2ab & 20th \\
11 & 1992/93 & 4 & 3a & 14th \\
12 & 1993/94 & 4 & 3a & 19th \\
13 & 1994/95 & 5 & reg. pref & 9th \\
14 & 1995/96 & 5 & reg. pref & 4th \\
15 & 1996/97 & 5 & reg. pref & 1st \\
16 & 1997/98 & 5 & reg. pref & 2nd \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where division = 'regional' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>tier</th>
<th>division</th>
<th>place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1981/82</td>
<td>4</td>
<td>3a</td>
<td>17th</td>
</tr>
<tr>
<th>1</th>
<td>1982/83</td>
<td>5</td>
<td>regional</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1983/84</td>
<td>4</td>
<td>3a</td>
<td>1st</td>
</tr>
<tr>
<th>3</th>
<td>1984/85</td>
<td>4</td>
<td>3a</td>
<td>2nd</td>
</tr>
<tr>
<th>4</th>
<td>1985/86</td>
<td>4</td>
<td>3a</td>
<td>1st</td>
</tr>
<tr>
<th>5</th>
<td>1986/87</td>
<td>3</td>
<td>2ab</td>
<td>10th</td>
</tr>
<tr>
<th>6</th>
<td>1987/88</td>
<td>3</td>
<td>2ab</td>
<td>1st</td>
</tr>
<tr>
<th>7</th>
<td>1988/89</td>
<td>2</td>
<td>2a</td>
<td>18th</td>
</tr>
<tr>
<th>8</th>
<td>1989/90</td>
<td>3</td>
<td>2ab</td>
<td>7th</td>
</tr>
<tr>
<th>9</th>
<td>1990/91</td>
<td>3</td>
<td>2ab</td>
<td>8th</td>
</tr>
<tr>
<th>10</th>
<td>1991/92</td>
<td>3</td>
<td>2ab</td>
<td>20th</td>
</tr>
<tr>
<th>11</th>
<td>1992/93</td>
<td>4</td>
<td>3a</td>
<td>14th</td>
</tr>
<tr>
<th>12</th>
<td>1993/94</td>
<td>4</td>
<td>3a</td>
<td>19th</td>
</tr>
<tr>
<th>13</th>
<td>1994/95</td>
<td>5</td>
<td>reg. pref</td>
<td>9th</td>
</tr>
<tr>
<th>14</th>
<td>1995/96</td>
<td>5</td>
<td>reg. pref</td>
<td>4th</td>
</tr>
<tr>
<th>15</th>
<td>1996/97</td>
<td>5</td>
<td>reg. pref</td>
<td>1st</td>
</tr>
<tr>
<th>16</th>
<td>1997/98</td>
<td>5</td>
<td>reg. pref</td>
<td>2nd</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where division = 'regional' <table_name> : table | | season | tier | division | place |
|---:|:---------|-------:|:-----------|:--------|
| 0 | 1981/82 | 4 | 3a | 17th |
| 1 | 1982/83 | 5 | regional | none |
| 2 | 1983/84 | 4 | 3a | 1st |
| 3 | 1984/85 | 4 | 3a | 2nd |
| 4 | 1985/86 | 4 | 3a | 1st |
| 5 | 1986/87 | 3 | 2ab | 10th |
| 6 | 1987/88 | 3 | 2ab | 1st |
| 7 | 1988/89 | 2 | 2a | 18th |
| 8 | 1989/90 | 3 | 2ab | 7th |
| 9 | 1990/91 | 3 | 2ab | 8th |
| 10 | 1991/92 | 3 | 2ab | 20th |
| 11 | 1992/93 | 4 | 3a | 14th |
| 12 | 1993/94 | 4 | 3a | 19th |
| 13 | 1994/95 | 5 | reg. pref | 9th |
| 14 | 1995/96 | 5 | reg. pref | 4th |
| 15 | 1996/97 | 5 | reg. pref | 1st |
| 16 | 1997/98 | 5 | reg. pref | 2nd | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where builder = 'hm dockyard, devonport' col : name | pennant | namesake | builder | ordered | laid down | launched | commissioned | fate row 1 : leander | 75 | leander of abydos | hm dockyard, devonport | 18 february 1928 | 1 august 1928 | 13 july 1929 | 23 july 1931 | transferred to royal new zealand navy as hmnzs leander 1941-1945 broken up at blyth 1950 row 2 : orion | 85 | orion the hunter | hm dockyard, devonport | 24 march 1931 | 26 september 1931 | 24 november 1932 | 18 january 1934 | broken up at dalmuir, 1949 row 3 : neptune | 20 | neptune, god of the sea | hm dockyard, portsmouth | 2 march 1931 | 24 september 1931 | 31 january 1933 | 23 february 1934 | sunk in minefield off tripoli, 19 december 1941 row 4 : ajax | 22 | ajax the great | vickers armstrong | 1 october 1932 | 7 february 1933 | 1 march 1934 | 12 april 1935 | broken up at newport, 1949 row 5 : achilles | 70 | achilles | cammell laird | 16 february 1931 | 11 june 1931 | 1 september 1932 | 24 march 1936 | transferred to royal new zealand navy as hmnzs achilles 1941-1946 sold to indian navy as hims delhi 1948 row 6 : amphion | 29 | amphion of thebes | hm dockyard, portsmouth | 1 december 1932 | 22 june 1933 | 27 july 1934 | 15 june 1936 | sold to royal australian navy as hmas perth, 1939 sunk in torpedo attack, 1 march 1942 row 7 : apollo | 63 | apollo, god of light | hm dockyard, devonport | 1 march 1933 | 15 august 1933 | 9 october 1934 | 13 january 1936 | sold to royal australian navy as hmas hobart, 1938 broken up at osaka, 1962 row 8 : sydney (ex-phaeton) | 48 | city of sydney | swan hunter | 10 february 1933 | 8 july 1933 | 22 september 1934 | 24 september 1935 | sunk in surface action, 19 november 1941 | col : count ( "*" ) row 1 : 3 | select count ( * ) where builder = 'hm dockyard, devonport' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& name & pennant & namesake & builder & ordered & laid down & launched & commissioned & fate \\
\midrule
0 & leander & 75 & leander of abydos & hm dockyard, devonport & 18 february 1928 & 1 august 1928 & 13 july 1929 & 23 july 1931 & transferred to royal new zealand navy as hmnzs leander 1941-1945 broken up at blyth 1950 \\
1 & orion & 85 & orion the hunter & hm dockyard, devonport & 24 march 1931 & 26 september 1931 & 24 november 1932 & 18 january 1934 & broken up at dalmuir, 1949 \\
2 & neptune & 20 & neptune, god of the sea & hm dockyard, portsmouth & 2 march 1931 & 24 september 1931 & 31 january 1933 & 23 february 1934 & sunk in minefield off tripoli, 19 december 1941 \\
3 & ajax & 22 & ajax the great & vickers armstrong & 1 october 1932 & 7 february 1933 & 1 march 1934 & 12 april 1935 & broken up at newport, 1949 \\
4 & achilles & 70 & achilles & cammell laird & 16 february 1931 & 11 june 1931 & 1 september 1932 & 24 march 1936 & transferred to royal new zealand navy as hmnzs achilles 1941-1946 sold to indian navy as hims delhi 1948 \\
5 & amphion & 29 & amphion of thebes & hm dockyard, portsmouth & 1 december 1932 & 22 june 1933 & 27 july 1934 & 15 june 1936 & sold to royal australian navy as hmas perth, 1939 sunk in torpedo attack, 1 march 1942 \\
6 & apollo & 63 & apollo, god of light & hm dockyard, devonport & 1 march 1933 & 15 august 1933 & 9 october 1934 & 13 january 1936 & sold to royal australian navy as hmas hobart, 1938 broken up at osaka, 1962 \\
7 & sydney (ex-phaeton) & 48 & city of sydney & swan hunter & 10 february 1933 & 8 july 1933 & 22 september 1934 & 24 september 1935 & sunk in surface action, 19 november 1941 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( * ) where builder = 'hm dockyard, devonport' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>pennant</th>
<th>namesake</th>
<th>builder</th>
<th>ordered</th>
<th>laid down</th>
<th>launched</th>
<th>commissioned</th>
<th>fate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>leander</td>
<td>75</td>
<td>leander of abydos</td>
<td>hm dockyard, devonport</td>
<td>18 february 1928</td>
<td>1 august 1928</td>
<td>13 july 1929</td>
<td>23 july 1931</td>
<td>transferred to royal new zealand navy as hmnzs leander 1941-1945 broken up at blyth 1950</td>
</tr>
<tr>
<th>1</th>
<td>orion</td>
<td>85</td>
<td>orion the hunter</td>
<td>hm dockyard, devonport</td>
<td>24 march 1931</td>
<td>26 september 1931</td>
<td>24 november 1932</td>
<td>18 january 1934</td>
<td>broken up at dalmuir, 1949</td>
</tr>
<tr>
<th>2</th>
<td>neptune</td>
<td>20</td>
<td>neptune, god of the sea</td>
<td>hm dockyard, portsmouth</td>
<td>2 march 1931</td>
<td>24 september 1931</td>
<td>31 january 1933</td>
<td>23 february 1934</td>
<td>sunk in minefield off tripoli, 19 december 1941</td>
</tr>
<tr>
<th>3</th>
<td>ajax</td>
<td>22</td>
<td>ajax the great</td>
<td>vickers armstrong</td>
<td>1 october 1932</td>
<td>7 february 1933</td>
<td>1 march 1934</td>
<td>12 april 1935</td>
<td>broken up at newport, 1949</td>
</tr>
<tr>
<th>4</th>
<td>achilles</td>
<td>70</td>
<td>achilles</td>
<td>cammell laird</td>
<td>16 february 1931</td>
<td>11 june 1931</td>
<td>1 september 1932</td>
<td>24 march 1936</td>
<td>transferred to royal new zealand navy as hmnzs achilles 1941-1946 sold to indian navy as hims delhi 1948</td>
</tr>
<tr>
<th>5</th>
<td>amphion</td>
<td>29</td>
<td>amphion of thebes</td>
<td>hm dockyard, portsmouth</td>
<td>1 december 1932</td>
<td>22 june 1933</td>
<td>27 july 1934</td>
<td>15 june 1936</td>
<td>sold to royal australian navy as hmas perth, 1939 sunk in torpedo attack, 1 march 1942</td>
</tr>
<tr>
<th>6</th>
<td>apollo</td>
<td>63</td>
<td>apollo, god of light</td>
<td>hm dockyard, devonport</td>
<td>1 march 1933</td>
<td>15 august 1933</td>
<td>9 october 1934</td>
<td>13 january 1936</td>
<td>sold to royal australian navy as hmas hobart, 1938 broken up at osaka, 1962</td>
</tr>
<tr>
<th>7</th>
<td>sydney (ex-phaeton)</td>
<td>48</td>
<td>city of sydney</td>
<td>swan hunter</td>
<td>10 february 1933</td>
<td>8 july 1933</td>
<td>22 september 1934</td>
<td>24 september 1935</td>
<td>sunk in surface action, 19 november 1941</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( * ) where builder = 'hm dockyard, devonport' <table_name> : table | | name | pennant | namesake | builder | ordered | laid down | launched | commissioned | fate |
|---:|:--------------------|----------:|:------------------------|:------------------------|:-----------------|:------------------|:------------------|:------------------|:---------------------------------------------------------------------------------------------------------|
| 0 | leander | 75 | leander of abydos | hm dockyard, devonport | 18 february 1928 | 1 august 1928 | 13 july 1929 | 23 july 1931 | transferred to royal new zealand navy as hmnzs leander 1941-1945 broken up at blyth 1950 |
| 1 | orion | 85 | orion the hunter | hm dockyard, devonport | 24 march 1931 | 26 september 1931 | 24 november 1932 | 18 january 1934 | broken up at dalmuir, 1949 |
| 2 | neptune | 20 | neptune, god of the sea | hm dockyard, portsmouth | 2 march 1931 | 24 september 1931 | 31 january 1933 | 23 february 1934 | sunk in minefield off tripoli, 19 december 1941 |
| 3 | ajax | 22 | ajax the great | vickers armstrong | 1 october 1932 | 7 february 1933 | 1 march 1934 | 12 april 1935 | broken up at newport, 1949 |
| 4 | achilles | 70 | achilles | cammell laird | 16 february 1931 | 11 june 1931 | 1 september 1932 | 24 march 1936 | transferred to royal new zealand navy as hmnzs achilles 1941-1946 sold to indian navy as hims delhi 1948 |
| 5 | amphion | 29 | amphion of thebes | hm dockyard, portsmouth | 1 december 1932 | 22 june 1933 | 27 july 1934 | 15 june 1936 | sold to royal australian navy as hmas perth, 1939 sunk in torpedo attack, 1 march 1942 |
| 6 | apollo | 63 | apollo, god of light | hm dockyard, devonport | 1 march 1933 | 15 august 1933 | 9 october 1934 | 13 january 1936 | sold to royal australian navy as hmas hobart, 1938 broken up at osaka, 1962 |
| 7 | sydney (ex-phaeton) | 48 | city of sydney | swan hunter | 10 february 1933 | 8 july 1933 | 22 september 1934 | 24 september 1935 | sunk in surface action, 19 november 1941 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 3 | | [
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select count ( pearson symbol ) where c (pm) > 567 col : formula | color | symmetry | space group | no | pearson symbol | a (pm) | b (pm) | c (pm) | z | density, g/cm3 row 1 : pa | silvery-gray | tetragonal | i4/mmm | 139 | ti2 | 392.5 | 392.5 | 323.8 | 2 | 15.37 row 2 : pao | none | rocksalt | fm3m | 225 | cf8 | 496.1 | none | none | 4 | 13.44 row 3 : pao2 | black | fcc | fm3m | 225 | cf12 | 550.5 | none | none | 4 | 10.47 row 4 : pa2o5 | white | none | fm3m | 225 | cf16 | 547.6 | 547.6 | 547.6 | 4 | 10.96 row 5 : pa2o5 | white | none | orthorhombic | none | none | 692 | 402 | 418 | none | none row 6 : pah3 | black | cubic | pm3n | 223 | cp32 | 664.8 | 664.8 | 664.8 | 8 | 10.58 row 7 : paf4 | brown-red | monoclinic | c2/c | 15 | ms60 | none | none | none | 2 | none row 8 : pacl4 | green-yellow | tetragonal | i41/amd | 141 | ti20 | 837.7 | 837.7 | 748.1 | 4 | 4.72 row 9 : pabr4 | brown | tetragonal | i41/amd | 141 | ti20 | 882.4 | 882.4 | 795.7 | none | none row 10 : pacl5 | yellow | monoclinic | c2/c | 15 | ms24 | 797 | 1135 | 836 | 4 | 3.74 row 11 : pabr5 | red | monoclinic | p21/c | 14 | mp24 | 838.5 | 1120.5 | 1214.6 | 4 | 4.98 row 12 : paobr3 | none | monoclinic | c2 | none | none | 1691.1 | 387.1 | 933.4 | none | none row 13 : pa(po3)4 | none | orthorhombic | none | none | none | 696.9 | 895.9 | 1500.9 | none | none row 14 : pa2p2o7 | none | cubic | pa3 | none | none | 865 | 865 | 865 | none | none row 15 : pa(c8h8)2 | golden-yellow | monoclinic | none | none | none | 709 | 875 | 1062 | none | none | col : count ( "pearson symbol" ) row 1 : 9 | select count ( pearson symbol ) where c (pm) > 567 <table_name> : table \begin{tabular}{llllllllllll}
\toprule
& formula & color & symmetry & space group & no & pearson symbol & a (pm) & b (pm) & c (pm) & z & density, g/cm3 \\
\midrule
0 & pa & silvery-gray & tetragonal & i4/mmm & 139 & ti2 & 392.5 & 392.5 & 323.8 & 2 & 15.37 \\
1 & pao & none & rocksalt & fm3m & 225 & cf8 & 496.1 & none & none & 4 & 13.44 \\
2 & pao2 & black & fcc & fm3m & 225 & cf12 & 550.5 & none & none & 4 & 10.47 \\
3 & pa2o5 & white & none & fm3m & 225 & cf16 & 547.6 & 547.6 & 547.6 & 4 & 10.96 \\
4 & pa2o5 & white & none & orthorhombic & none & none & 692 & 402 & 418 & none & none \\
5 & pah3 & black & cubic & pm3n & 223 & cp32 & 664.8 & 664.8 & 664.8 & 8 & 10.58 \\
6 & paf4 & brown-red & monoclinic & c2/c & 15 & ms60 & none & none & none & 2 & none \\
7 & pacl4 & green-yellow & tetragonal & i41/amd & 141 & ti20 & 837.7 & 837.7 & 748.1 & 4 & 4.72 \\
8 & pabr4 & brown & tetragonal & i41/amd & 141 & ti20 & 882.4 & 882.4 & 795.7 & none & none \\
9 & pacl5 & yellow & monoclinic & c2/c & 15 & ms24 & 797 & 1135 & 836 & 4 & 3.74 \\
10 & pabr5 & red & monoclinic & p21/c & 14 & mp24 & 838.5 & 1120.5 & 1214.6 & 4 & 4.98 \\
11 & paobr3 & none & monoclinic & c2 & none & none & 1691.1 & 387.1 & 933.4 & none & none \\
12 & pa(po3)4 & none & orthorhombic & none & none & none & 696.9 & 895.9 & 1500.9 & none & none \\
13 & pa2p2o7 & none & cubic & pa3 & none & none & 865 & 865 & 865 & none & none \\
14 & pa(c8h8)2 & golden-yellow & monoclinic & none & none & none & 709 & 875 & 1062 & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "pearson symbol" ) \\
\midrule
0 & 9 \\
\bottomrule
\end{tabular}
| select count ( pearson symbol ) where c (pm) > 567 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>formula</th>
<th>color</th>
<th>symmetry</th>
<th>space group</th>
<th>no</th>
<th>pearson symbol</th>
<th>a (pm)</th>
<th>b (pm)</th>
<th>c (pm)</th>
<th>z</th>
<th>density, g/cm3</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>pa</td>
<td>silvery-gray</td>
<td>tetragonal</td>
<td>i4/mmm</td>
<td>139</td>
<td>ti2</td>
<td>392.5</td>
<td>392.5</td>
<td>323.8</td>
<td>2</td>
<td>15.37</td>
</tr>
<tr>
<th>1</th>
<td>pao</td>
<td>none</td>
<td>rocksalt</td>
<td>fm3m</td>
<td>225</td>
<td>cf8</td>
<td>496.1</td>
<td>none</td>
<td>none</td>
<td>4</td>
<td>13.44</td>
</tr>
<tr>
<th>2</th>
<td>pao2</td>
<td>black</td>
<td>fcc</td>
<td>fm3m</td>
<td>225</td>
<td>cf12</td>
<td>550.5</td>
<td>none</td>
<td>none</td>
<td>4</td>
<td>10.47</td>
</tr>
<tr>
<th>3</th>
<td>pa2o5</td>
<td>white</td>
<td>none</td>
<td>fm3m</td>
<td>225</td>
<td>cf16</td>
<td>547.6</td>
<td>547.6</td>
<td>547.6</td>
<td>4</td>
<td>10.96</td>
</tr>
<tr>
<th>4</th>
<td>pa2o5</td>
<td>white</td>
<td>none</td>
<td>orthorhombic</td>
<td>none</td>
<td>none</td>
<td>692</td>
<td>402</td>
<td>418</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>pah3</td>
<td>black</td>
<td>cubic</td>
<td>pm3n</td>
<td>223</td>
<td>cp32</td>
<td>664.8</td>
<td>664.8</td>
<td>664.8</td>
<td>8</td>
<td>10.58</td>
</tr>
<tr>
<th>6</th>
<td>paf4</td>
<td>brown-red</td>
<td>monoclinic</td>
<td>c2/c</td>
<td>15</td>
<td>ms60</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>pacl4</td>
<td>green-yellow</td>
<td>tetragonal</td>
<td>i41/amd</td>
<td>141</td>
<td>ti20</td>
<td>837.7</td>
<td>837.7</td>
<td>748.1</td>
<td>4</td>
<td>4.72</td>
</tr>
<tr>
<th>8</th>
<td>pabr4</td>
<td>brown</td>
<td>tetragonal</td>
<td>i41/amd</td>
<td>141</td>
<td>ti20</td>
<td>882.4</td>
<td>882.4</td>
<td>795.7</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>pacl5</td>
<td>yellow</td>
<td>monoclinic</td>
<td>c2/c</td>
<td>15</td>
<td>ms24</td>
<td>797</td>
<td>1135</td>
<td>836</td>
<td>4</td>
<td>3.74</td>
</tr>
<tr>
<th>10</th>
<td>pabr5</td>
<td>red</td>
<td>monoclinic</td>
<td>p21/c</td>
<td>14</td>
<td>mp24</td>
<td>838.5</td>
<td>1120.5</td>
<td>1214.6</td>
<td>4</td>
<td>4.98</td>
</tr>
<tr>
<th>11</th>
<td>paobr3</td>
<td>none</td>
<td>monoclinic</td>
<td>c2</td>
<td>none</td>
<td>none</td>
<td>1691.1</td>
<td>387.1</td>
<td>933.4</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>pa(po3)4</td>
<td>none</td>
<td>orthorhombic</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>696.9</td>
<td>895.9</td>
<td>1500.9</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>pa2p2o7</td>
<td>none</td>
<td>cubic</td>
<td>pa3</td>
<td>none</td>
<td>none</td>
<td>865</td>
<td>865</td>
<td>865</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>pa(c8h8)2</td>
<td>golden-yellow</td>
<td>monoclinic</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>709</td>
<td>875</td>
<td>1062</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "pearson symbol" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9</td>
</tr>
</tbody>
</table> | select count ( pearson symbol ) where c (pm) > 567 <table_name> : table | | formula | color | symmetry | space group | no | pearson symbol | a (pm) | b (pm) | c (pm) | z | density, g/cm3 |
|---:|:----------|:--------------|:-------------|:--------------|:-----|:-----------------|:---------|:---------|:---------|:-----|:-----------------|
| 0 | pa | silvery-gray | tetragonal | i4/mmm | 139 | ti2 | 392.5 | 392.5 | 323.8 | 2 | 15.37 |
| 1 | pao | none | rocksalt | fm3m | 225 | cf8 | 496.1 | none | none | 4 | 13.44 |
| 2 | pao2 | black | fcc | fm3m | 225 | cf12 | 550.5 | none | none | 4 | 10.47 |
| 3 | pa2o5 | white | none | fm3m | 225 | cf16 | 547.6 | 547.6 | 547.6 | 4 | 10.96 |
| 4 | pa2o5 | white | none | orthorhombic | none | none | 692 | 402 | 418 | none | none |
| 5 | pah3 | black | cubic | pm3n | 223 | cp32 | 664.8 | 664.8 | 664.8 | 8 | 10.58 |
| 6 | paf4 | brown-red | monoclinic | c2/c | 15 | ms60 | none | none | none | 2 | none |
| 7 | pacl4 | green-yellow | tetragonal | i41/amd | 141 | ti20 | 837.7 | 837.7 | 748.1 | 4 | 4.72 |
| 8 | pabr4 | brown | tetragonal | i41/amd | 141 | ti20 | 882.4 | 882.4 | 795.7 | none | none |
| 9 | pacl5 | yellow | monoclinic | c2/c | 15 | ms24 | 797 | 1135 | 836 | 4 | 3.74 |
| 10 | pabr5 | red | monoclinic | p21/c | 14 | mp24 | 838.5 | 1120.5 | 1214.6 | 4 | 4.98 |
| 11 | paobr3 | none | monoclinic | c2 | none | none | 1691.1 | 387.1 | 933.4 | none | none |
| 12 | pa(po3)4 | none | orthorhombic | none | none | none | 696.9 | 895.9 | 1500.9 | none | none |
| 13 | pa2p2o7 | none | cubic | pa3 | none | none | 865 | 865 | 865 | none | none |
| 14 | pa(c8h8)2 | golden-yellow | monoclinic | none | none | none | 709 | 875 | 1062 | none | none | | | | count ( "pearson symbol" ) |
|---:|-----------------------------:|
| 0 | 9 | | [
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select count ( record ) where time (s) < 1253 col : event | record | athlete(s) | date | time (s) row 1 : bobsleigh - two-man | start | beat hefti & thomas lamparter (sui) | 6 february 2009 | 4.7 row 2 : bobsleigh - two-man | track | thomas florschutz & richard adjei (ger) andre lange & kevin kuske (ger) | 20 february 2010 21 february 2010 | 51.57 row 3 : bobsleigh - four-man | start | andre lange, kevin kuske, alexander rodiger, & martin putze (ger) | 26 february 2010 | 4.7 row 4 : bobsleigh - four-man | track | steve holcomb, justin olsen, steve mesler, & curtis tomasevicz (usa) | 26 february 2010 | 50.86 row 5 : bobsleigh - two-woman | start | kaillie humphries & heather moyse (can) | 23 february 2010 24 february 2010 | 5.11 row 6 : bobsleigh - two-woman | track | kaillie humphries & heather moyse (can) | 24 february 2010 | 52.85 row 7 : men's skeleton | start | alexander tretiakov (rus) | 18 february 2010 | 4.48 row 8 : men's skeleton | track | jon montgomery (can) | 19 february 2010 | 52.2 row 9 : women's skeleton | start | anja huber (ger) | 18 february 2010 | 4.9 row 10 : women's skeleton | track | amy williams (gbr) | 19 february 2010 | 53.68 row 11 : luge - men's singles | start | andi langenhan (ger) | 21 february 2009 | 3.541 row 12 : luge - men's singles | track | felix loch (ger) | 21 february 2009 | 46.808 row 13 : luge - women's singles | start | natalie geisenberger (ger) | 20 february 2009 | 7.183 row 14 : luge - women's singles | track | natalie geisenberger (ger) | 20 february 2009 | 48.992 row 15 : luge - men's doubles | start | tobias wendl & tobias arlt (ger) | 20 february 2009 | 7.054 row 16 : luge - men's doubles | track | patric leitner & alexander resch (ger) | 20 february 2009 | 48.608 | col : count ( "record" ) row 1 : 0 | select count ( record ) where time (s) < 1253 <table_name> : table \begin{tabular}{llllll}
\toprule
& event & record & athlete(s) & date & time (s) \\
\midrule
0 & bobsleigh - two-man & start & beat hefti & thomas lamparter (sui) & 6 february 2009 & 4.7 \\
1 & bobsleigh - two-man & track & thomas florschutz & richard adjei (ger) andre lange & kevin kuske (ger) & 20 february 2010 21 february 2010 & 51.57 \\
2 & bobsleigh - four-man & start & andre lange, kevin kuske, alexander rodiger, & martin putze (ger) & 26 february 2010 & 4.7 \\
3 & bobsleigh - four-man & track & steve holcomb, justin olsen, steve mesler, & curtis tomasevicz (usa) & 26 february 2010 & 50.86 \\
4 & bobsleigh - two-woman & start & kaillie humphries & heather moyse (can) & 23 february 2010 24 february 2010 & 5.11 \\
5 & bobsleigh - two-woman & track & kaillie humphries & heather moyse (can) & 24 february 2010 & 52.85 \\
6 & men's skeleton & start & alexander tretiakov (rus) & 18 february 2010 & 4.48 \\
7 & men's skeleton & track & jon montgomery (can) & 19 february 2010 & 52.2 \\
8 & women's skeleton & start & anja huber (ger) & 18 february 2010 & 4.9 \\
9 & women's skeleton & track & amy williams (gbr) & 19 february 2010 & 53.68 \\
10 & luge - men's singles & start & andi langenhan (ger) & 21 february 2009 & 3.541 \\
11 & luge - men's singles & track & felix loch (ger) & 21 february 2009 & 46.808 \\
12 & luge - women's singles & start & natalie geisenberger (ger) & 20 february 2009 & 7.183 \\
13 & luge - women's singles & track & natalie geisenberger (ger) & 20 february 2009 & 48.992 \\
14 & luge - men's doubles & start & tobias wendl & tobias arlt (ger) & 20 february 2009 & 7.054 \\
15 & luge - men's doubles & track & patric leitner & alexander resch (ger) & 20 february 2009 & 48.608 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "record" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( record ) where time (s) < 1253 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>event</th>
<th>record</th>
<th>athlete(s)</th>
<th>date</th>
<th>time (s)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>bobsleigh - two-man</td>
<td>start</td>
<td>beat hefti & thomas lamparter (sui)</td>
<td>6 february 2009</td>
<td>4.7</td>
</tr>
<tr>
<th>1</th>
<td>bobsleigh - two-man</td>
<td>track</td>
<td>thomas florschutz & richard adjei (ger) andre lange & kevin kuske (ger)</td>
<td>20 february 2010 21 february 2010</td>
<td>51.57</td>
</tr>
<tr>
<th>2</th>
<td>bobsleigh - four-man</td>
<td>start</td>
<td>andre lange, kevin kuske, alexander rodiger, & martin putze (ger)</td>
<td>26 february 2010</td>
<td>4.7</td>
</tr>
<tr>
<th>3</th>
<td>bobsleigh - four-man</td>
<td>track</td>
<td>steve holcomb, justin olsen, steve mesler, & curtis tomasevicz (usa)</td>
<td>26 february 2010</td>
<td>50.86</td>
</tr>
<tr>
<th>4</th>
<td>bobsleigh - two-woman</td>
<td>start</td>
<td>kaillie humphries & heather moyse (can)</td>
<td>23 february 2010 24 february 2010</td>
<td>5.11</td>
</tr>
<tr>
<th>5</th>
<td>bobsleigh - two-woman</td>
<td>track</td>
<td>kaillie humphries & heather moyse (can)</td>
<td>24 february 2010</td>
<td>52.85</td>
</tr>
<tr>
<th>6</th>
<td>men's skeleton</td>
<td>start</td>
<td>alexander tretiakov (rus)</td>
<td>18 february 2010</td>
<td>4.48</td>
</tr>
<tr>
<th>7</th>
<td>men's skeleton</td>
<td>track</td>
<td>jon montgomery (can)</td>
<td>19 february 2010</td>
<td>52.2</td>
</tr>
<tr>
<th>8</th>
<td>women's skeleton</td>
<td>start</td>
<td>anja huber (ger)</td>
<td>18 february 2010</td>
<td>4.9</td>
</tr>
<tr>
<th>9</th>
<td>women's skeleton</td>
<td>track</td>
<td>amy williams (gbr)</td>
<td>19 february 2010</td>
<td>53.68</td>
</tr>
<tr>
<th>10</th>
<td>luge - men's singles</td>
<td>start</td>
<td>andi langenhan (ger)</td>
<td>21 february 2009</td>
<td>3.541</td>
</tr>
<tr>
<th>11</th>
<td>luge - men's singles</td>
<td>track</td>
<td>felix loch (ger)</td>
<td>21 february 2009</td>
<td>46.808</td>
</tr>
<tr>
<th>12</th>
<td>luge - women's singles</td>
<td>start</td>
<td>natalie geisenberger (ger)</td>
<td>20 february 2009</td>
<td>7.183</td>
</tr>
<tr>
<th>13</th>
<td>luge - women's singles</td>
<td>track</td>
<td>natalie geisenberger (ger)</td>
<td>20 february 2009</td>
<td>48.992</td>
</tr>
<tr>
<th>14</th>
<td>luge - men's doubles</td>
<td>start</td>
<td>tobias wendl & tobias arlt (ger)</td>
<td>20 february 2009</td>
<td>7.054</td>
</tr>
<tr>
<th>15</th>
<td>luge - men's doubles</td>
<td>track</td>
<td>patric leitner & alexander resch (ger)</td>
<td>20 february 2009</td>
<td>48.608</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "record" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( record ) where time (s) < 1253 <table_name> : table | | event | record | athlete(s) | date | time (s) |
|---:|:-----------------------|:---------|:------------------------------------------------------------------------|:----------------------------------|-----------:|
| 0 | bobsleigh - two-man | start | beat hefti & thomas lamparter (sui) | 6 february 2009 | 4.7 |
| 1 | bobsleigh - two-man | track | thomas florschutz & richard adjei (ger) andre lange & kevin kuske (ger) | 20 february 2010 21 february 2010 | 51.57 |
| 2 | bobsleigh - four-man | start | andre lange, kevin kuske, alexander rodiger, & martin putze (ger) | 26 february 2010 | 4.7 |
| 3 | bobsleigh - four-man | track | steve holcomb, justin olsen, steve mesler, & curtis tomasevicz (usa) | 26 february 2010 | 50.86 |
| 4 | bobsleigh - two-woman | start | kaillie humphries & heather moyse (can) | 23 february 2010 24 february 2010 | 5.11 |
| 5 | bobsleigh - two-woman | track | kaillie humphries & heather moyse (can) | 24 february 2010 | 52.85 |
| 6 | men's skeleton | start | alexander tretiakov (rus) | 18 february 2010 | 4.48 |
| 7 | men's skeleton | track | jon montgomery (can) | 19 february 2010 | 52.2 |
| 8 | women's skeleton | start | anja huber (ger) | 18 february 2010 | 4.9 |
| 9 | women's skeleton | track | amy williams (gbr) | 19 february 2010 | 53.68 |
| 10 | luge - men's singles | start | andi langenhan (ger) | 21 february 2009 | 3.541 |
| 11 | luge - men's singles | track | felix loch (ger) | 21 february 2009 | 46.808 |
| 12 | luge - women's singles | start | natalie geisenberger (ger) | 20 february 2009 | 7.183 |
| 13 | luge - women's singles | track | natalie geisenberger (ger) | 20 february 2009 | 48.992 |
| 14 | luge - men's doubles | start | tobias wendl & tobias arlt (ger) | 20 february 2009 | 7.054 |
| 15 | luge - men's doubles | track | patric leitner & alexander resch (ger) | 20 february 2009 | 48.608 | | | | count ( "record" ) |
|---:|---------------------:|
| 0 | 0 | | [
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[
1,
1,
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1,
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1,
1,
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1,
1,
1,
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select population where place = 'backer' col : place | code | area (km2) | population | most spoken language row 1 : backer | 91101 | 0.34 | 1217 | northern sotho row 2 : bochum | 91102 | 11.64 | 4142 | northern sotho row 3 : dendron | 91103 | 2.98 | 1885 | northern sotho row 4 : ga-ramokgopha | 91104 | 11.22 | 15806 | northern sotho row 5 : manthata | 91105 | 12.24 | 22121 | northern sotho row 6 : moletji | 91107 | 11.66 | 4989 | northern sotho row 7 : sekgosese | 91108 | 349.99 | 46749 | northern sotho row 8 : sekhokho | 91109 | 1.24 | 1852 | northern sotho row 9 : soekmekaar | 91110 | 1.06 | 217 | northern sotho row 10 : remainder of the municipality | 91106 | 2944.04 | 10463 | northern sotho | col : population row 1 : 1217 | select population where place = 'backer' <table_name> : table \begin{tabular}{llllll}
\toprule
& place & code & area (km2) & population & most spoken language \\
\midrule
0 & backer & 91101 & 0.34 & 1217 & northern sotho \\
1 & bochum & 91102 & 11.64 & 4142 & northern sotho \\
2 & dendron & 91103 & 2.98 & 1885 & northern sotho \\
3 & ga-ramokgopha & 91104 & 11.22 & 15806 & northern sotho \\
4 & manthata & 91105 & 12.24 & 22121 & northern sotho \\
5 & moletji & 91107 & 11.66 & 4989 & northern sotho \\
6 & sekgosese & 91108 & 349.99 & 46749 & northern sotho \\
7 & sekhokho & 91109 & 1.24 & 1852 & northern sotho \\
8 & soekmekaar & 91110 & 1.06 & 217 & northern sotho \\
9 & remainder of the municipality & 91106 & 2944.04 & 10463 & northern sotho \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& population \\
\midrule
0 & 1217 \\
\bottomrule
\end{tabular}
| select population where place = 'backer' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
<th>code</th>
<th>area (km2)</th>
<th>population</th>
<th>most spoken language</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>backer</td>
<td>91101</td>
<td>0.34</td>
<td>1217</td>
<td>northern sotho</td>
</tr>
<tr>
<th>1</th>
<td>bochum</td>
<td>91102</td>
<td>11.64</td>
<td>4142</td>
<td>northern sotho</td>
</tr>
<tr>
<th>2</th>
<td>dendron</td>
<td>91103</td>
<td>2.98</td>
<td>1885</td>
<td>northern sotho</td>
</tr>
<tr>
<th>3</th>
<td>ga-ramokgopha</td>
<td>91104</td>
<td>11.22</td>
<td>15806</td>
<td>northern sotho</td>
</tr>
<tr>
<th>4</th>
<td>manthata</td>
<td>91105</td>
<td>12.24</td>
<td>22121</td>
<td>northern sotho</td>
</tr>
<tr>
<th>5</th>
<td>moletji</td>
<td>91107</td>
<td>11.66</td>
<td>4989</td>
<td>northern sotho</td>
</tr>
<tr>
<th>6</th>
<td>sekgosese</td>
<td>91108</td>
<td>349.99</td>
<td>46749</td>
<td>northern sotho</td>
</tr>
<tr>
<th>7</th>
<td>sekhokho</td>
<td>91109</td>
<td>1.24</td>
<td>1852</td>
<td>northern sotho</td>
</tr>
<tr>
<th>8</th>
<td>soekmekaar</td>
<td>91110</td>
<td>1.06</td>
<td>217</td>
<td>northern sotho</td>
</tr>
<tr>
<th>9</th>
<td>remainder of the municipality</td>
<td>91106</td>
<td>2944.04</td>
<td>10463</td>
<td>northern sotho</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>population</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1217</td>
</tr>
</tbody>
</table> | select population where place = 'backer' <table_name> : table | | place | code | area (km2) | population | most spoken language |
|---:|:------------------------------|-------:|-------------:|-------------:|:-----------------------|
| 0 | backer | 91101 | 0.34 | 1217 | northern sotho |
| 1 | bochum | 91102 | 11.64 | 4142 | northern sotho |
| 2 | dendron | 91103 | 2.98 | 1885 | northern sotho |
| 3 | ga-ramokgopha | 91104 | 11.22 | 15806 | northern sotho |
| 4 | manthata | 91105 | 12.24 | 22121 | northern sotho |
| 5 | moletji | 91107 | 11.66 | 4989 | northern sotho |
| 6 | sekgosese | 91108 | 349.99 | 46749 | northern sotho |
| 7 | sekhokho | 91109 | 1.24 | 1852 | northern sotho |
| 8 | soekmekaar | 91110 | 1.06 | 217 | northern sotho |
| 9 | remainder of the municipality | 91106 | 2944.04 | 10463 | northern sotho | | | | population |
|---:|-------------:|
| 0 | 1217 | | [
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select nation where total = 74 col : rank | nation | gold | silver | bronze | total row 1 : 1 | china | 63 | 46 | 32 | 141 row 2 : 2 | great britain | 35 | 30 | 29 | 94 row 3 : 3 | canada | 28 | 19 | 25 | 72 row 4 : 4 | united states | 27 | 22 | 39 | 88 row 5 : 5 | australia | 26 | 38 | 36 | 100 row 6 : 6 | ukraine | 24 | 12 | 19 | 55 row 7 : 7 | spain | 20 | 27 | 24 | 71 row 8 : 8 | germany | 19 | 28 | 31 | 78 row 9 : 9 | france | 18 | 26 | 30 | 74 row 10 : 10 | japan | 17 | 16 | 20 | 53 | col : nation row 1 : france | select nation where total = 74 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & china & 63 & 46 & 32 & 141 \\
1 & 2 & great britain & 35 & 30 & 29 & 94 \\
2 & 3 & canada & 28 & 19 & 25 & 72 \\
3 & 4 & united states & 27 & 22 & 39 & 88 \\
4 & 5 & australia & 26 & 38 & 36 & 100 \\
5 & 6 & ukraine & 24 & 12 & 19 & 55 \\
6 & 7 & spain & 20 & 27 & 24 & 71 \\
7 & 8 & germany & 19 & 28 & 31 & 78 \\
8 & 9 & france & 18 & 26 & 30 & 74 \\
9 & 10 & japan & 17 & 16 & 20 & 53 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & france \\
\bottomrule
\end{tabular}
| select nation where total = 74 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>china</td>
<td>63</td>
<td>46</td>
<td>32</td>
<td>141</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>great britain</td>
<td>35</td>
<td>30</td>
<td>29</td>
<td>94</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>canada</td>
<td>28</td>
<td>19</td>
<td>25</td>
<td>72</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>united states</td>
<td>27</td>
<td>22</td>
<td>39</td>
<td>88</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>australia</td>
<td>26</td>
<td>38</td>
<td>36</td>
<td>100</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>ukraine</td>
<td>24</td>
<td>12</td>
<td>19</td>
<td>55</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>spain</td>
<td>20</td>
<td>27</td>
<td>24</td>
<td>71</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>germany</td>
<td>19</td>
<td>28</td>
<td>31</td>
<td>78</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>france</td>
<td>18</td>
<td>26</td>
<td>30</td>
<td>74</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>japan</td>
<td>17</td>
<td>16</td>
<td>20</td>
<td>53</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>france</td>
</tr>
</tbody>
</table> | select nation where total = 74 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|-------:|:--------------|-------:|---------:|---------:|--------:|
| 0 | 1 | china | 63 | 46 | 32 | 141 |
| 1 | 2 | great britain | 35 | 30 | 29 | 94 |
| 2 | 3 | canada | 28 | 19 | 25 | 72 |
| 3 | 4 | united states | 27 | 22 | 39 | 88 |
| 4 | 5 | australia | 26 | 38 | 36 | 100 |
| 5 | 6 | ukraine | 24 | 12 | 19 | 55 |
| 6 | 7 | spain | 20 | 27 | 24 | 71 |
| 7 | 8 | germany | 19 | 28 | 31 | 78 |
| 8 | 9 | france | 18 | 26 | 30 | 74 |
| 9 | 10 | japan | 17 | 16 | 20 | 53 | | | | nation |
|---:|:---------|
| 0 | france | | [
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select programming type where owner > network name order by flagship limit 43 col : network name | flagship | programming type | owner | affiliates row 1 : canal de las estrellas | xew 2 | soap operas, retro movies and sports | televisa | 1 row 2 : canal 5 | xhgc 5 | cartoons, movies, and series | televisa | 1 row 3 : azteca 7 | xhimt 7 | sports, series, and movies | tv azteca | 1 row 4 : galavision | xeq 9 | retro programming and sports | televisa | 1 row 5 : once tv | xeipn 11 | educational and cultural | national polytechnic institute | 1 row 6 : azteca 13 | xhdf 13 | news, soap operas, and sports | tv azteca | 1 row 7 : independent | none | varies | independent | 2 | col : min ( "programming type" ) row 1 : cartoons, movies, and series | select programming type where owner > network name order by flagship limit 43 <table_name> : table \begin{tabular}{llllll}
\toprule
& network name & flagship & programming type & owner & affiliates \\
\midrule
0 & canal de las estrellas & xew 2 & soap operas, retro movies and sports & televisa & 1 \\
1 & canal 5 & xhgc 5 & cartoons, movies, and series & televisa & 1 \\
2 & azteca 7 & xhimt 7 & sports, series, and movies & tv azteca & 1 \\
3 & galavision & xeq 9 & retro programming and sports & televisa & 1 \\
4 & once tv & xeipn 11 & educational and cultural & national polytechnic institute & 1 \\
5 & azteca 13 & xhdf 13 & news, soap operas, and sports & tv azteca & 1 \\
6 & independent & none & varies & independent & 2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& min ( "programming type" ) \\
\midrule
0 & cartoons, movies, and series \\
\bottomrule
\end{tabular}
| select programming type where owner > network name order by flagship limit 43 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>network name</th>
<th>flagship</th>
<th>programming type</th>
<th>owner</th>
<th>affiliates</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>canal de las estrellas</td>
<td>xew 2</td>
<td>soap operas, retro movies and sports</td>
<td>televisa</td>
<td>1</td>
</tr>
<tr>
<th>1</th>
<td>canal 5</td>
<td>xhgc 5</td>
<td>cartoons, movies, and series</td>
<td>televisa</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>azteca 7</td>
<td>xhimt 7</td>
<td>sports, series, and movies</td>
<td>tv azteca</td>
<td>1</td>
</tr>
<tr>
<th>3</th>
<td>galavision</td>
<td>xeq 9</td>
<td>retro programming and sports</td>
<td>televisa</td>
<td>1</td>
</tr>
<tr>
<th>4</th>
<td>once tv</td>
<td>xeipn 11</td>
<td>educational and cultural</td>
<td>national polytechnic institute</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>azteca 13</td>
<td>xhdf 13</td>
<td>news, soap operas, and sports</td>
<td>tv azteca</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>independent</td>
<td>none</td>
<td>varies</td>
<td>independent</td>
<td>2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>min ( "programming type" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>cartoons, movies, and series</td>
</tr>
</tbody>
</table> | select programming type where owner > network name order by flagship limit 43 <table_name> : table | | network name | flagship | programming type | owner | affiliates |
|---:|:-----------------------|:-----------|:-------------------------------------|:-------------------------------|-------------:|
| 0 | canal de las estrellas | xew 2 | soap operas, retro movies and sports | televisa | 1 |
| 1 | canal 5 | xhgc 5 | cartoons, movies, and series | televisa | 1 |
| 2 | azteca 7 | xhimt 7 | sports, series, and movies | tv azteca | 1 |
| 3 | galavision | xeq 9 | retro programming and sports | televisa | 1 |
| 4 | once tv | xeipn 11 | educational and cultural | national polytechnic institute | 1 |
| 5 | azteca 13 | xhdf 13 | news, soap operas, and sports | tv azteca | 1 |
| 6 | independent | none | varies | independent | 2 | | | | min ( "programming type" ) |
|---:|:-----------------------------|
| 0 | cartoons, movies, and series | | [
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select affiliates where network name = 'independent' col : network name | flagship | programming type | owner | affiliates row 1 : canal de las estrellas | xew 2 | soap operas, retro movies and sports | televisa | 1 row 2 : canal 5 | xhgc 5 | cartoons, movies, and series | televisa | 1 row 3 : azteca 7 | xhimt 7 | sports, series, and movies | tv azteca | 1 row 4 : galavision | xeq 9 | retro programming and sports | televisa | 1 row 5 : once tv | xeipn 11 | educational and cultural | national polytechnic institute | 1 row 6 : azteca 13 | xhdf 13 | news, soap operas, and sports | tv azteca | 1 row 7 : independent | none | varies | independent | 2 | col : affiliates row 1 : 2 | select affiliates where network name = 'independent' <table_name> : table \begin{tabular}{llllll}
\toprule
& network name & flagship & programming type & owner & affiliates \\
\midrule
0 & canal de las estrellas & xew 2 & soap operas, retro movies and sports & televisa & 1 \\
1 & canal 5 & xhgc 5 & cartoons, movies, and series & televisa & 1 \\
2 & azteca 7 & xhimt 7 & sports, series, and movies & tv azteca & 1 \\
3 & galavision & xeq 9 & retro programming and sports & televisa & 1 \\
4 & once tv & xeipn 11 & educational and cultural & national polytechnic institute & 1 \\
5 & azteca 13 & xhdf 13 & news, soap operas, and sports & tv azteca & 1 \\
6 & independent & none & varies & independent & 2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& affiliates \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select affiliates where network name = 'independent' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>network name</th>
<th>flagship</th>
<th>programming type</th>
<th>owner</th>
<th>affiliates</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>canal de las estrellas</td>
<td>xew 2</td>
<td>soap operas, retro movies and sports</td>
<td>televisa</td>
<td>1</td>
</tr>
<tr>
<th>1</th>
<td>canal 5</td>
<td>xhgc 5</td>
<td>cartoons, movies, and series</td>
<td>televisa</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>azteca 7</td>
<td>xhimt 7</td>
<td>sports, series, and movies</td>
<td>tv azteca</td>
<td>1</td>
</tr>
<tr>
<th>3</th>
<td>galavision</td>
<td>xeq 9</td>
<td>retro programming and sports</td>
<td>televisa</td>
<td>1</td>
</tr>
<tr>
<th>4</th>
<td>once tv</td>
<td>xeipn 11</td>
<td>educational and cultural</td>
<td>national polytechnic institute</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>azteca 13</td>
<td>xhdf 13</td>
<td>news, soap operas, and sports</td>
<td>tv azteca</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>independent</td>
<td>none</td>
<td>varies</td>
<td>independent</td>
<td>2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>affiliates</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select affiliates where network name = 'independent' <table_name> : table | | network name | flagship | programming type | owner | affiliates |
|---:|:-----------------------|:-----------|:-------------------------------------|:-------------------------------|-------------:|
| 0 | canal de las estrellas | xew 2 | soap operas, retro movies and sports | televisa | 1 |
| 1 | canal 5 | xhgc 5 | cartoons, movies, and series | televisa | 1 |
| 2 | azteca 7 | xhimt 7 | sports, series, and movies | tv azteca | 1 |
| 3 | galavision | xeq 9 | retro programming and sports | televisa | 1 |
| 4 | once tv | xeipn 11 | educational and cultural | national polytechnic institute | 1 |
| 5 | azteca 13 | xhdf 13 | news, soap operas, and sports | tv azteca | 1 |
| 6 | independent | none | varies | independent | 2 | | | | affiliates |
|---:|-------------:|
| 0 | 2 | | [
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select year where year = 1980 col : iteration | year | dates | location | theme row 1 : 1st | 1972 | 6 may-20 may | suva, fiji | "preserving culture" row 2 : 2nd | 1976 | 6 march-13 march | rotorua, new zealand | "sharing culture" row 3 : 3rd | 1980 | 30 june-12 july | port moresby, papua new guinea | "pacific awareness" row 4 : 4th | 1985 | 29 june-15 july | tahiti, french polynesia | "my pacific" row 5 : 5th | 1988 | 14 august-24 august | townsville, australia | "cultural interchange" row 6 : 6th | 1992 | 16 october-27 october | rarotonga, cook islands | "seafaring heritage" row 7 : 7th | 1996 | 8 september-23 september | apia, samoa | "unveiling treasures" row 8 : 8th | 2000 | 23 october-3 november | noumea, new caledonia | "words of past, present, future" row 9 : 9th | 2004 | 22 july-31 july | koror, palau | "nurture, regenerate, celebrate" row 10 : 10th | 2008 | 20 july-2 august | pago pago, american samoa | "threading the oceania 'ula" row 11 : 11th | 2012 | 1-14 july | honiara, solomon islands | "culture in harmony with nature" row 12 : 12th | 2016 | none | tumon, guam | "tba" row 13 : 13th | 2020 | none | tba, hawaii | "tba" | col : year row 1 : 1980 | select year where year = 1980 <table_name> : table \begin{tabular}{llllll}
\toprule
& iteration & year & dates & location & theme \\
\midrule
0 & 1st & 1972 & 6 may-20 may & suva, fiji & "preserving culture" \\
1 & 2nd & 1976 & 6 march-13 march & rotorua, new zealand & "sharing culture" \\
2 & 3rd & 1980 & 30 june-12 july & port moresby, papua new guinea & "pacific awareness" \\
3 & 4th & 1985 & 29 june-15 july & tahiti, french polynesia & "my pacific" \\
4 & 5th & 1988 & 14 august-24 august & townsville, australia & "cultural interchange" \\
5 & 6th & 1992 & 16 october-27 october & rarotonga, cook islands & "seafaring heritage" \\
6 & 7th & 1996 & 8 september-23 september & apia, samoa & "unveiling treasures" \\
7 & 8th & 2000 & 23 october-3 november & noumea, new caledonia & "words of past, present, future" \\
8 & 9th & 2004 & 22 july-31 july & koror, palau & "nurture, regenerate, celebrate" \\
9 & 10th & 2008 & 20 july-2 august & pago pago, american samoa & "threading the oceania 'ula" \\
10 & 11th & 2012 & 1-14 july & honiara, solomon islands & "culture in harmony with nature" \\
11 & 12th & 2016 & none & tumon, guam & "tba" \\
12 & 13th & 2020 & none & tba, hawaii & "tba" \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1980 \\
\bottomrule
\end{tabular}
| select year where year = 1980 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>iteration</th>
<th>year</th>
<th>dates</th>
<th>location</th>
<th>theme</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1st</td>
<td>1972</td>
<td>6 may-20 may</td>
<td>suva, fiji</td>
<td>"preserving culture"</td>
</tr>
<tr>
<th>1</th>
<td>2nd</td>
<td>1976</td>
<td>6 march-13 march</td>
<td>rotorua, new zealand</td>
<td>"sharing culture"</td>
</tr>
<tr>
<th>2</th>
<td>3rd</td>
<td>1980</td>
<td>30 june-12 july</td>
<td>port moresby, papua new guinea</td>
<td>"pacific awareness"</td>
</tr>
<tr>
<th>3</th>
<td>4th</td>
<td>1985</td>
<td>29 june-15 july</td>
<td>tahiti, french polynesia</td>
<td>"my pacific"</td>
</tr>
<tr>
<th>4</th>
<td>5th</td>
<td>1988</td>
<td>14 august-24 august</td>
<td>townsville, australia</td>
<td>"cultural interchange"</td>
</tr>
<tr>
<th>5</th>
<td>6th</td>
<td>1992</td>
<td>16 october-27 october</td>
<td>rarotonga, cook islands</td>
<td>"seafaring heritage"</td>
</tr>
<tr>
<th>6</th>
<td>7th</td>
<td>1996</td>
<td>8 september-23 september</td>
<td>apia, samoa</td>
<td>"unveiling treasures"</td>
</tr>
<tr>
<th>7</th>
<td>8th</td>
<td>2000</td>
<td>23 october-3 november</td>
<td>noumea, new caledonia</td>
<td>"words of past, present, future"</td>
</tr>
<tr>
<th>8</th>
<td>9th</td>
<td>2004</td>
<td>22 july-31 july</td>
<td>koror, palau</td>
<td>"nurture, regenerate, celebrate"</td>
</tr>
<tr>
<th>9</th>
<td>10th</td>
<td>2008</td>
<td>20 july-2 august</td>
<td>pago pago, american samoa</td>
<td>"threading the oceania 'ula"</td>
</tr>
<tr>
<th>10</th>
<td>11th</td>
<td>2012</td>
<td>1-14 july</td>
<td>honiara, solomon islands</td>
<td>"culture in harmony with nature"</td>
</tr>
<tr>
<th>11</th>
<td>12th</td>
<td>2016</td>
<td>none</td>
<td>tumon, guam</td>
<td>"tba"</td>
</tr>
<tr>
<th>12</th>
<td>13th</td>
<td>2020</td>
<td>none</td>
<td>tba, hawaii</td>
<td>"tba"</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1980</td>
</tr>
</tbody>
</table> | select year where year = 1980 <table_name> : table | | iteration | year | dates | location | theme |
|---:|:------------|-------:|:-------------------------|:-------------------------------|:---------------------------------|
| 0 | 1st | 1972 | 6 may-20 may | suva, fiji | "preserving culture" |
| 1 | 2nd | 1976 | 6 march-13 march | rotorua, new zealand | "sharing culture" |
| 2 | 3rd | 1980 | 30 june-12 july | port moresby, papua new guinea | "pacific awareness" |
| 3 | 4th | 1985 | 29 june-15 july | tahiti, french polynesia | "my pacific" |
| 4 | 5th | 1988 | 14 august-24 august | townsville, australia | "cultural interchange" |
| 5 | 6th | 1992 | 16 october-27 october | rarotonga, cook islands | "seafaring heritage" |
| 6 | 7th | 1996 | 8 september-23 september | apia, samoa | "unveiling treasures" |
| 7 | 8th | 2000 | 23 october-3 november | noumea, new caledonia | "words of past, present, future" |
| 8 | 9th | 2004 | 22 july-31 july | koror, palau | "nurture, regenerate, celebrate" |
| 9 | 10th | 2008 | 20 july-2 august | pago pago, american samoa | "threading the oceania 'ula" |
| 10 | 11th | 2012 | 1-14 july | honiara, solomon islands | "culture in harmony with nature" |
| 11 | 12th | 2016 | none | tumon, guam | "tba" |
| 12 | 13th | 2020 | none | tba, hawaii | "tba" | | | | year |
|---:|-------:|
| 0 | 1980 | | [
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select division where league = 'usl d-3 pro league' col : year | division | league | reg. season | playoffs | open cup row 1 : 1998 | 3 | usisl d-3 pro league | 3rd, northeast | division semifinals | 2nd round row 2 : 1999 | 3 | usl d-3 pro league | 1st, northern | champion | did not qualify row 3 : 2000 | 3 | usl d-3 pro league | 5th, northern | conference finals | did not qualify row 4 : 2001 | 3 | usl d-3 pro league | 7th, northern | did not qualify | did not qualify row 5 : 2002 | 3 | usl d-3 pro league | 1st, northern | quarterfinals | did not qualify row 6 : 2003 | 3 | usl pro select league | 3rd, northern | did not qualify | did not qualify row 7 : 2004 | 3 | usl pro soccer league | 3rd, northern | did not qualify | 2nd round row 8 : 2005 | 3 | usl second division | 1st | final | 3rd round row 9 : 2006 | 3 | usl second division | 6th | did not qualify | did not qualify row 10 : 2007 | 3 | usl second division | 6th | did not qualify | 2nd round row 11 : 2008 | 3 | usl second division | 6th | quarterfinals | 2nd round row 12 : 2009 | 3 | usl second division | 7th | did not qualify | 2nd round row 13 : 2010 | 4 | usl pdl | 6th, northeast | did not qualify | did not qualify row 14 : 2011 | 4 | usl pdl | 3rd, northeast | did not qualify | 1st round row 15 : 2012 | 4 | usl pdl | 3rd, northeast | did not qualify | did not qualify row 16 : 2013 | 4 | usl pdl | 4th, northeast | did not qualify | did not qualify | col : division row 1 : 3 row 2 : 3 row 3 : 3 row 4 : 3 | select division where league = 'usl d-3 pro league' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & division & league & reg. season & playoffs & open cup \\
\midrule
0 & 1998 & 3 & usisl d-3 pro league & 3rd, northeast & division semifinals & 2nd round \\
1 & 1999 & 3 & usl d-3 pro league & 1st, northern & champion & did not qualify \\
2 & 2000 & 3 & usl d-3 pro league & 5th, northern & conference finals & did not qualify \\
3 & 2001 & 3 & usl d-3 pro league & 7th, northern & did not qualify & did not qualify \\
4 & 2002 & 3 & usl d-3 pro league & 1st, northern & quarterfinals & did not qualify \\
5 & 2003 & 3 & usl pro select league & 3rd, northern & did not qualify & did not qualify \\
6 & 2004 & 3 & usl pro soccer league & 3rd, northern & did not qualify & 2nd round \\
7 & 2005 & 3 & usl second division & 1st & final & 3rd round \\
8 & 2006 & 3 & usl second division & 6th & did not qualify & did not qualify \\
9 & 2007 & 3 & usl second division & 6th & did not qualify & 2nd round \\
10 & 2008 & 3 & usl second division & 6th & quarterfinals & 2nd round \\
11 & 2009 & 3 & usl second division & 7th & did not qualify & 2nd round \\
12 & 2010 & 4 & usl pdl & 6th, northeast & did not qualify & did not qualify \\
13 & 2011 & 4 & usl pdl & 3rd, northeast & did not qualify & 1st round \\
14 & 2012 & 4 & usl pdl & 3rd, northeast & did not qualify & did not qualify \\
15 & 2013 & 4 & usl pdl & 4th, northeast & did not qualify & did not qualify \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& division \\
\midrule
0 & 3 \\
1 & 3 \\
2 & 3 \\
3 & 3 \\
\bottomrule
\end{tabular}
| select division where league = 'usl d-3 pro league' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>division</th>
<th>league</th>
<th>reg. season</th>
<th>playoffs</th>
<th>open cup</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1998</td>
<td>3</td>
<td>usisl d-3 pro league</td>
<td>3rd, northeast</td>
<td>division semifinals</td>
<td>2nd round</td>
</tr>
<tr>
<th>1</th>
<td>1999</td>
<td>3</td>
<td>usl d-3 pro league</td>
<td>1st, northern</td>
<td>champion</td>
<td>did not qualify</td>
</tr>
<tr>
<th>2</th>
<td>2000</td>
<td>3</td>
<td>usl d-3 pro league</td>
<td>5th, northern</td>
<td>conference finals</td>
<td>did not qualify</td>
</tr>
<tr>
<th>3</th>
<td>2001</td>
<td>3</td>
<td>usl d-3 pro league</td>
<td>7th, northern</td>
<td>did not qualify</td>
<td>did not qualify</td>
</tr>
<tr>
<th>4</th>
<td>2002</td>
<td>3</td>
<td>usl d-3 pro league</td>
<td>1st, northern</td>
<td>quarterfinals</td>
<td>did not qualify</td>
</tr>
<tr>
<th>5</th>
<td>2003</td>
<td>3</td>
<td>usl pro select league</td>
<td>3rd, northern</td>
<td>did not qualify</td>
<td>did not qualify</td>
</tr>
<tr>
<th>6</th>
<td>2004</td>
<td>3</td>
<td>usl pro soccer league</td>
<td>3rd, northern</td>
<td>did not qualify</td>
<td>2nd round</td>
</tr>
<tr>
<th>7</th>
<td>2005</td>
<td>3</td>
<td>usl second division</td>
<td>1st</td>
<td>final</td>
<td>3rd round</td>
</tr>
<tr>
<th>8</th>
<td>2006</td>
<td>3</td>
<td>usl second division</td>
<td>6th</td>
<td>did not qualify</td>
<td>did not qualify</td>
</tr>
<tr>
<th>9</th>
<td>2007</td>
<td>3</td>
<td>usl second division</td>
<td>6th</td>
<td>did not qualify</td>
<td>2nd round</td>
</tr>
<tr>
<th>10</th>
<td>2008</td>
<td>3</td>
<td>usl second division</td>
<td>6th</td>
<td>quarterfinals</td>
<td>2nd round</td>
</tr>
<tr>
<th>11</th>
<td>2009</td>
<td>3</td>
<td>usl second division</td>
<td>7th</td>
<td>did not qualify</td>
<td>2nd round</td>
</tr>
<tr>
<th>12</th>
<td>2010</td>
<td>4</td>
<td>usl pdl</td>
<td>6th, northeast</td>
<td>did not qualify</td>
<td>did not qualify</td>
</tr>
<tr>
<th>13</th>
<td>2011</td>
<td>4</td>
<td>usl pdl</td>
<td>3rd, northeast</td>
<td>did not qualify</td>
<td>1st round</td>
</tr>
<tr>
<th>14</th>
<td>2012</td>
<td>4</td>
<td>usl pdl</td>
<td>3rd, northeast</td>
<td>did not qualify</td>
<td>did not qualify</td>
</tr>
<tr>
<th>15</th>
<td>2013</td>
<td>4</td>
<td>usl pdl</td>
<td>4th, northeast</td>
<td>did not qualify</td>
<td>did not qualify</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>division</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
<tr>
<th>1</th>
<td>3</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
</tr>
</tbody>
</table> | select division where league = 'usl d-3 pro league' <table_name> : table | | year | division | league | reg. season | playoffs | open cup |
|---:|-------:|-----------:|:----------------------|:---------------|:--------------------|:----------------|
| 0 | 1998 | 3 | usisl d-3 pro league | 3rd, northeast | division semifinals | 2nd round |
| 1 | 1999 | 3 | usl d-3 pro league | 1st, northern | champion | did not qualify |
| 2 | 2000 | 3 | usl d-3 pro league | 5th, northern | conference finals | did not qualify |
| 3 | 2001 | 3 | usl d-3 pro league | 7th, northern | did not qualify | did not qualify |
| 4 | 2002 | 3 | usl d-3 pro league | 1st, northern | quarterfinals | did not qualify |
| 5 | 2003 | 3 | usl pro select league | 3rd, northern | did not qualify | did not qualify |
| 6 | 2004 | 3 | usl pro soccer league | 3rd, northern | did not qualify | 2nd round |
| 7 | 2005 | 3 | usl second division | 1st | final | 3rd round |
| 8 | 2006 | 3 | usl second division | 6th | did not qualify | did not qualify |
| 9 | 2007 | 3 | usl second division | 6th | did not qualify | 2nd round |
| 10 | 2008 | 3 | usl second division | 6th | quarterfinals | 2nd round |
| 11 | 2009 | 3 | usl second division | 7th | did not qualify | 2nd round |
| 12 | 2010 | 4 | usl pdl | 6th, northeast | did not qualify | did not qualify |
| 13 | 2011 | 4 | usl pdl | 3rd, northeast | did not qualify | 1st round |
| 14 | 2012 | 4 | usl pdl | 3rd, northeast | did not qualify | did not qualify |
| 15 | 2013 | 4 | usl pdl | 4th, northeast | did not qualify | did not qualify | | | | division |
|---:|-----------:|
| 0 | 3 |
| 1 | 3 |
| 2 | 3 |
| 3 | 3 | | [
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select count ( nationality ) where rank = 'none' col : rank | name | nationality | time | notes row 1 : none | jill sterkel | united states | 1:00.53 | nr, gr row 2 : none | lisa buese | united states | 1:00.59 | none row 3 : none | nancy garapick | canada | 1:02.96 | none row 4 : 4 | shelley cramer | u.s. virgin islands | 1:03.51 | nr row 5 : 5 | susan sloan | canada | 1:03.52 | none row 6 : 6 | maria paris | costa rica | 1:03.58 | none row 7 : 7 | rosanna juncos | argentina | 1:04.75 | none row 8 : 8 | adriana pereira | brazil | 1:06.79 | none | col : count ( "nationality" ) row 1 : 3 | select count ( nationality ) where rank = 'none' <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & nationality & time & notes \\
\midrule
0 & none & jill sterkel & united states & 1:00.53 & nr, gr \\
1 & none & lisa buese & united states & 1:00.59 & none \\
2 & none & nancy garapick & canada & 1:02.96 & none \\
3 & 4 & shelley cramer & u.s. virgin islands & 1:03.51 & nr \\
4 & 5 & susan sloan & canada & 1:03.52 & none \\
5 & 6 & maria paris & costa rica & 1:03.58 & none \\
6 & 7 & rosanna juncos & argentina & 1:04.75 & none \\
7 & 8 & adriana pereira & brazil & 1:06.79 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "nationality" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( nationality ) where rank = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>nationality</th>
<th>time</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>jill sterkel</td>
<td>united states</td>
<td>1:00.53</td>
<td>nr, gr</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>lisa buese</td>
<td>united states</td>
<td>1:00.59</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>nancy garapick</td>
<td>canada</td>
<td>1:02.96</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>shelley cramer</td>
<td>u.s. virgin islands</td>
<td>1:03.51</td>
<td>nr</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>susan sloan</td>
<td>canada</td>
<td>1:03.52</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>maria paris</td>
<td>costa rica</td>
<td>1:03.58</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>rosanna juncos</td>
<td>argentina</td>
<td>1:04.75</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>adriana pereira</td>
<td>brazil</td>
<td>1:06.79</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "nationality" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( nationality ) where rank = 'none' <table_name> : table | | rank | name | nationality | time | notes |
|---:|:-------|:----------------|:--------------------|:--------|:--------|
| 0 | none | jill sterkel | united states | 1:00.53 | nr, gr |
| 1 | none | lisa buese | united states | 1:00.59 | none |
| 2 | none | nancy garapick | canada | 1:02.96 | none |
| 3 | 4 | shelley cramer | u.s. virgin islands | 1:03.51 | nr |
| 4 | 5 | susan sloan | canada | 1:03.52 | none |
| 5 | 6 | maria paris | costa rica | 1:03.58 | none |
| 6 | 7 | rosanna juncos | argentina | 1:04.75 | none |
| 7 | 8 | adriana pereira | brazil | 1:06.79 | none | | | | count ( "nationality" ) |
|---:|--------------------------:|
| 0 | 3 | | [
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select year where link = '' col : wicket | score | batting partners | opposition | venue | year | link row 1 : 1st | 375 | ra white & mj powell | gloucestershire | northampton | 2002.0 | row 2 : 2nd | 344 | g cook & rj boyd-moss | lancashire | northampton | 1986.0 | row 3 : 3rd | 393 | a fordham & aj lamb | yorkshire | leeds | 1990.0 | row 4 : 4th | 370 | rt virgin & p willey | somerset | northampton | 1976.0 | row 5 : 5th | 401 | mb loye & d ripley | glamorgan | northampton | 1998.0 | row 6 : 6th | 376 | r subba | | | | row 7 : & a lightfoot | surrey | the oval | 1958 | | | row 8 : 7th | 293 | djg sales & d ripley | essex | northampton | 1999.0 | row 9 : 8th | 179 | aj hall & jd middlebrook | surrey | the oval | 2011.0 | row 10 : 9th | 156 | r subba | | | | row 11 : & s starkie | lancashire | northampton | 1955 | | | row 12 : 10th | 148 | bw bellamy & jv murdin | glamorgan | northampton | 1925.0 | | col : year row 1 : 2002 row 2 : 1986 row 3 : 1990 row 4 : 1976 row 5 : 1998 row 6 : 1999 row 7 : 2011 row 8 : 1925 | select year where link = '' <table_name> : table \begin{tabular}{llllllll}
\toprule
& wicket & score & batting partners & opposition & venue & year & link \\
\midrule
0 & 1st & 375 & ra white & mj powell & gloucestershire & northampton & 2002.0 & \\
1 & 2nd & 344 & g cook & rj boyd-moss & lancashire & northampton & 1986.0 & \\
2 & 3rd & 393 & a fordham & aj lamb & yorkshire & leeds & 1990.0 & \\
3 & 4th & 370 & rt virgin & p willey & somerset & northampton & 1976.0 & \\
4 & 5th & 401 & mb loye & d ripley & glamorgan & northampton & 1998.0 & \\
5 & 6th & 376 & r subba & & & & \\
6 & & a lightfoot & surrey & the oval & 1958 & & & \\
7 & 7th & 293 & djg sales & d ripley & essex & northampton & 1999.0 & \\
8 & 8th & 179 & aj hall & jd middlebrook & surrey & the oval & 2011.0 & \\
9 & 9th & 156 & r subba & & & & \\
10 & & s starkie & lancashire & northampton & 1955 & & & \\
11 & 10th & 148 & bw bellamy & jv murdin & glamorgan & northampton & 1925.0 | & NaN \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 2002 \\
1 & 1986 \\
2 & 1990 \\
3 & 1976 \\
4 & 1998 \\
5 & 1999 \\
6 & 2011 \\
7 & 1925 \\
\bottomrule
\end{tabular}
| select year where link = '' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>wicket</th>
<th>score</th>
<th>batting partners</th>
<th>opposition</th>
<th>venue</th>
<th>year</th>
<th>link</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1st</td>
<td>375</td>
<td>ra white & mj powell</td>
<td>gloucestershire</td>
<td>northampton</td>
<td>2002.0</td>
<td></td>
</tr>
<tr>
<th>1</th>
<td>2nd</td>
<td>344</td>
<td>g cook & rj boyd-moss</td>
<td>lancashire</td>
<td>northampton</td>
<td>1986.0</td>
<td></td>
</tr>
<tr>
<th>2</th>
<td>3rd</td>
<td>393</td>
<td>a fordham & aj lamb</td>
<td>yorkshire</td>
<td>leeds</td>
<td>1990.0</td>
<td></td>
</tr>
<tr>
<th>3</th>
<td>4th</td>
<td>370</td>
<td>rt virgin & p willey</td>
<td>somerset</td>
<td>northampton</td>
<td>1976.0</td>
<td></td>
</tr>
<tr>
<th>4</th>
<td>5th</td>
<td>401</td>
<td>mb loye & d ripley</td>
<td>glamorgan</td>
<td>northampton</td>
<td>1998.0</td>
<td></td>
</tr>
<tr>
<th>5</th>
<td>6th</td>
<td>376</td>
<td>r subba</td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>6</th>
<td>& a lightfoot</td>
<td>surrey</td>
<td>the oval</td>
<td>1958</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>7th</td>
<td>293</td>
<td>djg sales & d ripley</td>
<td>essex</td>
<td>northampton</td>
<td>1999.0</td>
<td></td>
</tr>
<tr>
<th>8</th>
<td>8th</td>
<td>179</td>
<td>aj hall & jd middlebrook</td>
<td>surrey</td>
<td>the oval</td>
<td>2011.0</td>
<td></td>
</tr>
<tr>
<th>9</th>
<td>9th</td>
<td>156</td>
<td>r subba</td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>10</th>
<td>& s starkie</td>
<td>lancashire</td>
<td>northampton</td>
<td>1955</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>11</th>
<td>10th</td>
<td>148</td>
<td>bw bellamy & jv murdin</td>
<td>glamorgan</td>
<td>northampton</td>
<td>1925.0 |</td>
<td>None</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2002</td>
</tr>
<tr>
<th>1</th>
<td>1986</td>
</tr>
<tr>
<th>2</th>
<td>1990</td>
</tr>
<tr>
<th>3</th>
<td>1976</td>
</tr>
<tr>
<th>4</th>
<td>1998</td>
</tr>
<tr>
<th>5</th>
<td>1999</td>
</tr>
<tr>
<th>6</th>
<td>2011</td>
</tr>
<tr>
<th>7</th>
<td>1925</td>
</tr>
</tbody>
</table> | select year where link = '' <table_name> : table | | wicket | score | batting partners | opposition | venue | year | link |
|---:|:--------------|:-----------|:-------------------------|:----------------|:------------|:---------|:-------|
| 0 | 1st | 375 | ra white & mj powell | gloucestershire | northampton | 2002.0 | |
| 1 | 2nd | 344 | g cook & rj boyd-moss | lancashire | northampton | 1986.0 | |
| 2 | 3rd | 393 | a fordham & aj lamb | yorkshire | leeds | 1990.0 | |
| 3 | 4th | 370 | rt virgin & p willey | somerset | northampton | 1976.0 | |
| 4 | 5th | 401 | mb loye & d ripley | glamorgan | northampton | 1998.0 | |
| 5 | 6th | 376 | r subba | | | | |
| 6 | & a lightfoot | surrey | the oval | 1958 | | | |
| 7 | 7th | 293 | djg sales & d ripley | essex | northampton | 1999.0 | |
| 8 | 8th | 179 | aj hall & jd middlebrook | surrey | the oval | 2011.0 | |
| 9 | 9th | 156 | r subba | | | | |
| 10 | & s starkie | lancashire | northampton | 1955 | | | |
| 11 | 10th | 148 | bw bellamy & jv murdin | glamorgan | northampton | 1925.0 | | | | | | year |
|---:|-------:|
| 0 | 2002 |
| 1 | 1986 |
| 2 | 1990 |
| 3 | 1976 |
| 4 | 1998 |
| 5 | 1999 |
| 6 | 2011 |
| 7 | 1925 | | [
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select distinct lives lost where lake > ship col : ship | type of vessel | lake | location | lives lost row 1 : argus | steamer | lake huron | 25 miles off kincardine, ontario | 25 lost row 2 : james carruthers | steamer | lake huron | near kincardine | 18 lost row 3 : hydrus | steamer | lake huron | near lexington, michigan | 28 lost row 4 : leafield | steamer | lake superior | none | all hands row 5 : john a. mcgean | steamer | lake huron | near goderich, ontario | 28 lost row 6 : plymouth | barge | lake michigan | none | 7 lost row 7 : charles s. price | steamer | lake huron | near port huron, michigan | 28 lost row 8 : regina | steamer | lake huron | near harbor beach, michigan | none row 9 : issac m. scott | steamer | lake huron | near port elgin, ontario | 28 lost row 10 : henry b. smith | steamer | lake superior | none | all hands row 11 : wexford | steamer | lake huron | north of grand bend, ontario | all hands row 12 : lightship no. 82 | lightship | lake erie | point albino (near buffalo) | 6 lost | col : "distinct lives lost" row 1 : distinct lives lost row 2 : distinct lives lost row 3 : distinct lives lost row 4 : distinct lives lost row 5 : distinct lives lost row 6 : distinct lives lost row 7 : distinct lives lost | select distinct lives lost where lake > ship <table_name> : table \begin{tabular}{llllll}
\toprule
& ship & type of vessel & lake & location & lives lost \\
\midrule
0 & argus & steamer & lake huron & 25 miles off kincardine, ontario & 25 lost \\
1 & james carruthers & steamer & lake huron & near kincardine & 18 lost \\
2 & hydrus & steamer & lake huron & near lexington, michigan & 28 lost \\
3 & leafield & steamer & lake superior & none & all hands \\
4 & john a. mcgean & steamer & lake huron & near goderich, ontario & 28 lost \\
5 & plymouth & barge & lake michigan & none & 7 lost \\
6 & charles s. price & steamer & lake huron & near port huron, michigan & 28 lost \\
7 & regina & steamer & lake huron & near harbor beach, michigan & none \\
8 & issac m. scott & steamer & lake huron & near port elgin, ontario & 28 lost \\
9 & henry b. smith & steamer & lake superior & none & all hands \\
10 & wexford & steamer & lake huron & north of grand bend, ontario & all hands \\
11 & lightship no. 82 & lightship & lake erie & point albino (near buffalo) & 6 lost \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "distinct lives lost" \\
\midrule
0 & distinct lives lost \\
1 & distinct lives lost \\
2 & distinct lives lost \\
3 & distinct lives lost \\
4 & distinct lives lost \\
5 & distinct lives lost \\
6 & distinct lives lost \\
\bottomrule
\end{tabular}
| select distinct lives lost where lake > ship <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>ship</th>
<th>type of vessel</th>
<th>lake</th>
<th>location</th>
<th>lives lost</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>argus</td>
<td>steamer</td>
<td>lake huron</td>
<td>25 miles off kincardine, ontario</td>
<td>25 lost</td>
</tr>
<tr>
<th>1</th>
<td>james carruthers</td>
<td>steamer</td>
<td>lake huron</td>
<td>near kincardine</td>
<td>18 lost</td>
</tr>
<tr>
<th>2</th>
<td>hydrus</td>
<td>steamer</td>
<td>lake huron</td>
<td>near lexington, michigan</td>
<td>28 lost</td>
</tr>
<tr>
<th>3</th>
<td>leafield</td>
<td>steamer</td>
<td>lake superior</td>
<td>none</td>
<td>all hands</td>
</tr>
<tr>
<th>4</th>
<td>john a. mcgean</td>
<td>steamer</td>
<td>lake huron</td>
<td>near goderich, ontario</td>
<td>28 lost</td>
</tr>
<tr>
<th>5</th>
<td>plymouth</td>
<td>barge</td>
<td>lake michigan</td>
<td>none</td>
<td>7 lost</td>
</tr>
<tr>
<th>6</th>
<td>charles s. price</td>
<td>steamer</td>
<td>lake huron</td>
<td>near port huron, michigan</td>
<td>28 lost</td>
</tr>
<tr>
<th>7</th>
<td>regina</td>
<td>steamer</td>
<td>lake huron</td>
<td>near harbor beach, michigan</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>issac m. scott</td>
<td>steamer</td>
<td>lake huron</td>
<td>near port elgin, ontario</td>
<td>28 lost</td>
</tr>
<tr>
<th>9</th>
<td>henry b. smith</td>
<td>steamer</td>
<td>lake superior</td>
<td>none</td>
<td>all hands</td>
</tr>
<tr>
<th>10</th>
<td>wexford</td>
<td>steamer</td>
<td>lake huron</td>
<td>north of grand bend, ontario</td>
<td>all hands</td>
</tr>
<tr>
<th>11</th>
<td>lightship no. 82</td>
<td>lightship</td>
<td>lake erie</td>
<td>point albino (near buffalo)</td>
<td>6 lost</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"distinct lives lost"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>distinct lives lost</td>
</tr>
<tr>
<th>1</th>
<td>distinct lives lost</td>
</tr>
<tr>
<th>2</th>
<td>distinct lives lost</td>
</tr>
<tr>
<th>3</th>
<td>distinct lives lost</td>
</tr>
<tr>
<th>4</th>
<td>distinct lives lost</td>
</tr>
<tr>
<th>5</th>
<td>distinct lives lost</td>
</tr>
<tr>
<th>6</th>
<td>distinct lives lost</td>
</tr>
</tbody>
</table> | select distinct lives lost where lake > ship <table_name> : table | | ship | type of vessel | lake | location | lives lost |
|---:|:-----------------|:-----------------|:--------------|:---------------------------------|:-------------|
| 0 | argus | steamer | lake huron | 25 miles off kincardine, ontario | 25 lost |
| 1 | james carruthers | steamer | lake huron | near kincardine | 18 lost |
| 2 | hydrus | steamer | lake huron | near lexington, michigan | 28 lost |
| 3 | leafield | steamer | lake superior | none | all hands |
| 4 | john a. mcgean | steamer | lake huron | near goderich, ontario | 28 lost |
| 5 | plymouth | barge | lake michigan | none | 7 lost |
| 6 | charles s. price | steamer | lake huron | near port huron, michigan | 28 lost |
| 7 | regina | steamer | lake huron | near harbor beach, michigan | none |
| 8 | issac m. scott | steamer | lake huron | near port elgin, ontario | 28 lost |
| 9 | henry b. smith | steamer | lake superior | none | all hands |
| 10 | wexford | steamer | lake huron | north of grand bend, ontario | all hands |
| 11 | lightship no. 82 | lightship | lake erie | point albino (near buffalo) | 6 lost | | | | "distinct lives lost" |
|---:|:------------------------|
| 0 | distinct lives lost |
| 1 | distinct lives lost |
| 2 | distinct lives lost |
| 3 | distinct lives lost |
| 4 | distinct lives lost |
| 5 | distinct lives lost |
| 6 | distinct lives lost | | [
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select result where rank = 6 col : rank | name | nationality | result | notes row 1 : none | huang qiuyan | china | 14.39 | sb row 2 : none | anastasiya juravleva | uzbekistan | 14.21 | #name? row 3 : none | zhang hao | china | 13.63 | none row 4 : 4 | wacharee ritthiwat | thailand | 13.54 | sb row 5 : 5 | tatyana bocharova | kazakhstan | 13.5 | none row 6 : 6 | wang kuo-huei | chinese taipei | 13.25 | sb row 7 : 7 | fumiyo yoshida | japan | 13.09 | none row 8 : 8 | ngew sin mei | malaysia | 12.93 | none row 9 : 9 | manisha dey | india | 12.83 | none row 10 : 10 | thitima muangjan | thailand | 12.79 | none row 11 : 11 | phan thi thu lan | vietnam | 12.75 | none row 12 : 12 | lo yu-hsin | chinese taipei | 12.69 | none row 13 : none | elena bobrovskaya | kyrgyzstan | dns | none | col : result row 1 : 13.25 | select result where rank = 6 <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & nationality & result & notes \\
\midrule
0 & none & huang qiuyan & china & 14.39 & sb \\
1 & none & anastasiya juravleva & uzbekistan & 14.21 & #name? \\
2 & none & zhang hao & china & 13.63 & none \\
3 & 4 & wacharee ritthiwat & thailand & 13.54 & sb \\
4 & 5 & tatyana bocharova & kazakhstan & 13.5 & none \\
5 & 6 & wang kuo-huei & chinese taipei & 13.25 & sb \\
6 & 7 & fumiyo yoshida & japan & 13.09 & none \\
7 & 8 & ngew sin mei & malaysia & 12.93 & none \\
8 & 9 & manisha dey & india & 12.83 & none \\
9 & 10 & thitima muangjan & thailand & 12.79 & none \\
10 & 11 & phan thi thu lan & vietnam & 12.75 & none \\
11 & 12 & lo yu-hsin & chinese taipei & 12.69 & none \\
12 & none & elena bobrovskaya & kyrgyzstan & dns & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& result \\
\midrule
0 & 13.25 \\
\bottomrule
\end{tabular}
| select result where rank = 6 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>nationality</th>
<th>result</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>huang qiuyan</td>
<td>china</td>
<td>14.39</td>
<td>sb</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>anastasiya juravleva</td>
<td>uzbekistan</td>
<td>14.21</td>
<td>#name?</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>zhang hao</td>
<td>china</td>
<td>13.63</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>wacharee ritthiwat</td>
<td>thailand</td>
<td>13.54</td>
<td>sb</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>tatyana bocharova</td>
<td>kazakhstan</td>
<td>13.5</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>wang kuo-huei</td>
<td>chinese taipei</td>
<td>13.25</td>
<td>sb</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>fumiyo yoshida</td>
<td>japan</td>
<td>13.09</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>ngew sin mei</td>
<td>malaysia</td>
<td>12.93</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>manisha dey</td>
<td>india</td>
<td>12.83</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>thitima muangjan</td>
<td>thailand</td>
<td>12.79</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>phan thi thu lan</td>
<td>vietnam</td>
<td>12.75</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>lo yu-hsin</td>
<td>chinese taipei</td>
<td>12.69</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>none</td>
<td>elena bobrovskaya</td>
<td>kyrgyzstan</td>
<td>dns</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>13.25</td>
</tr>
</tbody>
</table> | select result where rank = 6 <table_name> : table | | rank | name | nationality | result | notes |
|---:|:-------|:---------------------|:---------------|:---------|:--------|
| 0 | none | huang qiuyan | china | 14.39 | sb |
| 1 | none | anastasiya juravleva | uzbekistan | 14.21 | #name? |
| 2 | none | zhang hao | china | 13.63 | none |
| 3 | 4 | wacharee ritthiwat | thailand | 13.54 | sb |
| 4 | 5 | tatyana bocharova | kazakhstan | 13.5 | none |
| 5 | 6 | wang kuo-huei | chinese taipei | 13.25 | sb |
| 6 | 7 | fumiyo yoshida | japan | 13.09 | none |
| 7 | 8 | ngew sin mei | malaysia | 12.93 | none |
| 8 | 9 | manisha dey | india | 12.83 | none |
| 9 | 10 | thitima muangjan | thailand | 12.79 | none |
| 10 | 11 | phan thi thu lan | vietnam | 12.75 | none |
| 11 | 12 | lo yu-hsin | chinese taipei | 12.69 | none |
| 12 | none | elena bobrovskaya | kyrgyzstan | dns | none | | | | result |
|---:|---------:|
| 0 | 13.25 | | [
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select year where result = '36-31' col : year | date | winner | result | loser | location row 1 : 2000 | september 10 | new york giants | 33-18 | philadelphia eagles | veterans stadium row 2 : 2000 | october 29 | new york giants | 24-7 | philadelphia eagles | giants stadium row 3 : 2001 | january 7 | new york giants | 20-10 | philadelphia eagles | giants stadium row 4 : 2001 | october 22 | philadelphia eagles | 10-9 | new york giants | giants stadium row 5 : 2001 | december 30 | philadelphia eagles | 24-21 | new york giants | veterans stadium row 6 : 2002 | october 28 | philadelphia eagles | 17-3 | new york giants | veterans stadium row 7 : 2002 | december 28 | new york giants | 10-7 | philadelphia eagles | giants stadium row 8 : 2003 | october 19 | philadelphia eagles | 14-10 | new york giants | giants stadium row 9 : 2003 | november 16 | philadelphia eagles | 28-10 | new york giants | lincoln financial field row 10 : 2004 | september 12 | philadelphia eagles | 31-17 | new york giants | lincoln financial field row 11 : 2004 | november 28 | philadelphia eagles | 27-6 | new york giants | giants stadium row 12 : 2005 | november 20 | new york giants | 27-17 | philadelphia eagles | giants stadium row 13 : 2005 | december 11 | new york giants | 26-23 (ot) | philadelphia eagles | lincoln financial field row 14 : 2006 | september 17 | new york giants | 30-24 (ot) | philadelphia eagles | lincoln financial field row 15 : 2006 | december 17 | philadelphia eagles | 36-22 | new york giants | giants stadium row 16 : 2007 | january 7 | philadelphia eagles | 23-20 | new york giants | lincoln financial field row 17 : 2007 | september 30 | new york giants | 16-3 | philadelphia eagles | giants stadium row 18 : 2007 | december 9 | new york giants | 16-13 | philadelphia eagles | lincoln financial field row 19 : 2008 | november 9 | new york giants | 36-31 | philadelphia eagles | lincoln financial field row 20 : 2008 | december 7 | philadelphia eagles | 20-14 | new york giants | giants stadium row 21 : 2009 | january 11 | philadelphia eagles | 23-11 | new york giants | giants stadium row 22 : 2009 | november 1 | philadelphia eagles | 40-17 | new york giants | lincoln financial field row 23 : 2009 | december 13 | philadelphia eagles | 45-38 | new york giants | giants stadium | col : year row 1 : 2008 | select year where result = '36-31' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & date & winner & result & loser & location \\
\midrule
0 & 2000 & september 10 & new york giants & 33-18 & philadelphia eagles & veterans stadium \\
1 & 2000 & october 29 & new york giants & 24-7 & philadelphia eagles & giants stadium \\
2 & 2001 & january 7 & new york giants & 20-10 & philadelphia eagles & giants stadium \\
3 & 2001 & october 22 & philadelphia eagles & 10-9 & new york giants & giants stadium \\
4 & 2001 & december 30 & philadelphia eagles & 24-21 & new york giants & veterans stadium \\
5 & 2002 & october 28 & philadelphia eagles & 17-3 & new york giants & veterans stadium \\
6 & 2002 & december 28 & new york giants & 10-7 & philadelphia eagles & giants stadium \\
7 & 2003 & october 19 & philadelphia eagles & 14-10 & new york giants & giants stadium \\
8 & 2003 & november 16 & philadelphia eagles & 28-10 & new york giants & lincoln financial field \\
9 & 2004 & september 12 & philadelphia eagles & 31-17 & new york giants & lincoln financial field \\
10 & 2004 & november 28 & philadelphia eagles & 27-6 & new york giants & giants stadium \\
11 & 2005 & november 20 & new york giants & 27-17 & philadelphia eagles & giants stadium \\
12 & 2005 & december 11 & new york giants & 26-23 (ot) & philadelphia eagles & lincoln financial field \\
13 & 2006 & september 17 & new york giants & 30-24 (ot) & philadelphia eagles & lincoln financial field \\
14 & 2006 & december 17 & philadelphia eagles & 36-22 & new york giants & giants stadium \\
15 & 2007 & january 7 & philadelphia eagles & 23-20 & new york giants & lincoln financial field \\
16 & 2007 & september 30 & new york giants & 16-3 & philadelphia eagles & giants stadium \\
17 & 2007 & december 9 & new york giants & 16-13 & philadelphia eagles & lincoln financial field \\
18 & 2008 & november 9 & new york giants & 36-31 & philadelphia eagles & lincoln financial field \\
19 & 2008 & december 7 & philadelphia eagles & 20-14 & new york giants & giants stadium \\
20 & 2009 & january 11 & philadelphia eagles & 23-11 & new york giants & giants stadium \\
21 & 2009 & november 1 & philadelphia eagles & 40-17 & new york giants & lincoln financial field \\
22 & 2009 & december 13 & philadelphia eagles & 45-38 & new york giants & giants stadium \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 2008 \\
\bottomrule
\end{tabular}
| select year where result = '36-31' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>date</th>
<th>winner</th>
<th>result</th>
<th>loser</th>
<th>location</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2000</td>
<td>september 10</td>
<td>new york giants</td>
<td>33-18</td>
<td>philadelphia eagles</td>
<td>veterans stadium</td>
</tr>
<tr>
<th>1</th>
<td>2000</td>
<td>october 29</td>
<td>new york giants</td>
<td>24-7</td>
<td>philadelphia eagles</td>
<td>giants stadium</td>
</tr>
<tr>
<th>2</th>
<td>2001</td>
<td>january 7</td>
<td>new york giants</td>
<td>20-10</td>
<td>philadelphia eagles</td>
<td>giants stadium</td>
</tr>
<tr>
<th>3</th>
<td>2001</td>
<td>october 22</td>
<td>philadelphia eagles</td>
<td>10-9</td>
<td>new york giants</td>
<td>giants stadium</td>
</tr>
<tr>
<th>4</th>
<td>2001</td>
<td>december 30</td>
<td>philadelphia eagles</td>
<td>24-21</td>
<td>new york giants</td>
<td>veterans stadium</td>
</tr>
<tr>
<th>5</th>
<td>2002</td>
<td>october 28</td>
<td>philadelphia eagles</td>
<td>17-3</td>
<td>new york giants</td>
<td>veterans stadium</td>
</tr>
<tr>
<th>6</th>
<td>2002</td>
<td>december 28</td>
<td>new york giants</td>
<td>10-7</td>
<td>philadelphia eagles</td>
<td>giants stadium</td>
</tr>
<tr>
<th>7</th>
<td>2003</td>
<td>october 19</td>
<td>philadelphia eagles</td>
<td>14-10</td>
<td>new york giants</td>
<td>giants stadium</td>
</tr>
<tr>
<th>8</th>
<td>2003</td>
<td>november 16</td>
<td>philadelphia eagles</td>
<td>28-10</td>
<td>new york giants</td>
<td>lincoln financial field</td>
</tr>
<tr>
<th>9</th>
<td>2004</td>
<td>september 12</td>
<td>philadelphia eagles</td>
<td>31-17</td>
<td>new york giants</td>
<td>lincoln financial field</td>
</tr>
<tr>
<th>10</th>
<td>2004</td>
<td>november 28</td>
<td>philadelphia eagles</td>
<td>27-6</td>
<td>new york giants</td>
<td>giants stadium</td>
</tr>
<tr>
<th>11</th>
<td>2005</td>
<td>november 20</td>
<td>new york giants</td>
<td>27-17</td>
<td>philadelphia eagles</td>
<td>giants stadium</td>
</tr>
<tr>
<th>12</th>
<td>2005</td>
<td>december 11</td>
<td>new york giants</td>
<td>26-23 (ot)</td>
<td>philadelphia eagles</td>
<td>lincoln financial field</td>
</tr>
<tr>
<th>13</th>
<td>2006</td>
<td>september 17</td>
<td>new york giants</td>
<td>30-24 (ot)</td>
<td>philadelphia eagles</td>
<td>lincoln financial field</td>
</tr>
<tr>
<th>14</th>
<td>2006</td>
<td>december 17</td>
<td>philadelphia eagles</td>
<td>36-22</td>
<td>new york giants</td>
<td>giants stadium</td>
</tr>
<tr>
<th>15</th>
<td>2007</td>
<td>january 7</td>
<td>philadelphia eagles</td>
<td>23-20</td>
<td>new york giants</td>
<td>lincoln financial field</td>
</tr>
<tr>
<th>16</th>
<td>2007</td>
<td>september 30</td>
<td>new york giants</td>
<td>16-3</td>
<td>philadelphia eagles</td>
<td>giants stadium</td>
</tr>
<tr>
<th>17</th>
<td>2007</td>
<td>december 9</td>
<td>new york giants</td>
<td>16-13</td>
<td>philadelphia eagles</td>
<td>lincoln financial field</td>
</tr>
<tr>
<th>18</th>
<td>2008</td>
<td>november 9</td>
<td>new york giants</td>
<td>36-31</td>
<td>philadelphia eagles</td>
<td>lincoln financial field</td>
</tr>
<tr>
<th>19</th>
<td>2008</td>
<td>december 7</td>
<td>philadelphia eagles</td>
<td>20-14</td>
<td>new york giants</td>
<td>giants stadium</td>
</tr>
<tr>
<th>20</th>
<td>2009</td>
<td>january 11</td>
<td>philadelphia eagles</td>
<td>23-11</td>
<td>new york giants</td>
<td>giants stadium</td>
</tr>
<tr>
<th>21</th>
<td>2009</td>
<td>november 1</td>
<td>philadelphia eagles</td>
<td>40-17</td>
<td>new york giants</td>
<td>lincoln financial field</td>
</tr>
<tr>
<th>22</th>
<td>2009</td>
<td>december 13</td>
<td>philadelphia eagles</td>
<td>45-38</td>
<td>new york giants</td>
<td>giants stadium</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2008</td>
</tr>
</tbody>
</table> | select year where result = '36-31' <table_name> : table | | year | date | winner | result | loser | location |
|---:|-------:|:-------------|:--------------------|:-----------|:--------------------|:------------------------|
| 0 | 2000 | september 10 | new york giants | 33-18 | philadelphia eagles | veterans stadium |
| 1 | 2000 | october 29 | new york giants | 24-7 | philadelphia eagles | giants stadium |
| 2 | 2001 | january 7 | new york giants | 20-10 | philadelphia eagles | giants stadium |
| 3 | 2001 | october 22 | philadelphia eagles | 10-9 | new york giants | giants stadium |
| 4 | 2001 | december 30 | philadelphia eagles | 24-21 | new york giants | veterans stadium |
| 5 | 2002 | october 28 | philadelphia eagles | 17-3 | new york giants | veterans stadium |
| 6 | 2002 | december 28 | new york giants | 10-7 | philadelphia eagles | giants stadium |
| 7 | 2003 | october 19 | philadelphia eagles | 14-10 | new york giants | giants stadium |
| 8 | 2003 | november 16 | philadelphia eagles | 28-10 | new york giants | lincoln financial field |
| 9 | 2004 | september 12 | philadelphia eagles | 31-17 | new york giants | lincoln financial field |
| 10 | 2004 | november 28 | philadelphia eagles | 27-6 | new york giants | giants stadium |
| 11 | 2005 | november 20 | new york giants | 27-17 | philadelphia eagles | giants stadium |
| 12 | 2005 | december 11 | new york giants | 26-23 (ot) | philadelphia eagles | lincoln financial field |
| 13 | 2006 | september 17 | new york giants | 30-24 (ot) | philadelphia eagles | lincoln financial field |
| 14 | 2006 | december 17 | philadelphia eagles | 36-22 | new york giants | giants stadium |
| 15 | 2007 | january 7 | philadelphia eagles | 23-20 | new york giants | lincoln financial field |
| 16 | 2007 | september 30 | new york giants | 16-3 | philadelphia eagles | giants stadium |
| 17 | 2007 | december 9 | new york giants | 16-13 | philadelphia eagles | lincoln financial field |
| 18 | 2008 | november 9 | new york giants | 36-31 | philadelphia eagles | lincoln financial field |
| 19 | 2008 | december 7 | philadelphia eagles | 20-14 | new york giants | giants stadium |
| 20 | 2009 | january 11 | philadelphia eagles | 23-11 | new york giants | giants stadium |
| 21 | 2009 | november 1 | philadelphia eagles | 40-17 | new york giants | lincoln financial field |
| 22 | 2009 | december 13 | philadelphia eagles | 45-38 | new york giants | giants stadium | | | | year |
|---:|-------:|
| 0 | 2008 | | [
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select count ( * ) where country = 'nigeria' col : country | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 row 1 : australia | 160 | 230 | 290 | 230 | 200 | 200 | 200 | none | none | none | none | none row 2 : brazil | 30000 | 22000 | 26000 | 29000 | 29900 | 35000 | 40000 | 57300 | 58000 | 58000 | 58000 | 58000 row 3 : canada | 2290 | 3200 | 3410 | 3280 | 3400 | 3310 | 4167 | 3020 | 4380 | 4330 | 4420 | 4400 row 4 : congo d.r | none | 50 | 50 | 13 | 52 | 25 | none | none | none | none | none | none row 5 : mozambique | none | none | 5 | 34 | 130 | 34 | 29 | none | none | none | none | none row 6 : nigeria | 35 | 30 | 30 | 190 | 170 | 40 | 35 | none | none | none | none | none row 7 : rwanda | 28 | 120 | 76 | 22 | 63 | 63 | 80 | none | none | none | none | none row 8 : world | 32600 | 25600 | 29900 | 32800 | 34000 | 38700 | 44500 | 60400 | 62900 | 62900 | 62900 | 63000 | col : count ( "*" ) row 1 : 1 | select count ( * ) where country = 'nigeria' <table_name> : table \begin{tabular}{llllllllllllll}
\toprule
& country & 2000 & 2001 & 2002 & 2003 & 2004 & 2005 & 2006 & 2007 & 2008 & 2009 & 2010 & 2011 \\
\midrule
0 & australia & 160 & 230 & 290 & 230 & 200 & 200 & 200 & none & none & none & none & none \\
1 & brazil & 30000 & 22000 & 26000 & 29000 & 29900 & 35000 & 40000 & 57300 & 58000 & 58000 & 58000 & 58000 \\
2 & canada & 2290 & 3200 & 3410 & 3280 & 3400 & 3310 & 4167 & 3020 & 4380 & 4330 & 4420 & 4400 \\
3 & congo d.r & none & 50 & 50 & 13 & 52 & 25 & none & none & none & none & none & none \\
4 & mozambique & none & none & 5 & 34 & 130 & 34 & 29 & none & none & none & none & none \\
5 & nigeria & 35 & 30 & 30 & 190 & 170 & 40 & 35 & none & none & none & none & none \\
6 & rwanda & 28 & 120 & 76 & 22 & 63 & 63 & 80 & none & none & none & none & none \\
7 & world & 32600 & 25600 & 29900 & 32800 & 34000 & 38700 & 44500 & 60400 & 62900 & 62900 & 62900 & 63000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where country = 'nigeria' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>country</th>
<th>2000</th>
<th>2001</th>
<th>2002</th>
<th>2003</th>
<th>2004</th>
<th>2005</th>
<th>2006</th>
<th>2007</th>
<th>2008</th>
<th>2009</th>
<th>2010</th>
<th>2011</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>australia</td>
<td>160</td>
<td>230</td>
<td>290</td>
<td>230</td>
<td>200</td>
<td>200</td>
<td>200</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>brazil</td>
<td>30000</td>
<td>22000</td>
<td>26000</td>
<td>29000</td>
<td>29900</td>
<td>35000</td>
<td>40000</td>
<td>57300</td>
<td>58000</td>
<td>58000</td>
<td>58000</td>
<td>58000</td>
</tr>
<tr>
<th>2</th>
<td>canada</td>
<td>2290</td>
<td>3200</td>
<td>3410</td>
<td>3280</td>
<td>3400</td>
<td>3310</td>
<td>4167</td>
<td>3020</td>
<td>4380</td>
<td>4330</td>
<td>4420</td>
<td>4400</td>
</tr>
<tr>
<th>3</th>
<td>congo d.r</td>
<td>none</td>
<td>50</td>
<td>50</td>
<td>13</td>
<td>52</td>
<td>25</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>mozambique</td>
<td>none</td>
<td>none</td>
<td>5</td>
<td>34</td>
<td>130</td>
<td>34</td>
<td>29</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>nigeria</td>
<td>35</td>
<td>30</td>
<td>30</td>
<td>190</td>
<td>170</td>
<td>40</td>
<td>35</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>rwanda</td>
<td>28</td>
<td>120</td>
<td>76</td>
<td>22</td>
<td>63</td>
<td>63</td>
<td>80</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>world</td>
<td>32600</td>
<td>25600</td>
<td>29900</td>
<td>32800</td>
<td>34000</td>
<td>38700</td>
<td>44500</td>
<td>60400</td>
<td>62900</td>
<td>62900</td>
<td>62900</td>
<td>63000</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where country = 'nigeria' <table_name> : table | | country | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 |
|---:|:-----------|:-------|:-------|-------:|-------:|-------:|-------:|:-------|:-------|:-------|:-------|:-------|:-------|
| 0 | australia | 160 | 230 | 290 | 230 | 200 | 200 | 200 | none | none | none | none | none |
| 1 | brazil | 30000 | 22000 | 26000 | 29000 | 29900 | 35000 | 40000 | 57300 | 58000 | 58000 | 58000 | 58000 |
| 2 | canada | 2290 | 3200 | 3410 | 3280 | 3400 | 3310 | 4167 | 3020 | 4380 | 4330 | 4420 | 4400 |
| 3 | congo d.r | none | 50 | 50 | 13 | 52 | 25 | none | none | none | none | none | none |
| 4 | mozambique | none | none | 5 | 34 | 130 | 34 | 29 | none | none | none | none | none |
| 5 | nigeria | 35 | 30 | 30 | 190 | 170 | 40 | 35 | none | none | none | none | none |
| 6 | rwanda | 28 | 120 | 76 | 22 | 63 | 63 | 80 | none | none | none | none | none |
| 7 | world | 32600 | 25600 | 29900 | 32800 | 34000 | 38700 | 44500 | 60400 | 62900 | 62900 | 62900 | 63000 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select score where money ($) = 17000 col : place | player | country | score | to par | money ($) row 1 : t1 | larry nelson | united states | 70-72-73-72=287 | -1 | playoff row 2 : t1 | lanny wadkins | united states | 70-70-74-73=287 | -1 | playoff row 3 : t3 | scott hoch | united states | 74-74-71-69=288 | e | 58750 row 4 : t3 | d. a. weibring | united states | 73-72-67-76=288 | e | 58750 row 5 : t5 | mark mccumber | united states | 74-69-69-77=289 | 1 | 37500 row 6 : t5 | don pooley | united states | 73-71-73-72=289 | 1 | 37500 row 7 : t7 | ben crenshaw | united states | 72-70-74-74=290 | 2 | 27500 row 8 : t7 | bobby wadkins | united states | 68-74-71-77=290 | 2 | 27500 row 9 : 9 | curtis strange | united states | 70-76-71-74=291 | 3 | 22500 row 10 : t10 | seve ballesteros | spain | 72-70-72-78=292 | 4 | 17000 row 11 : t10 | david frost | south africa | 75-70-71-76=292 | 4 | 17000 row 12 : t10 | tom kite | united states | 72-77-71-72=292 | 4 | 17000 row 13 : t10 | nick price | zimbabwe | 76-71-70-75=292 | 4 | 17000 | col : score row 1 : 72-70-72-78=292 row 2 : 75-70-71-76=292 row 3 : 72-77-71-72=292 row 4 : 76-71-70-75=292 | select score where money ($) = 17000 <table_name> : table \begin{tabular}{lllllll}
\toprule
& place & player & country & score & to par & money ($) \\
\midrule
0 & t1 & larry nelson & united states & 70-72-73-72=287 & -1 & playoff \\
1 & t1 & lanny wadkins & united states & 70-70-74-73=287 & -1 & playoff \\
2 & t3 & scott hoch & united states & 74-74-71-69=288 & e & 58750 \\
3 & t3 & d. a. weibring & united states & 73-72-67-76=288 & e & 58750 \\
4 & t5 & mark mccumber & united states & 74-69-69-77=289 & 1 & 37500 \\
5 & t5 & don pooley & united states & 73-71-73-72=289 & 1 & 37500 \\
6 & t7 & ben crenshaw & united states & 72-70-74-74=290 & 2 & 27500 \\
7 & t7 & bobby wadkins & united states & 68-74-71-77=290 & 2 & 27500 \\
8 & 9 & curtis strange & united states & 70-76-71-74=291 & 3 & 22500 \\
9 & t10 & seve ballesteros & spain & 72-70-72-78=292 & 4 & 17000 \\
10 & t10 & david frost & south africa & 75-70-71-76=292 & 4 & 17000 \\
11 & t10 & tom kite & united states & 72-77-71-72=292 & 4 & 17000 \\
12 & t10 & nick price & zimbabwe & 76-71-70-75=292 & 4 & 17000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& score \\
\midrule
0 & 72-70-72-78=292 \\
1 & 75-70-71-76=292 \\
2 & 72-77-71-72=292 \\
3 & 76-71-70-75=292 \\
\bottomrule
\end{tabular}
| select score where money ($) = 17000 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
<th>player</th>
<th>country</th>
<th>score</th>
<th>to par</th>
<th>money ($)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>t1</td>
<td>larry nelson</td>
<td>united states</td>
<td>70-72-73-72=287</td>
<td>-1</td>
<td>playoff</td>
</tr>
<tr>
<th>1</th>
<td>t1</td>
<td>lanny wadkins</td>
<td>united states</td>
<td>70-70-74-73=287</td>
<td>-1</td>
<td>playoff</td>
</tr>
<tr>
<th>2</th>
<td>t3</td>
<td>scott hoch</td>
<td>united states</td>
<td>74-74-71-69=288</td>
<td>e</td>
<td>58750</td>
</tr>
<tr>
<th>3</th>
<td>t3</td>
<td>d. a. weibring</td>
<td>united states</td>
<td>73-72-67-76=288</td>
<td>e</td>
<td>58750</td>
</tr>
<tr>
<th>4</th>
<td>t5</td>
<td>mark mccumber</td>
<td>united states</td>
<td>74-69-69-77=289</td>
<td>1</td>
<td>37500</td>
</tr>
<tr>
<th>5</th>
<td>t5</td>
<td>don pooley</td>
<td>united states</td>
<td>73-71-73-72=289</td>
<td>1</td>
<td>37500</td>
</tr>
<tr>
<th>6</th>
<td>t7</td>
<td>ben crenshaw</td>
<td>united states</td>
<td>72-70-74-74=290</td>
<td>2</td>
<td>27500</td>
</tr>
<tr>
<th>7</th>
<td>t7</td>
<td>bobby wadkins</td>
<td>united states</td>
<td>68-74-71-77=290</td>
<td>2</td>
<td>27500</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>curtis strange</td>
<td>united states</td>
<td>70-76-71-74=291</td>
<td>3</td>
<td>22500</td>
</tr>
<tr>
<th>9</th>
<td>t10</td>
<td>seve ballesteros</td>
<td>spain</td>
<td>72-70-72-78=292</td>
<td>4</td>
<td>17000</td>
</tr>
<tr>
<th>10</th>
<td>t10</td>
<td>david frost</td>
<td>south africa</td>
<td>75-70-71-76=292</td>
<td>4</td>
<td>17000</td>
</tr>
<tr>
<th>11</th>
<td>t10</td>
<td>tom kite</td>
<td>united states</td>
<td>72-77-71-72=292</td>
<td>4</td>
<td>17000</td>
</tr>
<tr>
<th>12</th>
<td>t10</td>
<td>nick price</td>
<td>zimbabwe</td>
<td>76-71-70-75=292</td>
<td>4</td>
<td>17000</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>score</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>72-70-72-78=292</td>
</tr>
<tr>
<th>1</th>
<td>75-70-71-76=292</td>
</tr>
<tr>
<th>2</th>
<td>72-77-71-72=292</td>
</tr>
<tr>
<th>3</th>
<td>76-71-70-75=292</td>
</tr>
</tbody>
</table> | select score where money ($) = 17000 <table_name> : table | | place | player | country | score | to par | money ($) |
|---:|:--------|:-----------------|:--------------|:----------------|:---------|:------------|
| 0 | t1 | larry nelson | united states | 70-72-73-72=287 | -1 | playoff |
| 1 | t1 | lanny wadkins | united states | 70-70-74-73=287 | -1 | playoff |
| 2 | t3 | scott hoch | united states | 74-74-71-69=288 | e | 58750 |
| 3 | t3 | d. a. weibring | united states | 73-72-67-76=288 | e | 58750 |
| 4 | t5 | mark mccumber | united states | 74-69-69-77=289 | 1 | 37500 |
| 5 | t5 | don pooley | united states | 73-71-73-72=289 | 1 | 37500 |
| 6 | t7 | ben crenshaw | united states | 72-70-74-74=290 | 2 | 27500 |
| 7 | t7 | bobby wadkins | united states | 68-74-71-77=290 | 2 | 27500 |
| 8 | 9 | curtis strange | united states | 70-76-71-74=291 | 3 | 22500 |
| 9 | t10 | seve ballesteros | spain | 72-70-72-78=292 | 4 | 17000 |
| 10 | t10 | david frost | south africa | 75-70-71-76=292 | 4 | 17000 |
| 11 | t10 | tom kite | united states | 72-77-71-72=292 | 4 | 17000 |
| 12 | t10 | nick price | zimbabwe | 76-71-70-75=292 | 4 | 17000 | | | | score |
|---:|:----------------|
| 0 | 72-70-72-78=292 |
| 1 | 75-70-71-76=292 |
| 2 | 72-77-71-72=292 |
| 3 | 76-71-70-75=292 | | [
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select attendance where conference = 'wikimania 2010' col : conference | date | place | attendance | archive of presentations row 1 : wikimania 2005 | 2007-08-05 00:00:00 | frankfurt, germany | 380 | slides, video row 2 : wikimania 2006 | 2006-08-04 00:00:00 | cambridge, united states | 400 | slides and papers, video row 3 : wikimania 2007 | 2005-08-03 00:00:00 | taipei, roc (taiwan) | 440 | commons gallery row 4 : wikimania 2008 | 2019-07-17 00:00:00 | alexandria, egypt | 650 | abstracts, slides,video row 5 : wikimania 2009 | 2028-08-26 00:00:00 | buenos aires, argentina | 559 | slides, video row 6 : wikimania 2010 | 2011-07-09 00:00:00 | gdansk, poland | about 500 | slides row 7 : wikimania 2011 | 2007-08-04 00:00:00 | haifa, israel | 720 | presentations, video row 8 : wikimania 2012 | 2015-07-12 00:00:00 | washington, d.c., united states | 1400 | presentations, videos row 9 : wikimania 2013 | 2011-08-07 00:00:00 | hong kong | 700 | presentations, videos row 10 : wikimania 2014 | 2010-08-06 00:00:00 | london, united kingdom | none | none | col : attendance row 1 : about 500 | select attendance where conference = 'wikimania 2010' <table_name> : table \begin{tabular}{llllll}
\toprule
& conference & date & place & attendance & archive of presentations \\
\midrule
0 & wikimania 2005 & 2007-08-05 00:00:00 & frankfurt, germany & 380 & slides, video \\
1 & wikimania 2006 & 2006-08-04 00:00:00 & cambridge, united states & 400 & slides and papers, video \\
2 & wikimania 2007 & 2005-08-03 00:00:00 & taipei, roc (taiwan) & 440 & commons gallery \\
3 & wikimania 2008 & 2019-07-17 00:00:00 & alexandria, egypt & 650 & abstracts, slides,video \\
4 & wikimania 2009 & 2028-08-26 00:00:00 & buenos aires, argentina & 559 & slides, video \\
5 & wikimania 2010 & 2011-07-09 00:00:00 & gdansk, poland & about 500 & slides \\
6 & wikimania 2011 & 2007-08-04 00:00:00 & haifa, israel & 720 & presentations, video \\
7 & wikimania 2012 & 2015-07-12 00:00:00 & washington, d.c., united states & 1400 & presentations, videos \\
8 & wikimania 2013 & 2011-08-07 00:00:00 & hong kong & 700 & presentations, videos \\
9 & wikimania 2014 & 2010-08-06 00:00:00 & london, united kingdom & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& attendance \\
\midrule
0 & about 500 \\
\bottomrule
\end{tabular}
| select attendance where conference = 'wikimania 2010' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>conference</th>
<th>date</th>
<th>place</th>
<th>attendance</th>
<th>archive of presentations</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>wikimania 2005</td>
<td>2007-08-05 00:00:00</td>
<td>frankfurt, germany</td>
<td>380</td>
<td>slides, video</td>
</tr>
<tr>
<th>1</th>
<td>wikimania 2006</td>
<td>2006-08-04 00:00:00</td>
<td>cambridge, united states</td>
<td>400</td>
<td>slides and papers, video</td>
</tr>
<tr>
<th>2</th>
<td>wikimania 2007</td>
<td>2005-08-03 00:00:00</td>
<td>taipei, roc (taiwan)</td>
<td>440</td>
<td>commons gallery</td>
</tr>
<tr>
<th>3</th>
<td>wikimania 2008</td>
<td>2019-07-17 00:00:00</td>
<td>alexandria, egypt</td>
<td>650</td>
<td>abstracts, slides,video</td>
</tr>
<tr>
<th>4</th>
<td>wikimania 2009</td>
<td>2028-08-26 00:00:00</td>
<td>buenos aires, argentina</td>
<td>559</td>
<td>slides, video</td>
</tr>
<tr>
<th>5</th>
<td>wikimania 2010</td>
<td>2011-07-09 00:00:00</td>
<td>gdansk, poland</td>
<td>about 500</td>
<td>slides</td>
</tr>
<tr>
<th>6</th>
<td>wikimania 2011</td>
<td>2007-08-04 00:00:00</td>
<td>haifa, israel</td>
<td>720</td>
<td>presentations, video</td>
</tr>
<tr>
<th>7</th>
<td>wikimania 2012</td>
<td>2015-07-12 00:00:00</td>
<td>washington, d.c., united states</td>
<td>1400</td>
<td>presentations, videos</td>
</tr>
<tr>
<th>8</th>
<td>wikimania 2013</td>
<td>2011-08-07 00:00:00</td>
<td>hong kong</td>
<td>700</td>
<td>presentations, videos</td>
</tr>
<tr>
<th>9</th>
<td>wikimania 2014</td>
<td>2010-08-06 00:00:00</td>
<td>london, united kingdom</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>about 500</td>
</tr>
</tbody>
</table> | select attendance where conference = 'wikimania 2010' <table_name> : table | | conference | date | place | attendance | archive of presentations |
|---:|:---------------|:--------------------|:--------------------------------|:-------------|:---------------------------|
| 0 | wikimania 2005 | 2007-08-05 00:00:00 | frankfurt, germany | 380 | slides, video |
| 1 | wikimania 2006 | 2006-08-04 00:00:00 | cambridge, united states | 400 | slides and papers, video |
| 2 | wikimania 2007 | 2005-08-03 00:00:00 | taipei, roc (taiwan) | 440 | commons gallery |
| 3 | wikimania 2008 | 2019-07-17 00:00:00 | alexandria, egypt | 650 | abstracts, slides,video |
| 4 | wikimania 2009 | 2028-08-26 00:00:00 | buenos aires, argentina | 559 | slides, video |
| 5 | wikimania 2010 | 2011-07-09 00:00:00 | gdansk, poland | about 500 | slides |
| 6 | wikimania 2011 | 2007-08-04 00:00:00 | haifa, israel | 720 | presentations, video |
| 7 | wikimania 2012 | 2015-07-12 00:00:00 | washington, d.c., united states | 1400 | presentations, videos |
| 8 | wikimania 2013 | 2011-08-07 00:00:00 | hong kong | 700 | presentations, videos |
| 9 | wikimania 2014 | 2010-08-06 00:00:00 | london, united kingdom | none | none | | | | attendance |
|---:|:-------------|
| 0 | about 500 | | [
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select count ( date ) where discipline = 11 col : season | date | location | discipline | place row 1 : 1993 | 1993-02-27 00:00:00 | whistler, bc, canada | downhill | 2nd row 2 : 1994 | 1993-12-12 00:00:00 | val-d'isere, france | super g | 3rd row 3 : 1994 | 1993-12-29 00:00:00 | bormio, italy | downhill | 3rd row 4 : 1994 | 1994-03-12 00:00:00 | whistler, bc, canada | downhill | 3rd row 5 : 1994 | 1994-03-13 00:00:00 | whistler, bc, canada | super g | 1st row 6 : 1994 | 1994-03-16 00:00:00 | vail, co, usa | downhill | 3rd row 7 : 1995 | 1994-12-11 00:00:00 | tignes, france | super g | 2nd | col : count ( "date" ) row 1 : 0 | select count ( date ) where discipline = 11 <table_name> : table \begin{tabular}{llllll}
\toprule
& season & date & location & discipline & place \\
\midrule
0 & 1993 & 1993-02-27 00:00:00 & whistler, bc, canada & downhill & 2nd \\
1 & 1994 & 1993-12-12 00:00:00 & val-d'isere, france & super g & 3rd \\
2 & 1994 & 1993-12-29 00:00:00 & bormio, italy & downhill & 3rd \\
3 & 1994 & 1994-03-12 00:00:00 & whistler, bc, canada & downhill & 3rd \\
4 & 1994 & 1994-03-13 00:00:00 & whistler, bc, canada & super g & 1st \\
5 & 1994 & 1994-03-16 00:00:00 & vail, co, usa & downhill & 3rd \\
6 & 1995 & 1994-12-11 00:00:00 & tignes, france & super g & 2nd \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "date" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( date ) where discipline = 11 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>date</th>
<th>location</th>
<th>discipline</th>
<th>place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1993</td>
<td>1993-02-27 00:00:00</td>
<td>whistler, bc, canada</td>
<td>downhill</td>
<td>2nd</td>
</tr>
<tr>
<th>1</th>
<td>1994</td>
<td>1993-12-12 00:00:00</td>
<td>val-d'isere, france</td>
<td>super g</td>
<td>3rd</td>
</tr>
<tr>
<th>2</th>
<td>1994</td>
<td>1993-12-29 00:00:00</td>
<td>bormio, italy</td>
<td>downhill</td>
<td>3rd</td>
</tr>
<tr>
<th>3</th>
<td>1994</td>
<td>1994-03-12 00:00:00</td>
<td>whistler, bc, canada</td>
<td>downhill</td>
<td>3rd</td>
</tr>
<tr>
<th>4</th>
<td>1994</td>
<td>1994-03-13 00:00:00</td>
<td>whistler, bc, canada</td>
<td>super g</td>
<td>1st</td>
</tr>
<tr>
<th>5</th>
<td>1994</td>
<td>1994-03-16 00:00:00</td>
<td>vail, co, usa</td>
<td>downhill</td>
<td>3rd</td>
</tr>
<tr>
<th>6</th>
<td>1995</td>
<td>1994-12-11 00:00:00</td>
<td>tignes, france</td>
<td>super g</td>
<td>2nd</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "date" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( date ) where discipline = 11 <table_name> : table | | season | date | location | discipline | place |
|---:|---------:|:--------------------|:---------------------|:-------------|:--------|
| 0 | 1993 | 1993-02-27 00:00:00 | whistler, bc, canada | downhill | 2nd |
| 1 | 1994 | 1993-12-12 00:00:00 | val-d'isere, france | super g | 3rd |
| 2 | 1994 | 1993-12-29 00:00:00 | bormio, italy | downhill | 3rd |
| 3 | 1994 | 1994-03-12 00:00:00 | whistler, bc, canada | downhill | 3rd |
| 4 | 1994 | 1994-03-13 00:00:00 | whistler, bc, canada | super g | 1st |
| 5 | 1994 | 1994-03-16 00:00:00 | vail, co, usa | downhill | 3rd |
| 6 | 1995 | 1994-12-11 00:00:00 | tignes, france | super g | 2nd | | | | count ( "date" ) |
|---:|-------------------:|
| 0 | 0 | | [
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select position where year = 1987 col : year | song | album | position | chart row 1 : 1987 | "summergirls" | 24/7 | 50 | billboard hot 100 row 2 : 1989 | "24/7" | 24/7 | 42 | billboard hot 100 row 3 : 1989 | "24/7" | 24/7 | 12 | hot r&b/hip-hop songs row 4 : 1989 | "i like it" | 24/7 | 7 | billboard hot 100 row 5 : 1989 | "i like it" | 24/7 | 3 | hot dance club play row 6 : 1989 | "sunshine" | 24/7 | 23 | billboard hot 100 row 7 : 1990 | "never 2 much of u" | 24/7 | 61 | billboard hot 100 row 8 : 1990 | "romeo" | swingin' | 6 | billboard hot 100 row 9 : 1991 | "gentle" | swingin' | 31 | billboard hot 100 row 10 : 1993 | "ooh child" | the way i am | 27 | billboard hot 100 row 11 : 1993 | "endlessly" | the way i am | none | billboard hot 100 | col : position row 1 : 50 | select position where year = 1987 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & song & album & position & chart \\
\midrule
0 & 1987 & "summergirls" & 24/7 & 50 & billboard hot 100 \\
1 & 1989 & "24/7" & 24/7 & 42 & billboard hot 100 \\
2 & 1989 & "24/7" & 24/7 & 12 & hot r&b/hip-hop songs \\
3 & 1989 & "i like it" & 24/7 & 7 & billboard hot 100 \\
4 & 1989 & "i like it" & 24/7 & 3 & hot dance club play \\
5 & 1989 & "sunshine" & 24/7 & 23 & billboard hot 100 \\
6 & 1990 & "never 2 much of u" & 24/7 & 61 & billboard hot 100 \\
7 & 1990 & "romeo" & swingin' & 6 & billboard hot 100 \\
8 & 1991 & "gentle" & swingin' & 31 & billboard hot 100 \\
9 & 1993 & "ooh child" & the way i am & 27 & billboard hot 100 \\
10 & 1993 & "endlessly" & the way i am & none & billboard hot 100 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& position \\
\midrule
0 & 50 \\
\bottomrule
\end{tabular}
| select position where year = 1987 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>song</th>
<th>album</th>
<th>position</th>
<th>chart</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1987</td>
<td>"summergirls"</td>
<td>24/7</td>
<td>50</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>1</th>
<td>1989</td>
<td>"24/7"</td>
<td>24/7</td>
<td>42</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>2</th>
<td>1989</td>
<td>"24/7"</td>
<td>24/7</td>
<td>12</td>
<td>hot r&b/hip-hop songs</td>
</tr>
<tr>
<th>3</th>
<td>1989</td>
<td>"i like it"</td>
<td>24/7</td>
<td>7</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>4</th>
<td>1989</td>
<td>"i like it"</td>
<td>24/7</td>
<td>3</td>
<td>hot dance club play</td>
</tr>
<tr>
<th>5</th>
<td>1989</td>
<td>"sunshine"</td>
<td>24/7</td>
<td>23</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>6</th>
<td>1990</td>
<td>"never 2 much of u"</td>
<td>24/7</td>
<td>61</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>7</th>
<td>1990</td>
<td>"romeo"</td>
<td>swingin'</td>
<td>6</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>8</th>
<td>1991</td>
<td>"gentle"</td>
<td>swingin'</td>
<td>31</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>9</th>
<td>1993</td>
<td>"ooh child"</td>
<td>the way i am</td>
<td>27</td>
<td>billboard hot 100</td>
</tr>
<tr>
<th>10</th>
<td>1993</td>
<td>"endlessly"</td>
<td>the way i am</td>
<td>none</td>
<td>billboard hot 100</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>position</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>50</td>
</tr>
</tbody>
</table> | select position where year = 1987 <table_name> : table | | year | song | album | position | chart |
|---:|-------:|:--------------------|:-------------|:-----------|:----------------------|
| 0 | 1987 | "summergirls" | 24/7 | 50 | billboard hot 100 |
| 1 | 1989 | "24/7" | 24/7 | 42 | billboard hot 100 |
| 2 | 1989 | "24/7" | 24/7 | 12 | hot r&b/hip-hop songs |
| 3 | 1989 | "i like it" | 24/7 | 7 | billboard hot 100 |
| 4 | 1989 | "i like it" | 24/7 | 3 | hot dance club play |
| 5 | 1989 | "sunshine" | 24/7 | 23 | billboard hot 100 |
| 6 | 1990 | "never 2 much of u" | 24/7 | 61 | billboard hot 100 |
| 7 | 1990 | "romeo" | swingin' | 6 | billboard hot 100 |
| 8 | 1991 | "gentle" | swingin' | 31 | billboard hot 100 |
| 9 | 1993 | "ooh child" | the way i am | 27 | billboard hot 100 |
| 10 | 1993 | "endlessly" | the way i am | none | billboard hot 100 | | | | position |
|---:|-----------:|
| 0 | 50 | | [
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select nation where nation = 'uzbekistan (uzb)' col : rank | nation | gold | silver | bronze | total row 1 : 1 | vietnam (vie) | 3 | 0 | 3 | 6 row 2 : 2 | south korea (kor) | 2 | 1 | 2 | 5 row 3 : 3 | kyrgyzstan (kgz) | 1 | 1 | 2 | 4 row 4 : 4 | kazakhstan (kaz) | 1 | 1 | 1 | 3 row 5 : 5 | iraq (irq) | 1 | 0 | 1 | 2 row 6 : 5 | turkmenistan (tkm) | 1 | 0 | 1 | 2 row 7 : 7 | jordan (jor) | 0 | 2 | 3 | 5 row 8 : 8 | uzbekistan (uzb) | 0 | 2 | 1 | 3 row 9 : 9 | tajikistan (tjk) | 0 | 1 | 1 | 2 row 10 : 10 | kuwait (kuw) | 0 | 1 | 0 | 1 row 11 : 11 | independent athletes (aoi) | 0 | 0 | 1 | 1 row 12 : 11 | mongolia (mgl) | 0 | 0 | 1 | 1 row 13 : 11 | palestine (ple) | 0 | 0 | 1 | 1 row 14 : total | total | 9 | 9 | 18 | 36 | col : nation row 1 : uzbekistan (uzb) | select nation where nation = 'uzbekistan (uzb)' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & vietnam (vie) & 3 & 0 & 3 & 6 \\
1 & 2 & south korea (kor) & 2 & 1 & 2 & 5 \\
2 & 3 & kyrgyzstan (kgz) & 1 & 1 & 2 & 4 \\
3 & 4 & kazakhstan (kaz) & 1 & 1 & 1 & 3 \\
4 & 5 & iraq (irq) & 1 & 0 & 1 & 2 \\
5 & 5 & turkmenistan (tkm) & 1 & 0 & 1 & 2 \\
6 & 7 & jordan (jor) & 0 & 2 & 3 & 5 \\
7 & 8 & uzbekistan (uzb) & 0 & 2 & 1 & 3 \\
8 & 9 & tajikistan (tjk) & 0 & 1 & 1 & 2 \\
9 & 10 & kuwait (kuw) & 0 & 1 & 0 & 1 \\
10 & 11 & independent athletes (aoi) & 0 & 0 & 1 & 1 \\
11 & 11 & mongolia (mgl) & 0 & 0 & 1 & 1 \\
12 & 11 & palestine (ple) & 0 & 0 & 1 & 1 \\
13 & total & total & 9 & 9 & 18 & 36 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & uzbekistan (uzb) \\
\bottomrule
\end{tabular}
| select nation where nation = 'uzbekistan (uzb)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>vietnam (vie)</td>
<td>3</td>
<td>0</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>south korea (kor)</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>5</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>kyrgyzstan (kgz)</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>kazakhstan (kaz)</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>iraq (irq)</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>turkmenistan (tkm)</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>jordan (jor)</td>
<td>0</td>
<td>2</td>
<td>3</td>
<td>5</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>uzbekistan (uzb)</td>
<td>0</td>
<td>2</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>tajikistan (tjk)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>kuwait (kuw)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>independent athletes (aoi)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>mongolia (mgl)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>11</td>
<td>palestine (ple)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>total</td>
<td>total</td>
<td>9</td>
<td>9</td>
<td>18</td>
<td>36</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>uzbekistan (uzb)</td>
</tr>
</tbody>
</table> | select nation where nation = 'uzbekistan (uzb)' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | vietnam (vie) | 3 | 0 | 3 | 6 |
| 1 | 2 | south korea (kor) | 2 | 1 | 2 | 5 |
| 2 | 3 | kyrgyzstan (kgz) | 1 | 1 | 2 | 4 |
| 3 | 4 | kazakhstan (kaz) | 1 | 1 | 1 | 3 |
| 4 | 5 | iraq (irq) | 1 | 0 | 1 | 2 |
| 5 | 5 | turkmenistan (tkm) | 1 | 0 | 1 | 2 |
| 6 | 7 | jordan (jor) | 0 | 2 | 3 | 5 |
| 7 | 8 | uzbekistan (uzb) | 0 | 2 | 1 | 3 |
| 8 | 9 | tajikistan (tjk) | 0 | 1 | 1 | 2 |
| 9 | 10 | kuwait (kuw) | 0 | 1 | 0 | 1 |
| 10 | 11 | independent athletes (aoi) | 0 | 0 | 1 | 1 |
| 11 | 11 | mongolia (mgl) | 0 | 0 | 1 | 1 |
| 12 | 11 | palestine (ple) | 0 | 0 | 1 | 1 |
| 13 | total | total | 9 | 9 | 18 | 36 | | | | nation |
|---:|:-----------------|
| 0 | uzbekistan (uzb) | | [
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select count ( * ) where venue = 'kingston, jamaica' col : year | competition | venue | position | notes row 1 : 2002 | world junior championships | kingston, jamaica | 1st | 64.51 m (1.75 kg) row 2 : 2002 | asian games | busan, south korea | 1st | 60.76 m row 3 : 2003 | universiade | daegu, south korea | 1st | 62.32 m row 4 : 2003 | asian championships | manila, philippines | 1st | 61.43 m row 5 : 2004 | olympic games | athens, greece | 18th (q) | 60.60 m row 6 : 2005 | world championships | helsinki, finland | 18th (q) | 61.75 m row 7 : 2005 | universiade | izmir, turkey | 7th | 59.67 m row 8 : 2005 | east asian games | macau | 1st | 61.74 m row 9 : 2006 | asian games | doha, qatar | 5th | 58.54 m row 10 : 2009 | asian championships | guangzhou, china | 3rd | 59.27 m | col : count ( "*" ) row 1 : 1 | select count ( * ) where venue = 'kingston, jamaica' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & competition & venue & position & notes \\
\midrule
0 & 2002 & world junior championships & kingston, jamaica & 1st & 64.51 m (1.75 kg) \\
1 & 2002 & asian games & busan, south korea & 1st & 60.76 m \\
2 & 2003 & universiade & daegu, south korea & 1st & 62.32 m \\
3 & 2003 & asian championships & manila, philippines & 1st & 61.43 m \\
4 & 2004 & olympic games & athens, greece & 18th (q) & 60.60 m \\
5 & 2005 & world championships & helsinki, finland & 18th (q) & 61.75 m \\
6 & 2005 & universiade & izmir, turkey & 7th & 59.67 m \\
7 & 2005 & east asian games & macau & 1st & 61.74 m \\
8 & 2006 & asian games & doha, qatar & 5th & 58.54 m \\
9 & 2009 & asian championships & guangzhou, china & 3rd & 59.27 m \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where venue = 'kingston, jamaica' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>competition</th>
<th>venue</th>
<th>position</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2002</td>
<td>world junior championships</td>
<td>kingston, jamaica</td>
<td>1st</td>
<td>64.51 m (1.75 kg)</td>
</tr>
<tr>
<th>1</th>
<td>2002</td>
<td>asian games</td>
<td>busan, south korea</td>
<td>1st</td>
<td>60.76 m</td>
</tr>
<tr>
<th>2</th>
<td>2003</td>
<td>universiade</td>
<td>daegu, south korea</td>
<td>1st</td>
<td>62.32 m</td>
</tr>
<tr>
<th>3</th>
<td>2003</td>
<td>asian championships</td>
<td>manila, philippines</td>
<td>1st</td>
<td>61.43 m</td>
</tr>
<tr>
<th>4</th>
<td>2004</td>
<td>olympic games</td>
<td>athens, greece</td>
<td>18th (q)</td>
<td>60.60 m</td>
</tr>
<tr>
<th>5</th>
<td>2005</td>
<td>world championships</td>
<td>helsinki, finland</td>
<td>18th (q)</td>
<td>61.75 m</td>
</tr>
<tr>
<th>6</th>
<td>2005</td>
<td>universiade</td>
<td>izmir, turkey</td>
<td>7th</td>
<td>59.67 m</td>
</tr>
<tr>
<th>7</th>
<td>2005</td>
<td>east asian games</td>
<td>macau</td>
<td>1st</td>
<td>61.74 m</td>
</tr>
<tr>
<th>8</th>
<td>2006</td>
<td>asian games</td>
<td>doha, qatar</td>
<td>5th</td>
<td>58.54 m</td>
</tr>
<tr>
<th>9</th>
<td>2009</td>
<td>asian championships</td>
<td>guangzhou, china</td>
<td>3rd</td>
<td>59.27 m</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where venue = 'kingston, jamaica' <table_name> : table | | year | competition | venue | position | notes |
|---:|-------:|:---------------------------|:--------------------|:-----------|:------------------|
| 0 | 2002 | world junior championships | kingston, jamaica | 1st | 64.51 m (1.75 kg) |
| 1 | 2002 | asian games | busan, south korea | 1st | 60.76 m |
| 2 | 2003 | universiade | daegu, south korea | 1st | 62.32 m |
| 3 | 2003 | asian championships | manila, philippines | 1st | 61.43 m |
| 4 | 2004 | olympic games | athens, greece | 18th (q) | 60.60 m |
| 5 | 2005 | world championships | helsinki, finland | 18th (q) | 61.75 m |
| 6 | 2005 | universiade | izmir, turkey | 7th | 59.67 m |
| 7 | 2005 | east asian games | macau | 1st | 61.74 m |
| 8 | 2006 | asian games | doha, qatar | 5th | 58.54 m |
| 9 | 2009 | asian championships | guangzhou, china | 3rd | 59.27 m | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where position = 'forward' col : # | name | position | birthday | size | weight | last team row 1 : 4 | tom lipke | guard/ forward | 12.04.1986 | 1,96 m | 98 kg | bremen roosters row 2 : 5 | muamer taletovic | guard | 02.04.1976 | 1,87 m | 90 kg | hertener lowen row 3 : 6 | david watson | guard | 16.09.1988 | 1,84 m | 78 kg | ssc karlsruhe row 4 : 7 | brandon gary | forward | 26.01.1983 | 2,03 m | 100 kg | iserlohn kangaroos row 5 : 8 | theodis tarver | center | 09.07.1984 | 2,06 m | 110 kg | bremen roosters row 6 : 9 | stefan svitek | forward | 25.05.1977 | 2,03 m | 108 kg | chemosvit svit row 7 : 10 | michael baumer | guard | 08.08.1990 | 1,80 m | 68 kg | bg karlsruhe row 8 : 11 | clifford crawford | guard | 07.01.1981 | 1,92 m | 98 kg | bremen roosters row 9 : 12 | max roser | guard/ forward | 31.07.1988 | 1,94 m | 87 kg | sg bad durkheim/speyer row 10 : 13 | edward seward | center | 20.10.1978 | 2,06 m | 110 kg | aschersleben tiger row 11 : 14 | julius parrisius | guard | 01.08.1985 | 1,85 m | 85 kg | union shops rastatt row 12 : 15 | leo niebuhr | forward | 04.08.1986 | 2,06 m | 88 kg | sg braunschweig row 13 : 16 | alexander rueck | guard | 24.03.1984 | 1,89 m | 85 kg | union shops rastatt row 14 : 17 | matthias hurst | forward/ center | 06.10.1989 | 2,04 m | 86 kg | bg karlsruhe | col : count ( "*" ) row 1 : 3 | select count ( * ) where position = 'forward' <table_name> : table \begin{tabular}{llllllll}
\toprule
& # & name & position & birthday & size & weight & last team \\
\midrule
0 & 4 & tom lipke & guard/ forward & 12.04.1986 & 1,96 m & 98 kg & bremen roosters \\
1 & 5 & muamer taletovic & guard & 02.04.1976 & 1,87 m & 90 kg & hertener lowen \\
2 & 6 & david watson & guard & 16.09.1988 & 1,84 m & 78 kg & ssc karlsruhe \\
3 & 7 & brandon gary & forward & 26.01.1983 & 2,03 m & 100 kg & iserlohn kangaroos \\
4 & 8 & theodis tarver & center & 09.07.1984 & 2,06 m & 110 kg & bremen roosters \\
5 & 9 & stefan svitek & forward & 25.05.1977 & 2,03 m & 108 kg & chemosvit svit \\
6 & 10 & michael baumer & guard & 08.08.1990 & 1,80 m & 68 kg & bg karlsruhe \\
7 & 11 & clifford crawford & guard & 07.01.1981 & 1,92 m & 98 kg & bremen roosters \\
8 & 12 & max roser & guard/ forward & 31.07.1988 & 1,94 m & 87 kg & sg bad durkheim/speyer \\
9 & 13 & edward seward & center & 20.10.1978 & 2,06 m & 110 kg & aschersleben tiger \\
10 & 14 & julius parrisius & guard & 01.08.1985 & 1,85 m & 85 kg & union shops rastatt \\
11 & 15 & leo niebuhr & forward & 04.08.1986 & 2,06 m & 88 kg & sg braunschweig \\
12 & 16 & alexander rueck & guard & 24.03.1984 & 1,89 m & 85 kg & union shops rastatt \\
13 & 17 & matthias hurst & forward/ center & 06.10.1989 & 2,04 m & 86 kg & bg karlsruhe \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( * ) where position = 'forward' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>name</th>
<th>position</th>
<th>birthday</th>
<th>size</th>
<th>weight</th>
<th>last team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
<td>tom lipke</td>
<td>guard/ forward</td>
<td>12.04.1986</td>
<td>1,96 m</td>
<td>98 kg</td>
<td>bremen roosters</td>
</tr>
<tr>
<th>1</th>
<td>5</td>
<td>muamer taletovic</td>
<td>guard</td>
<td>02.04.1976</td>
<td>1,87 m</td>
<td>90 kg</td>
<td>hertener lowen</td>
</tr>
<tr>
<th>2</th>
<td>6</td>
<td>david watson</td>
<td>guard</td>
<td>16.09.1988</td>
<td>1,84 m</td>
<td>78 kg</td>
<td>ssc karlsruhe</td>
</tr>
<tr>
<th>3</th>
<td>7</td>
<td>brandon gary</td>
<td>forward</td>
<td>26.01.1983</td>
<td>2,03 m</td>
<td>100 kg</td>
<td>iserlohn kangaroos</td>
</tr>
<tr>
<th>4</th>
<td>8</td>
<td>theodis tarver</td>
<td>center</td>
<td>09.07.1984</td>
<td>2,06 m</td>
<td>110 kg</td>
<td>bremen roosters</td>
</tr>
<tr>
<th>5</th>
<td>9</td>
<td>stefan svitek</td>
<td>forward</td>
<td>25.05.1977</td>
<td>2,03 m</td>
<td>108 kg</td>
<td>chemosvit svit</td>
</tr>
<tr>
<th>6</th>
<td>10</td>
<td>michael baumer</td>
<td>guard</td>
<td>08.08.1990</td>
<td>1,80 m</td>
<td>68 kg</td>
<td>bg karlsruhe</td>
</tr>
<tr>
<th>7</th>
<td>11</td>
<td>clifford crawford</td>
<td>guard</td>
<td>07.01.1981</td>
<td>1,92 m</td>
<td>98 kg</td>
<td>bremen roosters</td>
</tr>
<tr>
<th>8</th>
<td>12</td>
<td>max roser</td>
<td>guard/ forward</td>
<td>31.07.1988</td>
<td>1,94 m</td>
<td>87 kg</td>
<td>sg bad durkheim/speyer</td>
</tr>
<tr>
<th>9</th>
<td>13</td>
<td>edward seward</td>
<td>center</td>
<td>20.10.1978</td>
<td>2,06 m</td>
<td>110 kg</td>
<td>aschersleben tiger</td>
</tr>
<tr>
<th>10</th>
<td>14</td>
<td>julius parrisius</td>
<td>guard</td>
<td>01.08.1985</td>
<td>1,85 m</td>
<td>85 kg</td>
<td>union shops rastatt</td>
</tr>
<tr>
<th>11</th>
<td>15</td>
<td>leo niebuhr</td>
<td>forward</td>
<td>04.08.1986</td>
<td>2,06 m</td>
<td>88 kg</td>
<td>sg braunschweig</td>
</tr>
<tr>
<th>12</th>
<td>16</td>
<td>alexander rueck</td>
<td>guard</td>
<td>24.03.1984</td>
<td>1,89 m</td>
<td>85 kg</td>
<td>union shops rastatt</td>
</tr>
<tr>
<th>13</th>
<td>17</td>
<td>matthias hurst</td>
<td>forward/ center</td>
<td>06.10.1989</td>
<td>2,04 m</td>
<td>86 kg</td>
<td>bg karlsruhe</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( * ) where position = 'forward' <table_name> : table | | # | name | position | birthday | size | weight | last team |
|---:|----:|:------------------|:----------------|:-----------|:-------|:---------|:-----------------------|
| 0 | 4 | tom lipke | guard/ forward | 12.04.1986 | 1,96 m | 98 kg | bremen roosters |
| 1 | 5 | muamer taletovic | guard | 02.04.1976 | 1,87 m | 90 kg | hertener lowen |
| 2 | 6 | david watson | guard | 16.09.1988 | 1,84 m | 78 kg | ssc karlsruhe |
| 3 | 7 | brandon gary | forward | 26.01.1983 | 2,03 m | 100 kg | iserlohn kangaroos |
| 4 | 8 | theodis tarver | center | 09.07.1984 | 2,06 m | 110 kg | bremen roosters |
| 5 | 9 | stefan svitek | forward | 25.05.1977 | 2,03 m | 108 kg | chemosvit svit |
| 6 | 10 | michael baumer | guard | 08.08.1990 | 1,80 m | 68 kg | bg karlsruhe |
| 7 | 11 | clifford crawford | guard | 07.01.1981 | 1,92 m | 98 kg | bremen roosters |
| 8 | 12 | max roser | guard/ forward | 31.07.1988 | 1,94 m | 87 kg | sg bad durkheim/speyer |
| 9 | 13 | edward seward | center | 20.10.1978 | 2,06 m | 110 kg | aschersleben tiger |
| 10 | 14 | julius parrisius | guard | 01.08.1985 | 1,85 m | 85 kg | union shops rastatt |
| 11 | 15 | leo niebuhr | forward | 04.08.1986 | 2,06 m | 88 kg | sg braunschweig |
| 12 | 16 | alexander rueck | guard | 24.03.1984 | 1,89 m | 85 kg | union shops rastatt |
| 13 | 17 | matthias hurst | forward/ center | 06.10.1989 | 2,04 m | 86 kg | bg karlsruhe | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 3 | | [
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