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|---|---|---|---|---|---|---|---|---|---|---|
select residence where % = '19.6' col : riding | candidate | gender | residence | occupation | votes | % | rank | biographical notes row 1 : cape breton-canso | mark macneill | m | inverness | government and business policy advisor | 7660 | 21.1 | 3rd | served in ottawa as a consultant with national advisory board on science and technology, with the treasury board secretariat and the solicitor general's aboriginal policing secretariat row 2 : central nova | mary louise lorefice | f | antigonish | retired educator | 7659 | 19.6 | 3rd | lorefice is a retired teacher from antigonish, who has lived in the community for 38 years row 3 : cumberland-colchester-musquodoboit valley | karen olsson | f | north river | stay-at-home mother | 4874 | 12.3 | 2nd | none row 4 : dartmouth-cole harbour | brad pye | m | ottawa, on | senior political party program officer | 12793 | 31.5 | 2nd | pye is an international development worker and son of former dartmouth north mla jerry pye row 5 : halifax | megan leslie | f | halifax | community legal worker | 19252 | 42.7 | 1st | none row 6 : halifax west | tamara lorincz | f | halifax | director of nova scotia environment network | 12201 | 29.6 | 2nd | an environmentalist row 7 : kings-hants | carol e. harris | f | wolfville | university professor | 8291 | 22.0 | 3rd | she was the ndp's candidate in the 2000 election in esquimalt-juan de fuca row 8 : sackville-eastern shore | peter stoffer | m | windsor junction | parliamentarian | 24279 | 61.4 | 1st | stoffer has been the incumbent mp since 1997 row 9 : south shore-st. margaret's | gordon s. earle | m | upper tantallon | retired public servant | 13456 | 33.7 | 2nd | earle is the former federal mp for halifax west (1997-2000). has run in this riding unsuccessfully in 2004 and 2006 row 10 : sydney-victoria | wayne mckay | m | sydney | teacher | 8559 | 24.4 | 2nd | none row 11 : west nova | george barron | m | bear river | paramedic | 7097 | 16.9 | 3rd | barron was born near paris, ontario, he has been a paramedic for 22 years. he was nominated on october 28, 2007 | col : residence row 1 : antigonish | select residence where % = '19.6' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& riding & candidate & gender & residence & occupation & votes & % & rank & biographical notes \\
\midrule
0 & cape breton-canso & mark macneill & m & inverness & government and business policy advisor & 7660 & 21.1 & 3rd & served in ottawa as a consultant with national advisory board on science and technology, with the treasury board secretariat and the solicitor general's aboriginal policing secretariat \\
1 & central nova & mary louise lorefice & f & antigonish & retired educator & 7659 & 19.6 & 3rd & lorefice is a retired teacher from antigonish, who has lived in the community for 38 years \\
2 & cumberland-colchester-musquodoboit valley & karen olsson & f & north river & stay-at-home mother & 4874 & 12.3 & 2nd & none \\
3 & dartmouth-cole harbour & brad pye & m & ottawa, on & senior political party program officer & 12793 & 31.5 & 2nd & pye is an international development worker and son of former dartmouth north mla jerry pye \\
4 & halifax & megan leslie & f & halifax & community legal worker & 19252 & 42.7 & 1st & none \\
5 & halifax west & tamara lorincz & f & halifax & director of nova scotia environment network & 12201 & 29.6 & 2nd & an environmentalist \\
6 & kings-hants & carol e. harris & f & wolfville & university professor & 8291 & 22.0 & 3rd & she was the ndp's candidate in the 2000 election in esquimalt-juan de fuca \\
7 & sackville-eastern shore & peter stoffer & m & windsor junction & parliamentarian & 24279 & 61.4 & 1st & stoffer has been the incumbent mp since 1997 \\
8 & south shore-st. margaret's & gordon s. earle & m & upper tantallon & retired public servant & 13456 & 33.7 & 2nd & earle is the former federal mp for halifax west (1997-2000). has run in this riding unsuccessfully in 2004 and 2006 \\
9 & sydney-victoria & wayne mckay & m & sydney & teacher & 8559 & 24.4 & 2nd & none \\
10 & west nova & george barron & m & bear river & paramedic & 7097 & 16.9 & 3rd & barron was born near paris, ontario, he has been a paramedic for 22 years. he was nominated on october 28, 2007 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& residence \\
\midrule
0 & antigonish \\
\bottomrule
\end{tabular}
| select residence where % = '19.6' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>riding</th>
<th>candidate</th>
<th>gender</th>
<th>residence</th>
<th>occupation</th>
<th>votes</th>
<th>%</th>
<th>rank</th>
<th>biographical notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>cape breton-canso</td>
<td>mark macneill</td>
<td>m</td>
<td>inverness</td>
<td>government and business policy advisor</td>
<td>7660</td>
<td>21.1</td>
<td>3rd</td>
<td>served in ottawa as a consultant with national advisory board on science and technology, with the treasury board secretariat and the solicitor general's aboriginal policing secretariat</td>
</tr>
<tr>
<th>1</th>
<td>central nova</td>
<td>mary louise lorefice</td>
<td>f</td>
<td>antigonish</td>
<td>retired educator</td>
<td>7659</td>
<td>19.6</td>
<td>3rd</td>
<td>lorefice is a retired teacher from antigonish, who has lived in the community for 38 years</td>
</tr>
<tr>
<th>2</th>
<td>cumberland-colchester-musquodoboit valley</td>
<td>karen olsson</td>
<td>f</td>
<td>north river</td>
<td>stay-at-home mother</td>
<td>4874</td>
<td>12.3</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>dartmouth-cole harbour</td>
<td>brad pye</td>
<td>m</td>
<td>ottawa, on</td>
<td>senior political party program officer</td>
<td>12793</td>
<td>31.5</td>
<td>2nd</td>
<td>pye is an international development worker and son of former dartmouth north mla jerry pye</td>
</tr>
<tr>
<th>4</th>
<td>halifax</td>
<td>megan leslie</td>
<td>f</td>
<td>halifax</td>
<td>community legal worker</td>
<td>19252</td>
<td>42.7</td>
<td>1st</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>halifax west</td>
<td>tamara lorincz</td>
<td>f</td>
<td>halifax</td>
<td>director of nova scotia environment network</td>
<td>12201</td>
<td>29.6</td>
<td>2nd</td>
<td>an environmentalist</td>
</tr>
<tr>
<th>6</th>
<td>kings-hants</td>
<td>carol e. harris</td>
<td>f</td>
<td>wolfville</td>
<td>university professor</td>
<td>8291</td>
<td>22.0</td>
<td>3rd</td>
<td>she was the ndp's candidate in the 2000 election in esquimalt-juan de fuca</td>
</tr>
<tr>
<th>7</th>
<td>sackville-eastern shore</td>
<td>peter stoffer</td>
<td>m</td>
<td>windsor junction</td>
<td>parliamentarian</td>
<td>24279</td>
<td>61.4</td>
<td>1st</td>
<td>stoffer has been the incumbent mp since 1997</td>
</tr>
<tr>
<th>8</th>
<td>south shore-st. margaret's</td>
<td>gordon s. earle</td>
<td>m</td>
<td>upper tantallon</td>
<td>retired public servant</td>
<td>13456</td>
<td>33.7</td>
<td>2nd</td>
<td>earle is the former federal mp for halifax west (1997-2000). has run in this riding unsuccessfully in 2004 and 2006</td>
</tr>
<tr>
<th>9</th>
<td>sydney-victoria</td>
<td>wayne mckay</td>
<td>m</td>
<td>sydney</td>
<td>teacher</td>
<td>8559</td>
<td>24.4</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>west nova</td>
<td>george barron</td>
<td>m</td>
<td>bear river</td>
<td>paramedic</td>
<td>7097</td>
<td>16.9</td>
<td>3rd</td>
<td>barron was born near paris, ontario, he has been a paramedic for 22 years. he was nominated on october 28, 2007</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>residence</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>antigonish</td>
</tr>
</tbody>
</table> | select residence where % = '19.6' <table_name> : table | | riding | candidate | gender | residence | occupation | votes | % | rank | biographical notes |
|---:|:------------------------------------------|:---------------------|:---------|:-----------------|:--------------------------------------------|--------:|-----:|:-------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | cape breton-canso | mark macneill | m | inverness | government and business policy advisor | 7660 | 21.1 | 3rd | served in ottawa as a consultant with national advisory board on science and technology, with the treasury board secretariat and the solicitor general's aboriginal policing secretariat |
| 1 | central nova | mary louise lorefice | f | antigonish | retired educator | 7659 | 19.6 | 3rd | lorefice is a retired teacher from antigonish, who has lived in the community for 38 years |
| 2 | cumberland-colchester-musquodoboit valley | karen olsson | f | north river | stay-at-home mother | 4874 | 12.3 | 2nd | none |
| 3 | dartmouth-cole harbour | brad pye | m | ottawa, on | senior political party program officer | 12793 | 31.5 | 2nd | pye is an international development worker and son of former dartmouth north mla jerry pye |
| 4 | halifax | megan leslie | f | halifax | community legal worker | 19252 | 42.7 | 1st | none |
| 5 | halifax west | tamara lorincz | f | halifax | director of nova scotia environment network | 12201 | 29.6 | 2nd | an environmentalist |
| 6 | kings-hants | carol e. harris | f | wolfville | university professor | 8291 | 22 | 3rd | she was the ndp's candidate in the 2000 election in esquimalt-juan de fuca |
| 7 | sackville-eastern shore | peter stoffer | m | windsor junction | parliamentarian | 24279 | 61.4 | 1st | stoffer has been the incumbent mp since 1997 |
| 8 | south shore-st. margaret's | gordon s. earle | m | upper tantallon | retired public servant | 13456 | 33.7 | 2nd | earle is the former federal mp for halifax west (1997-2000). has run in this riding unsuccessfully in 2004 and 2006 |
| 9 | sydney-victoria | wayne mckay | m | sydney | teacher | 8559 | 24.4 | 2nd | none |
| 10 | west nova | george barron | m | bear river | paramedic | 7097 | 16.9 | 3rd | barron was born near paris, ontario, he has been a paramedic for 22 years. he was nominated on october 28, 2007 | | | | residence |
|---:|:------------|
| 0 | antigonish | | [
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select led where retired = 'running' col : year | car | start | qual | rank | finish | laps | led | retired row 1 : 1926 | 31 | 12 | 102.789 | 13 | 11 | 142 | 0 | flagged row 2 : 1927 | 27 | 27 | 107.765 | 22 | 3 | 200 | 0 | running row 3 : 1928 | 8 | 4 | 117.031 | 4 | 10 | 200 | 33 | running row 4 : 1929 | 23 | 11 | 112.146 | 15 | 17 | 91 | 0 | supercharger row 5 : 1930 | 9 | 20 | 100.033 | 18 | 20 | 79 | 0 | valve row 6 : 1931 | 37 | 19 | 111.725 | 6 | 18 | 167 | 0 | crash t4 row 7 : 1932 | 25 | 20 | 108.896 | 34 | 13 | 184 | 0 | flagged row 8 : 1933 | 34 | 12 | 113.578 | 15 | 7 | 200 | 0 | running row 9 : 1934 | 8 | 7 | 113.733 | 13 | 17 | 94 | 0 | rod row 10 : 1935 | 44 | 6 | 115.459 | 11 | 21 | 102 | 0 | magneto row 11 : 1937 | 38 | 7 | 118.788 | 16 | 8 | 200 | 0 | running row 12 : 1938 | 17 | 4 | 122.499 | 6 | 17 | 130 | 0 | rod row 13 : 1939 | 62 | 27 | 121.749 | 24 | 11 | 200 | 0 | running row 14 : totals | totals | totals | totals | totals | totals | 1989 | 33 | none | col : led row 1 : 0 row 2 : 33 row 3 : 0 row 4 : 0 row 5 : 0 | select led where retired = 'running' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& year & car & start & qual & rank & finish & laps & led & retired \\
\midrule
0 & 1926 & 31 & 12 & 102.789 & 13 & 11 & 142 & 0 & flagged \\
1 & 1927 & 27 & 27 & 107.765 & 22 & 3 & 200 & 0 & running \\
2 & 1928 & 8 & 4 & 117.031 & 4 & 10 & 200 & 33 & running \\
3 & 1929 & 23 & 11 & 112.146 & 15 & 17 & 91 & 0 & supercharger \\
4 & 1930 & 9 & 20 & 100.033 & 18 & 20 & 79 & 0 & valve \\
5 & 1931 & 37 & 19 & 111.725 & 6 & 18 & 167 & 0 & crash t4 \\
6 & 1932 & 25 & 20 & 108.896 & 34 & 13 & 184 & 0 & flagged \\
7 & 1933 & 34 & 12 & 113.578 & 15 & 7 & 200 & 0 & running \\
8 & 1934 & 8 & 7 & 113.733 & 13 & 17 & 94 & 0 & rod \\
9 & 1935 & 44 & 6 & 115.459 & 11 & 21 & 102 & 0 & magneto \\
10 & 1937 & 38 & 7 & 118.788 & 16 & 8 & 200 & 0 & running \\
11 & 1938 & 17 & 4 & 122.499 & 6 & 17 & 130 & 0 & rod \\
12 & 1939 & 62 & 27 & 121.749 & 24 & 11 & 200 & 0 & running \\
13 & totals & totals & totals & totals & totals & totals & 1989 & 33 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& led \\
\midrule
0 & 0 \\
1 & 33 \\
2 & 0 \\
3 & 0 \\
4 & 0 \\
\bottomrule
\end{tabular}
| select led 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>1926</td>
<td>31</td>
<td>12</td>
<td>102.789</td>
<td>13</td>
<td>11</td>
<td>142</td>
<td>0</td>
<td>flagged</td>
</tr>
<tr>
<th>1</th>
<td>1927</td>
<td>27</td>
<td>27</td>
<td>107.765</td>
<td>22</td>
<td>3</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>2</th>
<td>1928</td>
<td>8</td>
<td>4</td>
<td>117.031</td>
<td>4</td>
<td>10</td>
<td>200</td>
<td>33</td>
<td>running</td>
</tr>
<tr>
<th>3</th>
<td>1929</td>
<td>23</td>
<td>11</td>
<td>112.146</td>
<td>15</td>
<td>17</td>
<td>91</td>
<td>0</td>
<td>supercharger</td>
</tr>
<tr>
<th>4</th>
<td>1930</td>
<td>9</td>
<td>20</td>
<td>100.033</td>
<td>18</td>
<td>20</td>
<td>79</td>
<td>0</td>
<td>valve</td>
</tr>
<tr>
<th>5</th>
<td>1931</td>
<td>37</td>
<td>19</td>
<td>111.725</td>
<td>6</td>
<td>18</td>
<td>167</td>
<td>0</td>
<td>crash t4</td>
</tr>
<tr>
<th>6</th>
<td>1932</td>
<td>25</td>
<td>20</td>
<td>108.896</td>
<td>34</td>
<td>13</td>
<td>184</td>
<td>0</td>
<td>flagged</td>
</tr>
<tr>
<th>7</th>
<td>1933</td>
<td>34</td>
<td>12</td>
<td>113.578</td>
<td>15</td>
<td>7</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>8</th>
<td>1934</td>
<td>8</td>
<td>7</td>
<td>113.733</td>
<td>13</td>
<td>17</td>
<td>94</td>
<td>0</td>
<td>rod</td>
</tr>
<tr>
<th>9</th>
<td>1935</td>
<td>44</td>
<td>6</td>
<td>115.459</td>
<td>11</td>
<td>21</td>
<td>102</td>
<td>0</td>
<td>magneto</td>
</tr>
<tr>
<th>10</th>
<td>1937</td>
<td>38</td>
<td>7</td>
<td>118.788</td>
<td>16</td>
<td>8</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>11</th>
<td>1938</td>
<td>17</td>
<td>4</td>
<td>122.499</td>
<td>6</td>
<td>17</td>
<td>130</td>
<td>0</td>
<td>rod</td>
</tr>
<tr>
<th>12</th>
<td>1939</td>
<td>62</td>
<td>27</td>
<td>121.749</td>
<td>24</td>
<td>11</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>13</th>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>1989</td>
<td>33</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>led</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
<tr>
<th>1</th>
<td>33</td>
</tr>
<tr>
<th>2</th>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>0</td>
</tr>
</tbody>
</table> | select led where retired = 'running' <table_name> : table | | year | car | start | qual | rank | finish | laps | led | retired |
|---:|:-------|:-------|:--------|:--------|:-------|:---------|-------:|------:|:-------------|
| 0 | 1926 | 31 | 12 | 102.789 | 13 | 11 | 142 | 0 | flagged |
| 1 | 1927 | 27 | 27 | 107.765 | 22 | 3 | 200 | 0 | running |
| 2 | 1928 | 8 | 4 | 117.031 | 4 | 10 | 200 | 33 | running |
| 3 | 1929 | 23 | 11 | 112.146 | 15 | 17 | 91 | 0 | supercharger |
| 4 | 1930 | 9 | 20 | 100.033 | 18 | 20 | 79 | 0 | valve |
| 5 | 1931 | 37 | 19 | 111.725 | 6 | 18 | 167 | 0 | crash t4 |
| 6 | 1932 | 25 | 20 | 108.896 | 34 | 13 | 184 | 0 | flagged |
| 7 | 1933 | 34 | 12 | 113.578 | 15 | 7 | 200 | 0 | running |
| 8 | 1934 | 8 | 7 | 113.733 | 13 | 17 | 94 | 0 | rod |
| 9 | 1935 | 44 | 6 | 115.459 | 11 | 21 | 102 | 0 | magneto |
| 10 | 1937 | 38 | 7 | 118.788 | 16 | 8 | 200 | 0 | running |
| 11 | 1938 | 17 | 4 | 122.499 | 6 | 17 | 130 | 0 | rod |
| 12 | 1939 | 62 | 27 | 121.749 | 24 | 11 | 200 | 0 | running |
| 13 | totals | totals | totals | totals | totals | totals | 1989 | 33 | none | | | | led |
|---:|------:|
| 0 | 0 |
| 1 | 33 |
| 2 | 0 |
| 3 | 0 |
| 4 | 0 | | [
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select count ( * ) where title = 888 col : year | title | role | notes row 1 : 1986 | street legal | angela | none row 2 : 1986 | desiree's wish | waitress | none row 3 : 1988 | t. and t | sydney | none row 4 : 1989 | mosquito lake | tara harrison | none row 5 : 1991 | married to it | student in pageant | none row 6 : 1992 | a town torn apart | none | none row 7 : 1992 | the judge | millie waters | none row 8 : 1992 | forever knight | none | none row 9 : 1993 | family pictures | none | none row 10 : 1993 | kung fu: the legend continues | elizabeth | none row 11 : 1993 | ready or not | none | none row 12 : 1994 | reform school girl | lucille | none row 13 : 1994 | thicker than blood: the larry mclinden story | terra (age 16) | none row 14 : 1995 | skin deep | tina | none row 15 : 1995 | party of five | lorna | none row 16 : 1996 | 3rd rock from the sun | yoga lady | episode: "my mother the alien" row 17 : 1998 | sabrina goes to rome | gwen | none row 18 : 1999 | sabrina, down under | gwen | none row 19 : 1999 | touched by an angel | none | none row 20 : 1999 | black mask | additional voices | none row 21 : 1999 | candid camera | none | none row 22 : 1999 | 1997 kids' choice awards | herself | winner (with the cast of rugrats) for favorite cartoon row 23 : 1999 | 1998 kids' choice awards | herself | winner (with the cast of rugrats) for favorite cartoon row 24 : 1999 | 1999 kids' choice awards | herself | presenter, winner (with the cast of rugrats) for favorite cartoon, winner (with the cast of the rugrats movie) for favorite movie row 25 : 2004 | comic book: the movie | none | none row 26 : 2006 | take home chef | herself | none row 27 : 2007 | the bad girls club | season 2 narrator | none row 28 : 2008 | according to jim | kayla | none row 29 : 2010 | big time rush | miss collins | recurring role row 30 : 2013 | super fun night | young pamela | none row 31 : 2014 | ar | | row 32 : "suicide squad" | | | | col : count ( "*" ) row 1 : 0 | select count ( * ) where title = 888 <table_name> : table \begin{tabular}{lllll}
\toprule
& year & title & role & notes \\
\midrule
0 & 1986 & street legal & angela & none \\
1 & 1986 & desiree's wish & waitress & none \\
2 & 1988 & t. and t & sydney & none \\
3 & 1989 & mosquito lake & tara harrison & none \\
4 & 1991 & married to it & student in pageant & none \\
5 & 1992 & a town torn apart & none & none \\
6 & 1992 & the judge & millie waters & none \\
7 & 1992 & forever knight & none & none \\
8 & 1993 & family pictures & none & none \\
9 & 1993 & kung fu: the legend continues & elizabeth & none \\
10 & 1993 & ready or not & none & none \\
11 & 1994 & reform school girl & lucille & none \\
12 & 1994 & thicker than blood: the larry mclinden story & terra (age 16) & none \\
13 & 1995 & skin deep & tina & none \\
14 & 1995 & party of five & lorna & none \\
15 & 1996 & 3rd rock from the sun & yoga lady & episode: "my mother the alien" \\
16 & 1998 & sabrina goes to rome & gwen & none \\
17 & 1999 & sabrina, down under & gwen & none \\
18 & 1999 & touched by an angel & none & none \\
19 & 1999 & black mask & additional voices & none \\
20 & 1999 & candid camera & none & none \\
21 & 1999 & 1997 kids' choice awards & herself & winner (with the cast of rugrats) for favorite cartoon \\
22 & 1999 & 1998 kids' choice awards & herself & winner (with the cast of rugrats) for favorite cartoon \\
23 & 1999 & 1999 kids' choice awards & herself & presenter, winner (with the cast of rugrats) for favorite cartoon, winner (with the cast of the rugrats movie) for favorite movie \\
24 & 2004 & comic book: the movie & none & none \\
25 & 2006 & take home chef & herself & none \\
26 & 2007 & the bad girls club & season 2 narrator & none \\
27 & 2008 & according to jim & kayla & none \\
28 & 2010 & big time rush & miss collins & recurring role \\
29 & 2013 & super fun night & young pamela & none \\
30 & 2014 & ar & & \\
31 & "suicide squad" & & | & NaN \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where title = 888 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>role</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1986</td>
<td>street legal</td>
<td>angela</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1986</td>
<td>desiree's wish</td>
<td>waitress</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1988</td>
<td>t. and t</td>
<td>sydney</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1989</td>
<td>mosquito lake</td>
<td>tara harrison</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1991</td>
<td>married to it</td>
<td>student in pageant</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1992</td>
<td>a town torn apart</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1992</td>
<td>the judge</td>
<td>millie waters</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1992</td>
<td>forever knight</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1993</td>
<td>family pictures</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1993</td>
<td>kung fu: the legend continues</td>
<td>elizabeth</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>1993</td>
<td>ready or not</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>1994</td>
<td>reform school girl</td>
<td>lucille</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>1994</td>
<td>thicker than blood: the larry mclinden story</td>
<td>terra (age 16)</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>1995</td>
<td>skin deep</td>
<td>tina</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>1995</td>
<td>party of five</td>
<td>lorna</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>1996</td>
<td>3rd rock from the sun</td>
<td>yoga lady</td>
<td>episode: "my mother the alien"</td>
</tr>
<tr>
<th>16</th>
<td>1998</td>
<td>sabrina goes to rome</td>
<td>gwen</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>1999</td>
<td>sabrina, down under</td>
<td>gwen</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>1999</td>
<td>touched by an angel</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>1999</td>
<td>black mask</td>
<td>additional voices</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>1999</td>
<td>candid camera</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>1999</td>
<td>1997 kids' choice awards</td>
<td>herself</td>
<td>winner (with the cast of rugrats) for favorite cartoon</td>
</tr>
<tr>
<th>22</th>
<td>1999</td>
<td>1998 kids' choice awards</td>
<td>herself</td>
<td>winner (with the cast of rugrats) for favorite cartoon</td>
</tr>
<tr>
<th>23</th>
<td>1999</td>
<td>1999 kids' choice awards</td>
<td>herself</td>
<td>presenter, winner (with the cast of rugrats) for favorite cartoon, winner (with the cast of the rugrats movie) for favorite movie</td>
</tr>
<tr>
<th>24</th>
<td>2004</td>
<td>comic book: the movie</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>2006</td>
<td>take home chef</td>
<td>herself</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>2007</td>
<td>the bad girls club</td>
<td>season 2 narrator</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>2008</td>
<td>according to jim</td>
<td>kayla</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>2010</td>
<td>big time rush</td>
<td>miss collins</td>
<td>recurring role</td>
</tr>
<tr>
<th>29</th>
<td>2013</td>
<td>super fun night</td>
<td>young pamela</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>2014</td>
<td>ar</td>
<td></td>
<td></td>
</tr>
<tr>
<th>31</th>
<td>"suicide squad"</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 title = 888 <table_name> : table | | year | title | role | notes |
|---:|:----------------|:---------------------------------------------|:-------------------|:----------------------------------------------------------------------------------------------------------------------------------|
| 0 | 1986 | street legal | angela | none |
| 1 | 1986 | desiree's wish | waitress | none |
| 2 | 1988 | t. and t | sydney | none |
| 3 | 1989 | mosquito lake | tara harrison | none |
| 4 | 1991 | married to it | student in pageant | none |
| 5 | 1992 | a town torn apart | none | none |
| 6 | 1992 | the judge | millie waters | none |
| 7 | 1992 | forever knight | none | none |
| 8 | 1993 | family pictures | none | none |
| 9 | 1993 | kung fu: the legend continues | elizabeth | none |
| 10 | 1993 | ready or not | none | none |
| 11 | 1994 | reform school girl | lucille | none |
| 12 | 1994 | thicker than blood: the larry mclinden story | terra (age 16) | none |
| 13 | 1995 | skin deep | tina | none |
| 14 | 1995 | party of five | lorna | none |
| 15 | 1996 | 3rd rock from the sun | yoga lady | episode: "my mother the alien" |
| 16 | 1998 | sabrina goes to rome | gwen | none |
| 17 | 1999 | sabrina, down under | gwen | none |
| 18 | 1999 | touched by an angel | none | none |
| 19 | 1999 | black mask | additional voices | none |
| 20 | 1999 | candid camera | none | none |
| 21 | 1999 | 1997 kids' choice awards | herself | winner (with the cast of rugrats) for favorite cartoon |
| 22 | 1999 | 1998 kids' choice awards | herself | winner (with the cast of rugrats) for favorite cartoon |
| 23 | 1999 | 1999 kids' choice awards | herself | presenter, winner (with the cast of rugrats) for favorite cartoon, winner (with the cast of the rugrats movie) for favorite movie |
| 24 | 2004 | comic book: the movie | none | none |
| 25 | 2006 | take home chef | herself | none |
| 26 | 2007 | the bad girls club | season 2 narrator | none |
| 27 | 2008 | according to jim | kayla | none |
| 28 | 2010 | big time rush | miss collins | recurring role |
| 29 | 2013 | super fun night | young pamela | none |
| 30 | 2014 | ar | | |
| 31 | "suicide squad" | | | | | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select constructor where driver = 'juan pablo montoya' col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 9 | kimi raikkonen | mclaren-mercedes | 44 | 1:30:01.295 | 2 | 10 row 2 : 2 | 5 | fernando alonso | renault | 44 | 28.394 | 4 | 8 row 3 : 3 | 3 | jenson button | bar-honda | 44 | 32.077 | 8 | 6 row 4 : 4 | 7 | mark webber | williams-bmw | 44 | +1:09.167 | 9 | 5 row 5 : 5 | 2 | rubens barrichello | ferrari | 44 | +1:18.136 | 12 | 4 row 6 : 6 | 11 | jacques villeneuve | sauber-petronas | 44 | +1:27.435 | 14 | 3 row 7 : 7 | 17 | ralf schumacher | toyota | 44 | +1:27.574 | 5 | 2 row 8 : 8 | 18 | tiago monteiro | jordan-toyota | 43 | +1 lap | 19 | 1 row 9 : 9 | 15 | christian klien | red bull-cosworth | 43 | +1 lap | 16 | none row 10 : 10 | 12 | felipe massa | sauber-petronas | 43 | +1 lap | 7 | none row 11 : 11 | 19 | narain karthikeyan | jordan-toyota | 43 | +1 lap | 20 | none row 12 : 12 | 21 | christijan albers | minardi-cosworth | 42 | +2 laps | 18 | none row 13 : 13 | 20 | robert doornbos | minardi-cosworth | 41 | +3 laps | 17 | none row 14 : 14 | 10 | juan pablo montoya | mclaren-mercedes | 40 | collision | 1 | none row 15 : 15 | 8 | antonio pizzonia | williams-bmw | 39 | collision | 15 | none row 16 : ret | 16 | jarno trulli | toyota | 34 | accident | 3 | none row 17 : ret | 14 | david coulthard | red bull-cosworth | 18 | engine | 11 | none row 18 : ret | 1 | michael schumacher | ferrari | 13 | collision | 6 | none row 19 : ret | 4 | takuma sato | bar-honda | 13 | collision | 10 | none row 20 : ret | 6 | giancarlo fisichella | renault | 10 | accident | 13 | none | col : constructor row 1 : mclaren-mercedes | select constructor where driver = 'juan pablo montoya' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & constructor & laps & time/retired & grid & points \\
\midrule
0 & 1 & 9 & kimi raikkonen & mclaren-mercedes & 44 & 1:30:01.295 & 2 & 10 \\
1 & 2 & 5 & fernando alonso & renault & 44 & 28.394 & 4 & 8 \\
2 & 3 & 3 & jenson button & bar-honda & 44 & 32.077 & 8 & 6 \\
3 & 4 & 7 & mark webber & williams-bmw & 44 & +1:09.167 & 9 & 5 \\
4 & 5 & 2 & rubens barrichello & ferrari & 44 & +1:18.136 & 12 & 4 \\
5 & 6 & 11 & jacques villeneuve & sauber-petronas & 44 & +1:27.435 & 14 & 3 \\
6 & 7 & 17 & ralf schumacher & toyota & 44 & +1:27.574 & 5 & 2 \\
7 & 8 & 18 & tiago monteiro & jordan-toyota & 43 & +1 lap & 19 & 1 \\
8 & 9 & 15 & christian klien & red bull-cosworth & 43 & +1 lap & 16 & none \\
9 & 10 & 12 & felipe massa & sauber-petronas & 43 & +1 lap & 7 & none \\
10 & 11 & 19 & narain karthikeyan & jordan-toyota & 43 & +1 lap & 20 & none \\
11 & 12 & 21 & christijan albers & minardi-cosworth & 42 & +2 laps & 18 & none \\
12 & 13 & 20 & robert doornbos & minardi-cosworth & 41 & +3 laps & 17 & none \\
13 & 14 & 10 & juan pablo montoya & mclaren-mercedes & 40 & collision & 1 & none \\
14 & 15 & 8 & antonio pizzonia & williams-bmw & 39 & collision & 15 & none \\
15 & ret & 16 & jarno trulli & toyota & 34 & accident & 3 & none \\
16 & ret & 14 & david coulthard & red bull-cosworth & 18 & engine & 11 & none \\
17 & ret & 1 & michael schumacher & ferrari & 13 & collision & 6 & none \\
18 & ret & 4 & takuma sato & bar-honda & 13 & collision & 10 & none \\
19 & ret & 6 & giancarlo fisichella & renault & 10 & accident & 13 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& constructor \\
\midrule
0 & mclaren-mercedes \\
\bottomrule
\end{tabular}
| select constructor where driver = 'juan pablo montoya' <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>9</td>
<td>kimi raikkonen</td>
<td>mclaren-mercedes</td>
<td>44</td>
<td>1:30:01.295</td>
<td>2</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>5</td>
<td>fernando alonso</td>
<td>renault</td>
<td>44</td>
<td>28.394</td>
<td>4</td>
<td>8</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>3</td>
<td>jenson button</td>
<td>bar-honda</td>
<td>44</td>
<td>32.077</td>
<td>8</td>
<td>6</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>7</td>
<td>mark webber</td>
<td>williams-bmw</td>
<td>44</td>
<td>+1:09.167</td>
<td>9</td>
<td>5</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2</td>
<td>rubens barrichello</td>
<td>ferrari</td>
<td>44</td>
<td>+1:18.136</td>
<td>12</td>
<td>4</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>11</td>
<td>jacques villeneuve</td>
<td>sauber-petronas</td>
<td>44</td>
<td>+1:27.435</td>
<td>14</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>17</td>
<td>ralf schumacher</td>
<td>toyota</td>
<td>44</td>
<td>+1:27.574</td>
<td>5</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>18</td>
<td>tiago monteiro</td>
<td>jordan-toyota</td>
<td>43</td>
<td>+1 lap</td>
<td>19</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>15</td>
<td>christian klien</td>
<td>red bull-cosworth</td>
<td>43</td>
<td>+1 lap</td>
<td>16</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>12</td>
<td>felipe massa</td>
<td>sauber-petronas</td>
<td>43</td>
<td>+1 lap</td>
<td>7</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>19</td>
<td>narain karthikeyan</td>
<td>jordan-toyota</td>
<td>43</td>
<td>+1 lap</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>21</td>
<td>christijan albers</td>
<td>minardi-cosworth</td>
<td>42</td>
<td>+2 laps</td>
<td>18</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>20</td>
<td>robert doornbos</td>
<td>minardi-cosworth</td>
<td>41</td>
<td>+3 laps</td>
<td>17</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>10</td>
<td>juan pablo montoya</td>
<td>mclaren-mercedes</td>
<td>40</td>
<td>collision</td>
<td>1</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>8</td>
<td>antonio pizzonia</td>
<td>williams-bmw</td>
<td>39</td>
<td>collision</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>ret</td>
<td>16</td>
<td>jarno trulli</td>
<td>toyota</td>
<td>34</td>
<td>accident</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>ret</td>
<td>14</td>
<td>david coulthard</td>
<td>red bull-cosworth</td>
<td>18</td>
<td>engine</td>
<td>11</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>ret</td>
<td>1</td>
<td>michael schumacher</td>
<td>ferrari</td>
<td>13</td>
<td>collision</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>4</td>
<td>takuma sato</td>
<td>bar-honda</td>
<td>13</td>
<td>collision</td>
<td>10</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>6</td>
<td>giancarlo fisichella</td>
<td>renault</td>
<td>10</td>
<td>accident</td>
<td>13</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>constructor</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>mclaren-mercedes</td>
</tr>
</tbody>
</table> | select constructor where driver = 'juan pablo montoya' <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points |
|---:|:------|-----:|:---------------------|:------------------|-------:|:---------------|-------:|:---------|
| 0 | 1 | 9 | kimi raikkonen | mclaren-mercedes | 44 | 1:30:01.295 | 2 | 10 |
| 1 | 2 | 5 | fernando alonso | renault | 44 | 28.394 | 4 | 8 |
| 2 | 3 | 3 | jenson button | bar-honda | 44 | 32.077 | 8 | 6 |
| 3 | 4 | 7 | mark webber | williams-bmw | 44 | +1:09.167 | 9 | 5 |
| 4 | 5 | 2 | rubens barrichello | ferrari | 44 | +1:18.136 | 12 | 4 |
| 5 | 6 | 11 | jacques villeneuve | sauber-petronas | 44 | +1:27.435 | 14 | 3 |
| 6 | 7 | 17 | ralf schumacher | toyota | 44 | +1:27.574 | 5 | 2 |
| 7 | 8 | 18 | tiago monteiro | jordan-toyota | 43 | +1 lap | 19 | 1 |
| 8 | 9 | 15 | christian klien | red bull-cosworth | 43 | +1 lap | 16 | none |
| 9 | 10 | 12 | felipe massa | sauber-petronas | 43 | +1 lap | 7 | none |
| 10 | 11 | 19 | narain karthikeyan | jordan-toyota | 43 | +1 lap | 20 | none |
| 11 | 12 | 21 | christijan albers | minardi-cosworth | 42 | +2 laps | 18 | none |
| 12 | 13 | 20 | robert doornbos | minardi-cosworth | 41 | +3 laps | 17 | none |
| 13 | 14 | 10 | juan pablo montoya | mclaren-mercedes | 40 | collision | 1 | none |
| 14 | 15 | 8 | antonio pizzonia | williams-bmw | 39 | collision | 15 | none |
| 15 | ret | 16 | jarno trulli | toyota | 34 | accident | 3 | none |
| 16 | ret | 14 | david coulthard | red bull-cosworth | 18 | engine | 11 | none |
| 17 | ret | 1 | michael schumacher | ferrari | 13 | collision | 6 | none |
| 18 | ret | 4 | takuma sato | bar-honda | 13 | collision | 10 | none |
| 19 | ret | 6 | giancarlo fisichella | renault | 10 | accident | 13 | none | | | | constructor |
|---:|:-----------------|
| 0 | mclaren-mercedes | | [
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select nov where month = 'average low °c (°f)' col : month | jan | feb | mar | apr | may | jun | jul | aug | sep | oct | nov | dec | year row 1 : record high °c (°f) | 24.0 (75.2) | 24.0 (75.2) | 27.2 (81) | 32.6 (90.7) | 39.1 (102.4) | 41.4 (106.5) | 43.3 (109.9) | 44.8 (112.6) | 39.0 (102.2) | 35.2 (95.4) | 26.8 (80.2) | 23.0 (73.4) | 44.8 (112.6) row 2 : average high °c (°f) | 12.6 (54.7) | 12.9 (55.2) | 15.0 (59) | 18.0 (64.4) | 22.8 (73) | 26.8 (80.2) | 29.2 (84.6) | 29.2 (84.6) | 25.9 (78.6) | 21.5 (70.7) | 16.8 (62.2) | 13.9 (57) | 20.38 (68.68) row 3 : daily mean °c (°f) | 8.8 (47.8) | 8.9 (48) | 10.7 (51.3) | 13.3 (55.9) | 17.8 (64) | 21.8 (71.2) | 24.3 (75.7) | 24.3 (75.7) | 21.1 (70) | 17.1 (62.8) | 12.7 (54.9) | 10.1 (50.2) | 15.91 (60.62) row 4 : average low °c (°f) | 4.9 (40.8) | 4.8 (40.6) | 6.3 (43.3) | 8.6 (47.5) | 12.9 (55.2) | 16.7 (62.1) | 19.3 (66.7) | 19.4 (66.9) | 16.3 (61.3) | 12.6 (54.7) | 8.6 (47.5) | 6.2 (43.2) | 11.38 (52.48) row 5 : record low °c (°f) | -5.9 (21.4) | -3 (27) | -2.4 (27.7) | 1.1 (34) | 5.3 (41.5) | 7.8 (46) | 12.8 (55) | 12.8 (55) | 8.4 (47.1) | 1.0 (33.8) | 0.0 (32) | -1.6 (29.1) | -5.9 (21.4) row 6 : precipitation mm (inches) | 53.7 (2.114) | 64.2 (2.528) | 42.0 (1.654) | 40.5 (1.594) | 34.9 (1.374) | 23.3 (0.917) | 25.4 (1) | 30.4 (1.197) | 59.7 (2.35) | 61.5 (2.421) | 72.7 (2.862) | 54.3 (2.138) | 562.6 (22.149) row 7 : avg. precipitation days (≥ 1 mm) | 6.7 | 7.7 | 6.8 | 6.2 | 5.2 | 3.7 | 2.6 | 3.5 | 5.0 | 6.3 | 7.7 | 7.1 | 68.5 row 8 : % humidity | 77 | 74 | 72 | 68 | 68 | 65 | 64 | 65 | 68 | 72 | 76 | 78 | 70.6 | col : nov row 1 : 8.6 (47.5) | select nov where month = 'average low °c (°f)' <table_name> : table \begin{tabular}{lllllllllllllll}
\toprule
& month & jan & feb & mar & apr & may & jun & jul & aug & sep & oct & nov & dec & year \\
\midrule
0 & record high °c (°f) & 24.0 (75.2) & 24.0 (75.2) & 27.2 (81) & 32.6 (90.7) & 39.1 (102.4) & 41.4 (106.5) & 43.3 (109.9) & 44.8 (112.6) & 39.0 (102.2) & 35.2 (95.4) & 26.8 (80.2) & 23.0 (73.4) & 44.8 (112.6) \\
1 & average high °c (°f) & 12.6 (54.7) & 12.9 (55.2) & 15.0 (59) & 18.0 (64.4) & 22.8 (73) & 26.8 (80.2) & 29.2 (84.6) & 29.2 (84.6) & 25.9 (78.6) & 21.5 (70.7) & 16.8 (62.2) & 13.9 (57) & 20.38 (68.68) \\
2 & daily mean °c (°f) & 8.8 (47.8) & 8.9 (48) & 10.7 (51.3) & 13.3 (55.9) & 17.8 (64) & 21.8 (71.2) & 24.3 (75.7) & 24.3 (75.7) & 21.1 (70) & 17.1 (62.8) & 12.7 (54.9) & 10.1 (50.2) & 15.91 (60.62) \\
3 & average low °c (°f) & 4.9 (40.8) & 4.8 (40.6) & 6.3 (43.3) & 8.6 (47.5) & 12.9 (55.2) & 16.7 (62.1) & 19.3 (66.7) & 19.4 (66.9) & 16.3 (61.3) & 12.6 (54.7) & 8.6 (47.5) & 6.2 (43.2) & 11.38 (52.48) \\
4 & record low °c (°f) & -5.9 (21.4) & -3 (27) & -2.4 (27.7) & 1.1 (34) & 5.3 (41.5) & 7.8 (46) & 12.8 (55) & 12.8 (55) & 8.4 (47.1) & 1.0 (33.8) & 0.0 (32) & -1.6 (29.1) & -5.9 (21.4) \\
5 & precipitation mm (inches) & 53.7 (2.114) & 64.2 (2.528) & 42.0 (1.654) & 40.5 (1.594) & 34.9 (1.374) & 23.3 (0.917) & 25.4 (1) & 30.4 (1.197) & 59.7 (2.35) & 61.5 (2.421) & 72.7 (2.862) & 54.3 (2.138) & 562.6 (22.149) \\
6 & avg. precipitation days (≥ 1 mm) & 6.7 & 7.7 & 6.8 & 6.2 & 5.2 & 3.7 & 2.6 & 3.5 & 5.0 & 6.3 & 7.7 & 7.1 & 68.5 \\
7 & % humidity & 77 & 74 & 72 & 68 & 68 & 65 & 64 & 65 & 68 & 72 & 76 & 78 & 70.6 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nov \\
\midrule
0 & 8.6 (47.5) \\
\bottomrule
\end{tabular}
| select nov where month = 'average low °c (°f)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>month</th>
<th>jan</th>
<th>feb</th>
<th>mar</th>
<th>apr</th>
<th>may</th>
<th>jun</th>
<th>jul</th>
<th>aug</th>
<th>sep</th>
<th>oct</th>
<th>nov</th>
<th>dec</th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>record high °c (°f)</td>
<td>24.0 (75.2)</td>
<td>24.0 (75.2)</td>
<td>27.2 (81)</td>
<td>32.6 (90.7)</td>
<td>39.1 (102.4)</td>
<td>41.4 (106.5)</td>
<td>43.3 (109.9)</td>
<td>44.8 (112.6)</td>
<td>39.0 (102.2)</td>
<td>35.2 (95.4)</td>
<td>26.8 (80.2)</td>
<td>23.0 (73.4)</td>
<td>44.8 (112.6)</td>
</tr>
<tr>
<th>1</th>
<td>average high °c (°f)</td>
<td>12.6 (54.7)</td>
<td>12.9 (55.2)</td>
<td>15.0 (59)</td>
<td>18.0 (64.4)</td>
<td>22.8 (73)</td>
<td>26.8 (80.2)</td>
<td>29.2 (84.6)</td>
<td>29.2 (84.6)</td>
<td>25.9 (78.6)</td>
<td>21.5 (70.7)</td>
<td>16.8 (62.2)</td>
<td>13.9 (57)</td>
<td>20.38 (68.68)</td>
</tr>
<tr>
<th>2</th>
<td>daily mean °c (°f)</td>
<td>8.8 (47.8)</td>
<td>8.9 (48)</td>
<td>10.7 (51.3)</td>
<td>13.3 (55.9)</td>
<td>17.8 (64)</td>
<td>21.8 (71.2)</td>
<td>24.3 (75.7)</td>
<td>24.3 (75.7)</td>
<td>21.1 (70)</td>
<td>17.1 (62.8)</td>
<td>12.7 (54.9)</td>
<td>10.1 (50.2)</td>
<td>15.91 (60.62)</td>
</tr>
<tr>
<th>3</th>
<td>average low °c (°f)</td>
<td>4.9 (40.8)</td>
<td>4.8 (40.6)</td>
<td>6.3 (43.3)</td>
<td>8.6 (47.5)</td>
<td>12.9 (55.2)</td>
<td>16.7 (62.1)</td>
<td>19.3 (66.7)</td>
<td>19.4 (66.9)</td>
<td>16.3 (61.3)</td>
<td>12.6 (54.7)</td>
<td>8.6 (47.5)</td>
<td>6.2 (43.2)</td>
<td>11.38 (52.48)</td>
</tr>
<tr>
<th>4</th>
<td>record low °c (°f)</td>
<td>-5.9 (21.4)</td>
<td>-3 (27)</td>
<td>-2.4 (27.7)</td>
<td>1.1 (34)</td>
<td>5.3 (41.5)</td>
<td>7.8 (46)</td>
<td>12.8 (55)</td>
<td>12.8 (55)</td>
<td>8.4 (47.1)</td>
<td>1.0 (33.8)</td>
<td>0.0 (32)</td>
<td>-1.6 (29.1)</td>
<td>-5.9 (21.4)</td>
</tr>
<tr>
<th>5</th>
<td>precipitation mm (inches)</td>
<td>53.7 (2.114)</td>
<td>64.2 (2.528)</td>
<td>42.0 (1.654)</td>
<td>40.5 (1.594)</td>
<td>34.9 (1.374)</td>
<td>23.3 (0.917)</td>
<td>25.4 (1)</td>
<td>30.4 (1.197)</td>
<td>59.7 (2.35)</td>
<td>61.5 (2.421)</td>
<td>72.7 (2.862)</td>
<td>54.3 (2.138)</td>
<td>562.6 (22.149)</td>
</tr>
<tr>
<th>6</th>
<td>avg. precipitation days (≥ 1 mm)</td>
<td>6.7</td>
<td>7.7</td>
<td>6.8</td>
<td>6.2</td>
<td>5.2</td>
<td>3.7</td>
<td>2.6</td>
<td>3.5</td>
<td>5.0</td>
<td>6.3</td>
<td>7.7</td>
<td>7.1</td>
<td>68.5</td>
</tr>
<tr>
<th>7</th>
<td>% humidity</td>
<td>77</td>
<td>74</td>
<td>72</td>
<td>68</td>
<td>68</td>
<td>65</td>
<td>64</td>
<td>65</td>
<td>68</td>
<td>72</td>
<td>76</td>
<td>78</td>
<td>70.6</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nov</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>8.6 (47.5)</td>
</tr>
</tbody>
</table> | select nov where month = 'average low °c (°f)' <table_name> : table | | month | jan | feb | mar | apr | may | jun | jul | aug | sep | oct | nov | dec | year |
|---:|:---------------------------------|:-------------|:-------------|:-------------|:-------------|:-------------|:-------------|:-------------|:-------------|:-------------|:-------------|:-------------|:-------------|:---------------|
| 0 | record high °c (°f) | 24.0 (75.2) | 24.0 (75.2) | 27.2 (81) | 32.6 (90.7) | 39.1 (102.4) | 41.4 (106.5) | 43.3 (109.9) | 44.8 (112.6) | 39.0 (102.2) | 35.2 (95.4) | 26.8 (80.2) | 23.0 (73.4) | 44.8 (112.6) |
| 1 | average high °c (°f) | 12.6 (54.7) | 12.9 (55.2) | 15.0 (59) | 18.0 (64.4) | 22.8 (73) | 26.8 (80.2) | 29.2 (84.6) | 29.2 (84.6) | 25.9 (78.6) | 21.5 (70.7) | 16.8 (62.2) | 13.9 (57) | 20.38 (68.68) |
| 2 | daily mean °c (°f) | 8.8 (47.8) | 8.9 (48) | 10.7 (51.3) | 13.3 (55.9) | 17.8 (64) | 21.8 (71.2) | 24.3 (75.7) | 24.3 (75.7) | 21.1 (70) | 17.1 (62.8) | 12.7 (54.9) | 10.1 (50.2) | 15.91 (60.62) |
| 3 | average low °c (°f) | 4.9 (40.8) | 4.8 (40.6) | 6.3 (43.3) | 8.6 (47.5) | 12.9 (55.2) | 16.7 (62.1) | 19.3 (66.7) | 19.4 (66.9) | 16.3 (61.3) | 12.6 (54.7) | 8.6 (47.5) | 6.2 (43.2) | 11.38 (52.48) |
| 4 | record low °c (°f) | -5.9 (21.4) | -3 (27) | -2.4 (27.7) | 1.1 (34) | 5.3 (41.5) | 7.8 (46) | 12.8 (55) | 12.8 (55) | 8.4 (47.1) | 1.0 (33.8) | 0.0 (32) | -1.6 (29.1) | -5.9 (21.4) |
| 5 | precipitation mm (inches) | 53.7 (2.114) | 64.2 (2.528) | 42.0 (1.654) | 40.5 (1.594) | 34.9 (1.374) | 23.3 (0.917) | 25.4 (1) | 30.4 (1.197) | 59.7 (2.35) | 61.5 (2.421) | 72.7 (2.862) | 54.3 (2.138) | 562.6 (22.149) |
| 6 | avg. precipitation days (≥ 1 mm) | 6.7 | 7.7 | 6.8 | 6.2 | 5.2 | 3.7 | 2.6 | 3.5 | 5.0 | 6.3 | 7.7 | 7.1 | 68.5 |
| 7 | % humidity | 77 | 74 | 72 | 68 | 68 | 65 | 64 | 65 | 68 | 72 | 76 | 78 | 70.6 | | | | nov |
|---:|:-----------|
| 0 | 8.6 (47.5) | | [
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select count ( * ) where region = 'united kingdom' col : region | date | label | format | catalog row 1 : united kingdom | 1985-06-10 00:00:00 | i.r.s | vinyl lp | mirf1003 row 2 : united states | 1985-06-11 00:00:00 | i.r.s | lp | irs-5592 row 3 : united states | 1985-06-11 00:00:00 | i.r.s | cassette tape | irsc-5592 row 4 : united states | 1985-06-11 00:00:00 | i.r.s | compact disc | irsd-5592 row 5 : greece | 1985-01-01 00:00:00 | illegal | lp | 26525 row 6 : australia | 1985-01-01 00:00:00 | i.r.s./epic | lp | elps 4495 row 7 : the netherlands | 1985-01-01 00:00:00 | i.r.s | lp | 26525 row 8 : worldwide | 1990-01-01 00:00:00 | mca | compact disc | 5592 row 9 : worldwide | 1990-01-01 00:00:00 | i.r.s | cassette tape | irsc-5592 row 10 : the netherlands | 1992-08-06 00:00:00 | emi | compact disc | 7 13160 2 9 row 11 : united kingdom | 1992-01-01 00:00:00 | simply vinyl | 180-gram vinyl lp | svlp151 row 12 : worldwide | 1998-01-01 00:00:00 | capitol | compact disc | 93479 row 13 : europe | 1998-01-01 00:00:00 | emi | compact disc | 13160 row 14 : worldwide | 1999-01-01 00:00:00 | i.r.s | compact disc | 19016 row 15 : united states | 1999-01-01 00:00:00 | simply vinyl | lp | 151 row 16 : europe | 2000-01-01 00:00:00 | i.r.s | compact disc | 7131602 | col : count ( "*" ) row 1 : 2 | select count ( * ) where region = 'united kingdom' <table_name> : table \begin{tabular}{llllll}
\toprule
& region & date & label & format & catalog \\
\midrule
0 & united kingdom & 1985-06-10 00:00:00 & i.r.s & vinyl lp & mirf1003 \\
1 & united states & 1985-06-11 00:00:00 & i.r.s & lp & irs-5592 \\
2 & united states & 1985-06-11 00:00:00 & i.r.s & cassette tape & irsc-5592 \\
3 & united states & 1985-06-11 00:00:00 & i.r.s & compact disc & irsd-5592 \\
4 & greece & 1985-01-01 00:00:00 & illegal & lp & 26525 \\
5 & australia & 1985-01-01 00:00:00 & i.r.s./epic & lp & elps 4495 \\
6 & the netherlands & 1985-01-01 00:00:00 & i.r.s & lp & 26525 \\
7 & worldwide & 1990-01-01 00:00:00 & mca & compact disc & 5592 \\
8 & worldwide & 1990-01-01 00:00:00 & i.r.s & cassette tape & irsc-5592 \\
9 & the netherlands & 1992-08-06 00:00:00 & emi & compact disc & 7 13160 2 9 \\
10 & united kingdom & 1992-01-01 00:00:00 & simply vinyl & 180-gram vinyl lp & svlp151 \\
11 & worldwide & 1998-01-01 00:00:00 & capitol & compact disc & 93479 \\
12 & europe & 1998-01-01 00:00:00 & emi & compact disc & 13160 \\
13 & worldwide & 1999-01-01 00:00:00 & i.r.s & compact disc & 19016 \\
14 & united states & 1999-01-01 00:00:00 & simply vinyl & lp & 151 \\
15 & europe & 2000-01-01 00:00:00 & i.r.s & compact disc & 7131602 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( * ) where region = 'united kingdom' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>region</th>
<th>date</th>
<th>label</th>
<th>format</th>
<th>catalog</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>united kingdom</td>
<td>1985-06-10 00:00:00</td>
<td>i.r.s</td>
<td>vinyl lp</td>
<td>mirf1003</td>
</tr>
<tr>
<th>1</th>
<td>united states</td>
<td>1985-06-11 00:00:00</td>
<td>i.r.s</td>
<td>lp</td>
<td>irs-5592</td>
</tr>
<tr>
<th>2</th>
<td>united states</td>
<td>1985-06-11 00:00:00</td>
<td>i.r.s</td>
<td>cassette tape</td>
<td>irsc-5592</td>
</tr>
<tr>
<th>3</th>
<td>united states</td>
<td>1985-06-11 00:00:00</td>
<td>i.r.s</td>
<td>compact disc</td>
<td>irsd-5592</td>
</tr>
<tr>
<th>4</th>
<td>greece</td>
<td>1985-01-01 00:00:00</td>
<td>illegal</td>
<td>lp</td>
<td>26525</td>
</tr>
<tr>
<th>5</th>
<td>australia</td>
<td>1985-01-01 00:00:00</td>
<td>i.r.s./epic</td>
<td>lp</td>
<td>elps 4495</td>
</tr>
<tr>
<th>6</th>
<td>the netherlands</td>
<td>1985-01-01 00:00:00</td>
<td>i.r.s</td>
<td>lp</td>
<td>26525</td>
</tr>
<tr>
<th>7</th>
<td>worldwide</td>
<td>1990-01-01 00:00:00</td>
<td>mca</td>
<td>compact disc</td>
<td>5592</td>
</tr>
<tr>
<th>8</th>
<td>worldwide</td>
<td>1990-01-01 00:00:00</td>
<td>i.r.s</td>
<td>cassette tape</td>
<td>irsc-5592</td>
</tr>
<tr>
<th>9</th>
<td>the netherlands</td>
<td>1992-08-06 00:00:00</td>
<td>emi</td>
<td>compact disc</td>
<td>7 13160 2 9</td>
</tr>
<tr>
<th>10</th>
<td>united kingdom</td>
<td>1992-01-01 00:00:00</td>
<td>simply vinyl</td>
<td>180-gram vinyl lp</td>
<td>svlp151</td>
</tr>
<tr>
<th>11</th>
<td>worldwide</td>
<td>1998-01-01 00:00:00</td>
<td>capitol</td>
<td>compact disc</td>
<td>93479</td>
</tr>
<tr>
<th>12</th>
<td>europe</td>
<td>1998-01-01 00:00:00</td>
<td>emi</td>
<td>compact disc</td>
<td>13160</td>
</tr>
<tr>
<th>13</th>
<td>worldwide</td>
<td>1999-01-01 00:00:00</td>
<td>i.r.s</td>
<td>compact disc</td>
<td>19016</td>
</tr>
<tr>
<th>14</th>
<td>united states</td>
<td>1999-01-01 00:00:00</td>
<td>simply vinyl</td>
<td>lp</td>
<td>151</td>
</tr>
<tr>
<th>15</th>
<td>europe</td>
<td>2000-01-01 00:00:00</td>
<td>i.r.s</td>
<td>compact disc</td>
<td>7131602</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>2</td>
</tr>
</tbody>
</table> | select count ( * ) where region = 'united kingdom' <table_name> : table | | region | date | label | format | catalog |
|---:|:----------------|:--------------------|:-------------|:------------------|:------------|
| 0 | united kingdom | 1985-06-10 00:00:00 | i.r.s | vinyl lp | mirf1003 |
| 1 | united states | 1985-06-11 00:00:00 | i.r.s | lp | irs-5592 |
| 2 | united states | 1985-06-11 00:00:00 | i.r.s | cassette tape | irsc-5592 |
| 3 | united states | 1985-06-11 00:00:00 | i.r.s | compact disc | irsd-5592 |
| 4 | greece | 1985-01-01 00:00:00 | illegal | lp | 26525 |
| 5 | australia | 1985-01-01 00:00:00 | i.r.s./epic | lp | elps 4495 |
| 6 | the netherlands | 1985-01-01 00:00:00 | i.r.s | lp | 26525 |
| 7 | worldwide | 1990-01-01 00:00:00 | mca | compact disc | 5592 |
| 8 | worldwide | 1990-01-01 00:00:00 | i.r.s | cassette tape | irsc-5592 |
| 9 | the netherlands | 1992-08-06 00:00:00 | emi | compact disc | 7 13160 2 9 |
| 10 | united kingdom | 1992-01-01 00:00:00 | simply vinyl | 180-gram vinyl lp | svlp151 |
| 11 | worldwide | 1998-01-01 00:00:00 | capitol | compact disc | 93479 |
| 12 | europe | 1998-01-01 00:00:00 | emi | compact disc | 13160 |
| 13 | worldwide | 1999-01-01 00:00:00 | i.r.s | compact disc | 19016 |
| 14 | united states | 1999-01-01 00:00:00 | simply vinyl | lp | 151 |
| 15 | europe | 2000-01-01 00:00:00 | i.r.s | compact disc | 7131602 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 2 | | [
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select passengers where city = 'charlotte, nc' col : rank | city | passengers | top carriers row 1 : 1 | los angeles, ca | 700000 | american, spirit, united row 2 : 2 | chicago, il | 673000 | american, spirit, united row 3 : 3 | denver, co | 654000 | frontier, spirit, united row 4 : 4 | san francisco, ca | 492000 | united row 5 : 5 | dallas/fort worth, tx | 488000 | american, united row 6 : 6 | newark, nj | 480000 | united row 7 : 7 | las vegas, nv | 442000 | spirit, united row 8 : 8 | charlotte, nc | 441000 | united, us airways row 9 : 9 | atlanta, ga | 400000 | delta, united row 10 : 10 | phoenix, az | 393000 | united, us airways | col : passengers row 1 : 441000 | select passengers where city = 'charlotte, nc' <table_name> : table \begin{tabular}{lllll}
\toprule
& rank & city & passengers & top carriers \\
\midrule
0 & 1 & los angeles, ca & 700000 & american, spirit, united \\
1 & 2 & chicago, il & 673000 & american, spirit, united \\
2 & 3 & denver, co & 654000 & frontier, spirit, united \\
3 & 4 & san francisco, ca & 492000 & united \\
4 & 5 & dallas/fort worth, tx & 488000 & american, united \\
5 & 6 & newark, nj & 480000 & united \\
6 & 7 & las vegas, nv & 442000 & spirit, united \\
7 & 8 & charlotte, nc & 441000 & united, us airways \\
8 & 9 & atlanta, ga & 400000 & delta, united \\
9 & 10 & phoenix, az & 393000 & united, us airways \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& passengers \\
\midrule
0 & 441000 \\
\bottomrule
\end{tabular}
| select passengers where city = 'charlotte, nc' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>city</th>
<th>passengers</th>
<th>top carriers</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>los angeles, ca</td>
<td>700000</td>
<td>american, spirit, united</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>chicago, il</td>
<td>673000</td>
<td>american, spirit, united</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>denver, co</td>
<td>654000</td>
<td>frontier, spirit, united</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>san francisco, ca</td>
<td>492000</td>
<td>united</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>dallas/fort worth, tx</td>
<td>488000</td>
<td>american, united</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>newark, nj</td>
<td>480000</td>
<td>united</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>las vegas, nv</td>
<td>442000</td>
<td>spirit, united</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>charlotte, nc</td>
<td>441000</td>
<td>united, us airways</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>atlanta, ga</td>
<td>400000</td>
<td>delta, united</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>phoenix, az</td>
<td>393000</td>
<td>united, us airways</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>passengers</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>441000</td>
</tr>
</tbody>
</table> | select passengers where city = 'charlotte, nc' <table_name> : table | | rank | city | passengers | top carriers |
|---:|-------:|:----------------------|-------------:|:-------------------------|
| 0 | 1 | los angeles, ca | 700000 | american, spirit, united |
| 1 | 2 | chicago, il | 673000 | american, spirit, united |
| 2 | 3 | denver, co | 654000 | frontier, spirit, united |
| 3 | 4 | san francisco, ca | 492000 | united |
| 4 | 5 | dallas/fort worth, tx | 488000 | american, united |
| 5 | 6 | newark, nj | 480000 | united |
| 6 | 7 | las vegas, nv | 442000 | spirit, united |
| 7 | 8 | charlotte, nc | 441000 | united, us airways |
| 8 | 9 | atlanta, ga | 400000 | delta, united |
| 9 | 10 | phoenix, az | 393000 | united, us airways | | | | passengers |
|---:|-------------:|
| 0 | 441000 | | [
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select count ( years ) where 1986 = 1617 col : nation | 1986 | 1989 | 1991 | 1997 | 1999 | 2000 | 2003 | 2005 | 2007 | 2009 | 2011 | years row 1 : argentina | 4th | none | 4th | 4th | 3rd | 4th | 2nd | 2nd | 2nd | 1st | 2nd | 10 row 2 : brazil | 3rd | 3rd | 3rd | 1st | 1st | 1st | 1st | 1st | 1st | 2nd | 1st | 11 row 3 : canada | 2nd | 1st | 2nd | 2nd | none | none | 5th | 4th | 6th | none | none | 7 row 4 : chile | none | none | none | none | none | none | none | none | none | 3rd | 5th | 2 row 5 : colombia | none | none | none | none | 6th | 6th | none | none | none | none | none | 2 row 6 : costa rica | none | none | none | 5th | none | none | none | none | none | none | none | 1 row 7 : cuba | none | none | none | none | 2nd | none | none | none | none | none | 3rd | 2 row 8 : dominican republic | none | none | none | none | none | none | 6th | 5th | 3rd | 4th | 6th | 5 row 9 : greenland | none | none | none | none | 5th | 3rd | none | none | none | none | none | 2 row 10 : guatemala | none | none | none | none | none | none | 7th | none | none | none | none | 1 row 11 : mexico | none | 4th | none | 6th | none | 5th | none | none | 8th | 5th | 7th | 6 row 12 : paraguay | none | none | 6th | none | none | none | none | none | 4th | 7th | none | 3 row 13 : puerto rico | none | none | 7th | none | none | none | none | none | none | none | none | 1 row 14 : uruguay | none | none | 5th | 3rd | 4th | 2nd | 3rd | 3rd | 5th | 6th | 4th | 9 row 15 : united states | 1st | 2nd | 1st | none | none | none | 4th | 6th | 7th | none | none | 6 row 16 : venezuela | none | none | none | none | none | none | none | none | none | none | 8th | 1 | col : count ( "years" ) row 1 : 0 | select count ( years ) where 1986 = 1617 <table_name> : table \begin{tabular}{llllllllllllll}
\toprule
& nation & 1986 & 1989 & 1991 & 1997 & 1999 & 2000 & 2003 & 2005 & 2007 & 2009 & 2011 & years \\
\midrule
0 & argentina & 4th & none & 4th & 4th & 3rd & 4th & 2nd & 2nd & 2nd & 1st & 2nd & 10 \\
1 & brazil & 3rd & 3rd & 3rd & 1st & 1st & 1st & 1st & 1st & 1st & 2nd & 1st & 11 \\
2 & canada & 2nd & 1st & 2nd & 2nd & none & none & 5th & 4th & 6th & none & none & 7 \\
3 & chile & none & none & none & none & none & none & none & none & none & 3rd & 5th & 2 \\
4 & colombia & none & none & none & none & 6th & 6th & none & none & none & none & none & 2 \\
5 & costa rica & none & none & none & 5th & none & none & none & none & none & none & none & 1 \\
6 & cuba & none & none & none & none & 2nd & none & none & none & none & none & 3rd & 2 \\
7 & dominican republic & none & none & none & none & none & none & 6th & 5th & 3rd & 4th & 6th & 5 \\
8 & greenland & none & none & none & none & 5th & 3rd & none & none & none & none & none & 2 \\
9 & guatemala & none & none & none & none & none & none & 7th & none & none & none & none & 1 \\
10 & mexico & none & 4th & none & 6th & none & 5th & none & none & 8th & 5th & 7th & 6 \\
11 & paraguay & none & none & 6th & none & none & none & none & none & 4th & 7th & none & 3 \\
12 & puerto rico & none & none & 7th & none & none & none & none & none & none & none & none & 1 \\
13 & uruguay & none & none & 5th & 3rd & 4th & 2nd & 3rd & 3rd & 5th & 6th & 4th & 9 \\
14 & united states & 1st & 2nd & 1st & none & none & none & 4th & 6th & 7th & none & none & 6 \\
15 & venezuela & none & none & none & none & none & none & none & none & none & none & 8th & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "years" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( years ) where 1986 = 1617 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
<th>1986</th>
<th>1989</th>
<th>1991</th>
<th>1997</th>
<th>1999</th>
<th>2000</th>
<th>2003</th>
<th>2005</th>
<th>2007</th>
<th>2009</th>
<th>2011</th>
<th>years</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>argentina</td>
<td>4th</td>
<td>none</td>
<td>4th</td>
<td>4th</td>
<td>3rd</td>
<td>4th</td>
<td>2nd</td>
<td>2nd</td>
<td>2nd</td>
<td>1st</td>
<td>2nd</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>brazil</td>
<td>3rd</td>
<td>3rd</td>
<td>3rd</td>
<td>1st</td>
<td>1st</td>
<td>1st</td>
<td>1st</td>
<td>1st</td>
<td>1st</td>
<td>2nd</td>
<td>1st</td>
<td>11</td>
</tr>
<tr>
<th>2</th>
<td>canada</td>
<td>2nd</td>
<td>1st</td>
<td>2nd</td>
<td>2nd</td>
<td>none</td>
<td>none</td>
<td>5th</td>
<td>4th</td>
<td>6th</td>
<td>none</td>
<td>none</td>
<td>7</td>
</tr>
<tr>
<th>3</th>
<td>chile</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>3rd</td>
<td>5th</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>colombia</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>6th</td>
<td>6th</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>costa rica</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>5th</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>6</th>
<td>cuba</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>2nd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>3rd</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>dominican republic</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>6th</td>
<td>5th</td>
<td>3rd</td>
<td>4th</td>
<td>6th</td>
<td>5</td>
</tr>
<tr>
<th>8</th>
<td>greenland</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>5th</td>
<td>3rd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>guatemala</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>7th</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>mexico</td>
<td>none</td>
<td>4th</td>
<td>none</td>
<td>6th</td>
<td>none</td>
<td>5th</td>
<td>none</td>
<td>none</td>
<td>8th</td>
<td>5th</td>
<td>7th</td>
<td>6</td>
</tr>
<tr>
<th>11</th>
<td>paraguay</td>
<td>none</td>
<td>none</td>
<td>6th</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>4th</td>
<td>7th</td>
<td>none</td>
<td>3</td>
</tr>
<tr>
<th>12</th>
<td>puerto rico</td>
<td>none</td>
<td>none</td>
<td>7th</td>
<td>none</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>13</th>
<td>uruguay</td>
<td>none</td>
<td>none</td>
<td>5th</td>
<td>3rd</td>
<td>4th</td>
<td>2nd</td>
<td>3rd</td>
<td>3rd</td>
<td>5th</td>
<td>6th</td>
<td>4th</td>
<td>9</td>
</tr>
<tr>
<th>14</th>
<td>united states</td>
<td>1st</td>
<td>2nd</td>
<td>1st</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>4th</td>
<td>6th</td>
<td>7th</td>
<td>none</td>
<td>none</td>
<td>6</td>
</tr>
<tr>
<th>15</th>
<td>venezuela</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>8th</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "years" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( years ) where 1986 = 1617 <table_name> : table | | nation | 1986 | 1989 | 1991 | 1997 | 1999 | 2000 | 2003 | 2005 | 2007 | 2009 | 2011 | years |
|---:|:-------------------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|:-------|--------:|
| 0 | argentina | 4th | none | 4th | 4th | 3rd | 4th | 2nd | 2nd | 2nd | 1st | 2nd | 10 |
| 1 | brazil | 3rd | 3rd | 3rd | 1st | 1st | 1st | 1st | 1st | 1st | 2nd | 1st | 11 |
| 2 | canada | 2nd | 1st | 2nd | 2nd | none | none | 5th | 4th | 6th | none | none | 7 |
| 3 | chile | none | none | none | none | none | none | none | none | none | 3rd | 5th | 2 |
| 4 | colombia | none | none | none | none | 6th | 6th | none | none | none | none | none | 2 |
| 5 | costa rica | none | none | none | 5th | none | none | none | none | none | none | none | 1 |
| 6 | cuba | none | none | none | none | 2nd | none | none | none | none | none | 3rd | 2 |
| 7 | dominican republic | none | none | none | none | none | none | 6th | 5th | 3rd | 4th | 6th | 5 |
| 8 | greenland | none | none | none | none | 5th | 3rd | none | none | none | none | none | 2 |
| 9 | guatemala | none | none | none | none | none | none | 7th | none | none | none | none | 1 |
| 10 | mexico | none | 4th | none | 6th | none | 5th | none | none | 8th | 5th | 7th | 6 |
| 11 | paraguay | none | none | 6th | none | none | none | none | none | 4th | 7th | none | 3 |
| 12 | puerto rico | none | none | 7th | none | none | none | none | none | none | none | none | 1 |
| 13 | uruguay | none | none | 5th | 3rd | 4th | 2nd | 3rd | 3rd | 5th | 6th | 4th | 9 |
| 14 | united states | 1st | 2nd | 1st | none | none | none | 4th | 6th | 7th | none | none | 6 |
| 15 | venezuela | none | none | none | none | none | none | none | none | none | none | 8th | 1 | | | | count ( "years" ) |
|---:|--------------------:|
| 0 | 0 | | [
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select count ( * ) where name = 'daianji' col : name | japanese | distance (km) | connections | location row 1 : okayama | 岡山 | 0.0 | sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line | kita-ku, okayama row 2 : bizen-mikado | 備前三門 | 1.9 | none | kita-ku, okayama row 3 : daianji | 大安寺 | 3.3 | none | kita-ku, okayama row 4 : bizen-ichinomiya | 備前一宮 | 6.5 | none | kita-ku, okayama row 5 : kibitsu | 吉備津 | 8.4 | none | kita-ku, okayama row 6 : bitchu-takamatsu | 備中高松 | 11.0 | none | kita-ku, okayama row 7 : ashimori | 足守 | 13.4 | none | kita-ku, okayama row 8 : hattori | 服部 | 16.2 | none | soja row 9 : higashi-soja | 東総社 | 18.8 | none | soja row 10 : soja | 総社 | 20.4 | hakubi line ibara railway ibara line | soja | col : count ( "*" ) row 1 : 1 | select count ( * ) where name = 'daianji' <table_name> : table \begin{tabular}{llllll}
\toprule
& name & japanese & distance (km) & connections & location \\
\midrule
0 & okayama & 岡山 & 0.0 & sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line & kita-ku, okayama \\
1 & bizen-mikado & 備前三門 & 1.9 & none & kita-ku, okayama \\
2 & daianji & 大安寺 & 3.3 & none & kita-ku, okayama \\
3 & bizen-ichinomiya & 備前一宮 & 6.5 & none & kita-ku, okayama \\
4 & kibitsu & 吉備津 & 8.4 & none & kita-ku, okayama \\
5 & bitchu-takamatsu & 備中高松 & 11.0 & none & kita-ku, okayama \\
6 & ashimori & 足守 & 13.4 & none & kita-ku, okayama \\
7 & hattori & 服部 & 16.2 & none & soja \\
8 & higashi-soja & 東総社 & 18.8 & none & soja \\
9 & soja & 総社 & 20.4 & hakubi line ibara railway ibara line & soja \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where name = 'daianji' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>japanese</th>
<th>distance (km)</th>
<th>connections</th>
<th>location</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>okayama</td>
<td>岡山</td>
<td>0.0</td>
<td>sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>1</th>
<td>bizen-mikado</td>
<td>備前三門</td>
<td>1.9</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>2</th>
<td>daianji</td>
<td>大安寺</td>
<td>3.3</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>3</th>
<td>bizen-ichinomiya</td>
<td>備前一宮</td>
<td>6.5</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>4</th>
<td>kibitsu</td>
<td>吉備津</td>
<td>8.4</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>5</th>
<td>bitchu-takamatsu</td>
<td>備中高松</td>
<td>11.0</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>6</th>
<td>ashimori</td>
<td>足守</td>
<td>13.4</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>7</th>
<td>hattori</td>
<td>服部</td>
<td>16.2</td>
<td>none</td>
<td>soja</td>
</tr>
<tr>
<th>8</th>
<td>higashi-soja</td>
<td>東総社</td>
<td>18.8</td>
<td>none</td>
<td>soja</td>
</tr>
<tr>
<th>9</th>
<td>soja</td>
<td>総社</td>
<td>20.4</td>
<td>hakubi line ibara railway ibara line</td>
<td>soja</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 = 'daianji' <table_name> : table | | name | japanese | distance (km) | connections | location |
|---:|:-----------------|:-----------|----------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
| 0 | okayama | 岡山 | 0 | sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line | kita-ku, okayama |
| 1 | bizen-mikado | 備前三門 | 1.9 | none | kita-ku, okayama |
| 2 | daianji | 大安寺 | 3.3 | none | kita-ku, okayama |
| 3 | bizen-ichinomiya | 備前一宮 | 6.5 | none | kita-ku, okayama |
| 4 | kibitsu | 吉備津 | 8.4 | none | kita-ku, okayama |
| 5 | bitchu-takamatsu | 備中高松 | 11 | none | kita-ku, okayama |
| 6 | ashimori | 足守 | 13.4 | none | kita-ku, okayama |
| 7 | hattori | 服部 | 16.2 | none | soja |
| 8 | higashi-soja | 東総社 | 18.8 | none | soja |
| 9 | soja | 総社 | 20.4 | hakubi line ibara railway ibara line | soja | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where nationality = 'royal australian navy' col : date | ship | nationality | tonnage | fate row 1 : 1941-08-19 00:00:00 | ss aguila | united kingdom | 3255 | sunk row 2 : 1941-11-27 00:00:00 | hmas parramatta | royal australian navy | 1060 | sunk row 3 : 1941-12-23 00:00:00 | ss shuntien | united kingdom | 3059 | sunk row 4 : 1941-12-26 00:00:00 | ss warszawa | poland | 2487 | sunk row 5 : 1942-06-10 00:00:00 | mv athene | norway | 4681 | sunk row 6 : 1942-06-10 00:00:00 | ss brambleleaf | united kingdom | 5917 | damaged | col : count ( "*" ) row 1 : 1 | select count ( * ) where nationality = 'royal australian navy' <table_name> : table \begin{tabular}{llllll}
\toprule
& date & ship & nationality & tonnage & fate \\
\midrule
0 & 1941-08-19 00:00:00 & ss aguila & united kingdom & 3255 & sunk \\
1 & 1941-11-27 00:00:00 & hmas parramatta & royal australian navy & 1060 & sunk \\
2 & 1941-12-23 00:00:00 & ss shuntien & united kingdom & 3059 & sunk \\
3 & 1941-12-26 00:00:00 & ss warszawa & poland & 2487 & sunk \\
4 & 1942-06-10 00:00:00 & mv athene & norway & 4681 & sunk \\
5 & 1942-06-10 00:00:00 & ss brambleleaf & united kingdom & 5917 & damaged \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where nationality = 'royal australian navy' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>ship</th>
<th>nationality</th>
<th>tonnage</th>
<th>fate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1941-08-19 00:00:00</td>
<td>ss aguila</td>
<td>united kingdom</td>
<td>3255</td>
<td>sunk</td>
</tr>
<tr>
<th>1</th>
<td>1941-11-27 00:00:00</td>
<td>hmas parramatta</td>
<td>royal australian navy</td>
<td>1060</td>
<td>sunk</td>
</tr>
<tr>
<th>2</th>
<td>1941-12-23 00:00:00</td>
<td>ss shuntien</td>
<td>united kingdom</td>
<td>3059</td>
<td>sunk</td>
</tr>
<tr>
<th>3</th>
<td>1941-12-26 00:00:00</td>
<td>ss warszawa</td>
<td>poland</td>
<td>2487</td>
<td>sunk</td>
</tr>
<tr>
<th>4</th>
<td>1942-06-10 00:00:00</td>
<td>mv athene</td>
<td>norway</td>
<td>4681</td>
<td>sunk</td>
</tr>
<tr>
<th>5</th>
<td>1942-06-10 00:00:00</td>
<td>ss brambleleaf</td>
<td>united kingdom</td>
<td>5917</td>
<td>damaged</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 nationality = 'royal australian navy' <table_name> : table | | date | ship | nationality | tonnage | fate |
|---:|:--------------------|:----------------|:----------------------|----------:|:--------|
| 0 | 1941-08-19 00:00:00 | ss aguila | united kingdom | 3255 | sunk |
| 1 | 1941-11-27 00:00:00 | hmas parramatta | royal australian navy | 1060 | sunk |
| 2 | 1941-12-23 00:00:00 | ss shuntien | united kingdom | 3059 | sunk |
| 3 | 1941-12-26 00:00:00 | ss warszawa | poland | 2487 | sunk |
| 4 | 1942-06-10 00:00:00 | mv athene | norway | 4681 | sunk |
| 5 | 1942-06-10 00:00:00 | ss brambleleaf | united kingdom | 5917 | damaged | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select year where category = 'best album' col : year | award | nominated work | category | result row 1 : 2007 | cosmopolitan ultimate woman of the year | leona lewis | newcomer of the year | won row 2 : 2007 | the record of the year | "bleeding love" | the record of the year | won row 3 : 2008 | capital awards | leona lewis | favourite uk female artist | won row 4 : 2008 | britain's best | leona lewis | music award | won row 5 : 2008 | newnownext awards | leona lewis | the kylie award: next international crossover | won row 6 : 2008 | glamour woman of the year awards | leona lewis | uk solo artist | won row 7 : 2008 | nickelodeon uk kids choice awards | "bleeding love" | favourite song | won row 8 : 2008 | uk music video awards | "bleeding love" | people's choice award | won row 9 : 2008 | bambi award | leona lewis | shooting star | won row 10 : 2008 | new music weekly awards | leona lewis | top 40 new artist of the year | won row 11 : 2008 | billboard 2008 year end award | leona lewis | best new artist | won row 12 : 2008 | vh1 video of the year | "bleeding love" | best video | won row 13 : 2008 | nme best album | "spirit" | best album | nominated row 14 : 2008 | peta | leona lewis | person of the year | won row 15 : 2009 | naacp image awards | leona lewis | outstanding new artist | nominated row 16 : 2009 | swiss music awards | leona lewis | best international newcomer | won row 17 : 2009 | japan gold disc awards | leona lewis | new artist of the year | won row 18 : 2009 | hito pop music awards | "bleeding love" | best western song | won row 19 : 2009 | peta - sexiest vegetarian alive awards | leona lewis | sexiest vegetarian celebrity 2009 | won row 20 : 2009 | apra awards | "bleeding love" | most played foreign work | won row 21 : 2009 | beffta awards | leona lewis | best female act | won row 22 : 2009 | cosmopolitan awards | leona lewis | ultimate music star | won | col : year row 1 : 2008 | select year where category = 'best album' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & award & nominated work & category & result \\
\midrule
0 & 2007 & cosmopolitan ultimate woman of the year & leona lewis & newcomer of the year & won \\
1 & 2007 & the record of the year & "bleeding love" & the record of the year & won \\
2 & 2008 & capital awards & leona lewis & favourite uk female artist & won \\
3 & 2008 & britain's best & leona lewis & music award & won \\
4 & 2008 & newnownext awards & leona lewis & the kylie award: next international crossover & won \\
5 & 2008 & glamour woman of the year awards & leona lewis & uk solo artist & won \\
6 & 2008 & nickelodeon uk kids choice awards & "bleeding love" & favourite song & won \\
7 & 2008 & uk music video awards & "bleeding love" & people's choice award & won \\
8 & 2008 & bambi award & leona lewis & shooting star & won \\
9 & 2008 & new music weekly awards & leona lewis & top 40 new artist of the year & won \\
10 & 2008 & billboard 2008 year end award & leona lewis & best new artist & won \\
11 & 2008 & vh1 video of the year & "bleeding love" & best video & won \\
12 & 2008 & nme best album & "spirit" & best album & nominated \\
13 & 2008 & peta & leona lewis & person of the year & won \\
14 & 2009 & naacp image awards & leona lewis & outstanding new artist & nominated \\
15 & 2009 & swiss music awards & leona lewis & best international newcomer & won \\
16 & 2009 & japan gold disc awards & leona lewis & new artist of the year & won \\
17 & 2009 & hito pop music awards & "bleeding love" & best western song & won \\
18 & 2009 & peta - sexiest vegetarian alive awards & leona lewis & sexiest vegetarian celebrity 2009 & won \\
19 & 2009 & apra awards & "bleeding love" & most played foreign work & won \\
20 & 2009 & beffta awards & leona lewis & best female act & won \\
21 & 2009 & cosmopolitan awards & leona lewis & ultimate music star & won \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 2008 \\
\bottomrule
\end{tabular}
| select year where category = 'best album' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>award</th>
<th>nominated work</th>
<th>category</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2007</td>
<td>cosmopolitan ultimate woman of the year</td>
<td>leona lewis</td>
<td>newcomer of the year</td>
<td>won</td>
</tr>
<tr>
<th>1</th>
<td>2007</td>
<td>the record of the year</td>
<td>"bleeding love"</td>
<td>the record of the year</td>
<td>won</td>
</tr>
<tr>
<th>2</th>
<td>2008</td>
<td>capital awards</td>
<td>leona lewis</td>
<td>favourite uk female artist</td>
<td>won</td>
</tr>
<tr>
<th>3</th>
<td>2008</td>
<td>britain's best</td>
<td>leona lewis</td>
<td>music award</td>
<td>won</td>
</tr>
<tr>
<th>4</th>
<td>2008</td>
<td>newnownext awards</td>
<td>leona lewis</td>
<td>the kylie award: next international crossover</td>
<td>won</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>glamour woman of the year awards</td>
<td>leona lewis</td>
<td>uk solo artist</td>
<td>won</td>
</tr>
<tr>
<th>6</th>
<td>2008</td>
<td>nickelodeon uk kids choice awards</td>
<td>"bleeding love"</td>
<td>favourite song</td>
<td>won</td>
</tr>
<tr>
<th>7</th>
<td>2008</td>
<td>uk music video awards</td>
<td>"bleeding love"</td>
<td>people's choice award</td>
<td>won</td>
</tr>
<tr>
<th>8</th>
<td>2008</td>
<td>bambi award</td>
<td>leona lewis</td>
<td>shooting star</td>
<td>won</td>
</tr>
<tr>
<th>9</th>
<td>2008</td>
<td>new music weekly awards</td>
<td>leona lewis</td>
<td>top 40 new artist of the year</td>
<td>won</td>
</tr>
<tr>
<th>10</th>
<td>2008</td>
<td>billboard 2008 year end award</td>
<td>leona lewis</td>
<td>best new artist</td>
<td>won</td>
</tr>
<tr>
<th>11</th>
<td>2008</td>
<td>vh1 video of the year</td>
<td>"bleeding love"</td>
<td>best video</td>
<td>won</td>
</tr>
<tr>
<th>12</th>
<td>2008</td>
<td>nme best album</td>
<td>"spirit"</td>
<td>best album</td>
<td>nominated</td>
</tr>
<tr>
<th>13</th>
<td>2008</td>
<td>peta</td>
<td>leona lewis</td>
<td>person of the year</td>
<td>won</td>
</tr>
<tr>
<th>14</th>
<td>2009</td>
<td>naacp image awards</td>
<td>leona lewis</td>
<td>outstanding new artist</td>
<td>nominated</td>
</tr>
<tr>
<th>15</th>
<td>2009</td>
<td>swiss music awards</td>
<td>leona lewis</td>
<td>best international newcomer</td>
<td>won</td>
</tr>
<tr>
<th>16</th>
<td>2009</td>
<td>japan gold disc awards</td>
<td>leona lewis</td>
<td>new artist of the year</td>
<td>won</td>
</tr>
<tr>
<th>17</th>
<td>2009</td>
<td>hito pop music awards</td>
<td>"bleeding love"</td>
<td>best western song</td>
<td>won</td>
</tr>
<tr>
<th>18</th>
<td>2009</td>
<td>peta - sexiest vegetarian alive awards</td>
<td>leona lewis</td>
<td>sexiest vegetarian celebrity 2009</td>
<td>won</td>
</tr>
<tr>
<th>19</th>
<td>2009</td>
<td>apra awards</td>
<td>"bleeding love"</td>
<td>most played foreign work</td>
<td>won</td>
</tr>
<tr>
<th>20</th>
<td>2009</td>
<td>beffta awards</td>
<td>leona lewis</td>
<td>best female act</td>
<td>won</td>
</tr>
<tr>
<th>21</th>
<td>2009</td>
<td>cosmopolitan awards</td>
<td>leona lewis</td>
<td>ultimate music star</td>
<td>won</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 category = 'best album' <table_name> : table | | year | award | nominated work | category | result |
|---:|-------:|:----------------------------------------|:-----------------|:----------------------------------------------|:----------|
| 0 | 2007 | cosmopolitan ultimate woman of the year | leona lewis | newcomer of the year | won |
| 1 | 2007 | the record of the year | "bleeding love" | the record of the year | won |
| 2 | 2008 | capital awards | leona lewis | favourite uk female artist | won |
| 3 | 2008 | britain's best | leona lewis | music award | won |
| 4 | 2008 | newnownext awards | leona lewis | the kylie award: next international crossover | won |
| 5 | 2008 | glamour woman of the year awards | leona lewis | uk solo artist | won |
| 6 | 2008 | nickelodeon uk kids choice awards | "bleeding love" | favourite song | won |
| 7 | 2008 | uk music video awards | "bleeding love" | people's choice award | won |
| 8 | 2008 | bambi award | leona lewis | shooting star | won |
| 9 | 2008 | new music weekly awards | leona lewis | top 40 new artist of the year | won |
| 10 | 2008 | billboard 2008 year end award | leona lewis | best new artist | won |
| 11 | 2008 | vh1 video of the year | "bleeding love" | best video | won |
| 12 | 2008 | nme best album | "spirit" | best album | nominated |
| 13 | 2008 | peta | leona lewis | person of the year | won |
| 14 | 2009 | naacp image awards | leona lewis | outstanding new artist | nominated |
| 15 | 2009 | swiss music awards | leona lewis | best international newcomer | won |
| 16 | 2009 | japan gold disc awards | leona lewis | new artist of the year | won |
| 17 | 2009 | hito pop music awards | "bleeding love" | best western song | won |
| 18 | 2009 | peta - sexiest vegetarian alive awards | leona lewis | sexiest vegetarian celebrity 2009 | won |
| 19 | 2009 | apra awards | "bleeding love" | most played foreign work | won |
| 20 | 2009 | beffta awards | leona lewis | best female act | won |
| 21 | 2009 | cosmopolitan awards | leona lewis | ultimate music star | won | | | | year |
|---:|-------:|
| 0 | 2008 | | [
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select position where year < 1992 order by year desc limit 1 col : year | competition | venue | position | notes row 1 : 1989 | european indoor championships | the hague, netherlands | 10th | none row 2 : 1989 | world indoor championships | budapest, hungary | 9th | none row 3 : 1991 | world indoor championships | lisbon, portugal | 6th | none row 4 : 1991 | world championships | tokyo, japan | 5th | 5.75 m nr row 5 : 1992 | european indoor championships | genoa, italy | 5th | none row 6 : 1993 | world championships | stuttgart, germany | 11th | none | col : position row 1 : 10th row 2 : 9th row 3 : 6th row 4 : 5th row 5 : 5th | select position where year < 1992 order by year desc limit 1 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & competition & venue & position & notes \\
\midrule
0 & 1989 & european indoor championships & the hague, netherlands & 10th & none \\
1 & 1989 & world indoor championships & budapest, hungary & 9th & none \\
2 & 1991 & world indoor championships & lisbon, portugal & 6th & none \\
3 & 1991 & world championships & tokyo, japan & 5th & 5.75 m nr \\
4 & 1992 & european indoor championships & genoa, italy & 5th & none \\
5 & 1993 & world championships & stuttgart, germany & 11th & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& position \\
\midrule
0 & 10th \\
1 & 9th \\
2 & 6th \\
3 & 5th \\
4 & 5th \\
\bottomrule
\end{tabular}
| select position where year < 1992 order by year desc limit 1 <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>1989</td>
<td>european indoor championships</td>
<td>the hague, netherlands</td>
<td>10th</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1989</td>
<td>world indoor championships</td>
<td>budapest, hungary</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1991</td>
<td>world indoor championships</td>
<td>lisbon, portugal</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1991</td>
<td>world championships</td>
<td>tokyo, japan</td>
<td>5th</td>
<td>5.75 m nr</td>
</tr>
<tr>
<th>4</th>
<td>1992</td>
<td>european indoor championships</td>
<td>genoa, italy</td>
<td>5th</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1993</td>
<td>world championships</td>
<td>stuttgart, germany</td>
<td>11th</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>10th</td>
</tr>
<tr>
<th>1</th>
<td>9th</td>
</tr>
<tr>
<th>2</th>
<td>6th</td>
</tr>
<tr>
<th>3</th>
<td>5th</td>
</tr>
<tr>
<th>4</th>
<td>5th</td>
</tr>
</tbody>
</table> | select position where year < 1992 order by year desc limit 1 <table_name> : table | | year | competition | venue | position | notes |
|---:|-------:|:------------------------------|:-----------------------|:-----------|:----------|
| 0 | 1989 | european indoor championships | the hague, netherlands | 10th | none |
| 1 | 1989 | world indoor championships | budapest, hungary | 9th | none |
| 2 | 1991 | world indoor championships | lisbon, portugal | 6th | none |
| 3 | 1991 | world championships | tokyo, japan | 5th | 5.75 m nr |
| 4 | 1992 | european indoor championships | genoa, italy | 5th | none |
| 5 | 1993 | world championships | stuttgart, germany | 11th | none | | | | position |
|---:|:-----------|
| 0 | 10th |
| 1 | 9th |
| 2 | 6th |
| 3 | 5th |
| 4 | 5th | | [
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] |
select count ( * ) where nation = 'russia' col : rank | nation | gold | silver | bronze | total row 1 : 1 | canada | 9 | 6 | 5 | 20 row 2 : 2 | united states | 8 | 7 | 8 | 23 row 3 : 3 | austria | 7 | 9 | 8 | 24 row 4 : 4 | japan | 4 | 2 | 1 | 7 row 5 : 5 | italy | 3 | 7 | 4 | 14 row 6 : 6 | france | 3 | 4 | 4 | 11 row 7 : 7 | australia | 3 | 4 | 0 | 7 row 8 : 8 | norway | 2 | 2 | 2 | 6 row 9 : 9 | slovenia | 2 | 1 | 2 | 5 row 10 : 10 | finland | 2 | 1 | 1 | 4 row 11 : 10 | germany | 2 | 1 | 1 | 4 row 12 : 12 | russia | 2 | 0 | 3 | 5 row 13 : 13 | switzerland | 1 | 5 | 5 | 11 row 14 : 14 | china | 1 | 1 | 1 | 3 row 15 : 15 | poland | 1 | 1 | 0 | 2 row 16 : 16 | czech republic | 1 | 0 | 1 | 2 row 17 : 17 | belgium | 1 | 0 | 0 | 1 row 18 : 18 | netherlands | 0 | 1 | 0 | 1 row 19 : 19 | spain | 0 | 0 | 3 | 3 row 20 : 20 | bulgaria | 0 | 0 | 1 | 1 row 21 : 20 | great britain | 0 | 0 | 1 | 1 row 22 : 20 | sweden | 0 | 0 | 1 | 1 row 23 : total | total | 52 | 52 | 52 | 156 | col : count ( "*" ) row 1 : 1 | select count ( * ) where nation = 'russia' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & canada & 9 & 6 & 5 & 20 \\
1 & 2 & united states & 8 & 7 & 8 & 23 \\
2 & 3 & austria & 7 & 9 & 8 & 24 \\
3 & 4 & japan & 4 & 2 & 1 & 7 \\
4 & 5 & italy & 3 & 7 & 4 & 14 \\
5 & 6 & france & 3 & 4 & 4 & 11 \\
6 & 7 & australia & 3 & 4 & 0 & 7 \\
7 & 8 & norway & 2 & 2 & 2 & 6 \\
8 & 9 & slovenia & 2 & 1 & 2 & 5 \\
9 & 10 & finland & 2 & 1 & 1 & 4 \\
10 & 10 & germany & 2 & 1 & 1 & 4 \\
11 & 12 & russia & 2 & 0 & 3 & 5 \\
12 & 13 & switzerland & 1 & 5 & 5 & 11 \\
13 & 14 & china & 1 & 1 & 1 & 3 \\
14 & 15 & poland & 1 & 1 & 0 & 2 \\
15 & 16 & czech republic & 1 & 0 & 1 & 2 \\
16 & 17 & belgium & 1 & 0 & 0 & 1 \\
17 & 18 & netherlands & 0 & 1 & 0 & 1 \\
18 & 19 & spain & 0 & 0 & 3 & 3 \\
19 & 20 & bulgaria & 0 & 0 & 1 & 1 \\
20 & 20 & great britain & 0 & 0 & 1 & 1 \\
21 & 20 & sweden & 0 & 0 & 1 & 1 \\
22 & total & total & 52 & 52 & 52 & 156 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where nation = 'russia' <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>canada</td>
<td>9</td>
<td>6</td>
<td>5</td>
<td>20</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>united states</td>
<td>8</td>
<td>7</td>
<td>8</td>
<td>23</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>austria</td>
<td>7</td>
<td>9</td>
<td>8</td>
<td>24</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>japan</td>
<td>4</td>
<td>2</td>
<td>1</td>
<td>7</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>italy</td>
<td>3</td>
<td>7</td>
<td>4</td>
<td>14</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>france</td>
<td>3</td>
<td>4</td>
<td>4</td>
<td>11</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>australia</td>
<td>3</td>
<td>4</td>
<td>0</td>
<td>7</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>norway</td>
<td>2</td>
<td>2</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>slovenia</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>5</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>finland</td>
<td>2</td>
<td>1</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>germany</td>
<td>2</td>
<td>1</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>russia</td>
<td>2</td>
<td>0</td>
<td>3</td>
<td>5</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>switzerland</td>
<td>1</td>
<td>5</td>
<td>5</td>
<td>11</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>china</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>poland</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>czech republic</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>belgium</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>netherlands</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>spain</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>bulgaria</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>20</th>
<td>20</td>
<td>great britain</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>21</th>
<td>20</td>
<td>sweden</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>22</th>
<td>total</td>
<td>total</td>
<td>52</td>
<td>52</td>
<td>52</td>
<td>156</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 nation = 'russia' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------|-------:|---------:|---------:|--------:|
| 0 | 1 | canada | 9 | 6 | 5 | 20 |
| 1 | 2 | united states | 8 | 7 | 8 | 23 |
| 2 | 3 | austria | 7 | 9 | 8 | 24 |
| 3 | 4 | japan | 4 | 2 | 1 | 7 |
| 4 | 5 | italy | 3 | 7 | 4 | 14 |
| 5 | 6 | france | 3 | 4 | 4 | 11 |
| 6 | 7 | australia | 3 | 4 | 0 | 7 |
| 7 | 8 | norway | 2 | 2 | 2 | 6 |
| 8 | 9 | slovenia | 2 | 1 | 2 | 5 |
| 9 | 10 | finland | 2 | 1 | 1 | 4 |
| 10 | 10 | germany | 2 | 1 | 1 | 4 |
| 11 | 12 | russia | 2 | 0 | 3 | 5 |
| 12 | 13 | switzerland | 1 | 5 | 5 | 11 |
| 13 | 14 | china | 1 | 1 | 1 | 3 |
| 14 | 15 | poland | 1 | 1 | 0 | 2 |
| 15 | 16 | czech republic | 1 | 0 | 1 | 2 |
| 16 | 17 | belgium | 1 | 0 | 0 | 1 |
| 17 | 18 | netherlands | 0 | 1 | 0 | 1 |
| 18 | 19 | spain | 0 | 0 | 3 | 3 |
| 19 | 20 | bulgaria | 0 | 0 | 1 | 1 |
| 20 | 20 | great britain | 0 | 0 | 1 | 1 |
| 21 | 20 | sweden | 0 | 0 | 1 | 1 |
| 22 | total | total | 52 | 52 | 52 | 156 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select party where party = 'russian social democratic party' order by party asc limit 1792 col : party | first duma | second duma | third duma | fourth duma row 1 : russian social democratic party | 18 (mensheviks) | 47 (mensheviks) | 19 (bolsheviks) | 15 (bolsheviks) row 2 : socialist-revolutionary party | none | 37 | none | none row 3 : labour group | 136 | 104 | 13 | 10 row 4 : progressist party | 27 | 28 | 28 | 41 row 5 : constitutional democratic party (kadets) | 179 | 92 | 52 | 57 row 6 : non-russian national groups | 121 | none | 26 | 21 row 7 : centre party | none | none | none | 33 row 8 : octobrist party | 17 | 42 | 154 | 95 row 9 : nationalists | 60 | 93 | 26 | 22 row 10 : rightists | 8 | 10 | 147 | 154 row 11 : total | 566 | 453 | 465 | 448 | col : party row 1 : russian social democratic party | select party where party = 'russian social democratic party' order by party asc limit 1792 <table_name> : table \begin{tabular}{llllll}
\toprule
& party & first duma & second duma & third duma & fourth duma \\
\midrule
0 & russian social democratic party & 18 (mensheviks) & 47 (mensheviks) & 19 (bolsheviks) & 15 (bolsheviks) \\
1 & socialist-revolutionary party & none & 37 & none & none \\
2 & labour group & 136 & 104 & 13 & 10 \\
3 & progressist party & 27 & 28 & 28 & 41 \\
4 & constitutional democratic party (kadets) & 179 & 92 & 52 & 57 \\
5 & non-russian national groups & 121 & none & 26 & 21 \\
6 & centre party & none & none & none & 33 \\
7 & octobrist party & 17 & 42 & 154 & 95 \\
8 & nationalists & 60 & 93 & 26 & 22 \\
9 & rightists & 8 & 10 & 147 & 154 \\
10 & total & 566 & 453 & 465 & 448 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& party \\
\midrule
0 & russian social democratic party \\
\bottomrule
\end{tabular}
| select party where party = 'russian social democratic party' order by party asc limit 1792 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
<th>first duma</th>
<th>second duma</th>
<th>third duma</th>
<th>fourth duma</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>russian social democratic party</td>
<td>18 (mensheviks)</td>
<td>47 (mensheviks)</td>
<td>19 (bolsheviks)</td>
<td>15 (bolsheviks)</td>
</tr>
<tr>
<th>1</th>
<td>socialist-revolutionary party</td>
<td>none</td>
<td>37</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>labour group</td>
<td>136</td>
<td>104</td>
<td>13</td>
<td>10</td>
</tr>
<tr>
<th>3</th>
<td>progressist party</td>
<td>27</td>
<td>28</td>
<td>28</td>
<td>41</td>
</tr>
<tr>
<th>4</th>
<td>constitutional democratic party (kadets)</td>
<td>179</td>
<td>92</td>
<td>52</td>
<td>57</td>
</tr>
<tr>
<th>5</th>
<td>non-russian national groups</td>
<td>121</td>
<td>none</td>
<td>26</td>
<td>21</td>
</tr>
<tr>
<th>6</th>
<td>centre party</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>33</td>
</tr>
<tr>
<th>7</th>
<td>octobrist party</td>
<td>17</td>
<td>42</td>
<td>154</td>
<td>95</td>
</tr>
<tr>
<th>8</th>
<td>nationalists</td>
<td>60</td>
<td>93</td>
<td>26</td>
<td>22</td>
</tr>
<tr>
<th>9</th>
<td>rightists</td>
<td>8</td>
<td>10</td>
<td>147</td>
<td>154</td>
</tr>
<tr>
<th>10</th>
<td>total</td>
<td>566</td>
<td>453</td>
<td>465</td>
<td>448</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>russian social democratic party</td>
</tr>
</tbody>
</table> | select party where party = 'russian social democratic party' order by party asc limit 1792 <table_name> : table | | party | first duma | second duma | third duma | fourth duma |
|---:|:-----------------------------------------|:----------------|:----------------|:----------------|:----------------|
| 0 | russian social democratic party | 18 (mensheviks) | 47 (mensheviks) | 19 (bolsheviks) | 15 (bolsheviks) |
| 1 | socialist-revolutionary party | none | 37 | none | none |
| 2 | labour group | 136 | 104 | 13 | 10 |
| 3 | progressist party | 27 | 28 | 28 | 41 |
| 4 | constitutional democratic party (kadets) | 179 | 92 | 52 | 57 |
| 5 | non-russian national groups | 121 | none | 26 | 21 |
| 6 | centre party | none | none | none | 33 |
| 7 | octobrist party | 17 | 42 | 154 | 95 |
| 8 | nationalists | 60 | 93 | 26 | 22 |
| 9 | rightists | 8 | 10 | 147 | 154 |
| 10 | total | 566 | 453 | 465 | 448 | | | | party |
|---:|:--------------------------------|
| 0 | russian social democratic party | | [
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select count ( second ) where events = 'none' col : season | skip | third | second | lead | events row 1 : 1995-96 | arnold asham | david nedohin | sean nedohin | don rudd | none row 2 : 1996-97 | dale duguid | james kirkness | david nedohin | doug armstrong | none row 3 : 1997-98 | david nedohin (fourth) | randy ferbey (skip) | carter rycroft | pat mccallum | none row 4 : 1998-99 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | carter rycroft | none row 5 : 2000-01 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2001 alta., brier, wcc row 6 : 2001-02 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2002 alta., brier, wcc row 7 : 2002-03 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2003 alta., brier, wcc row 8 : 2003-04 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2004 alta., brier row 9 : 2004-05 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2005 alta., brier, wcc row 10 : 2007-08 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2008 alta row 11 : 2008-09 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2009 alta row 12 : 2009-10 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2009 coct, 2010 alta row 13 : 2010-11 | randy ferbey | david nedohin | blayne iskiw | david harper | 2011 alta row 14 : 2011-12 | david nedohin (fourth) | randy ferbey (skip) | ted appelman | brendan melnyk | none row 15 : 2012-13 | david nedohin | colin hodgson | mike westlund | tom sallows | none row 16 : 2013-14 | kevin martin | david nedohin | marc kennedy | ben hebert | 2013 coct, 2014 alta | col : count ( "second" ) row 1 : 6 | select count ( second ) where events = 'none' <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & skip & third & second & lead & events \\
\midrule
0 & 1995-96 & arnold asham & david nedohin & sean nedohin & don rudd & none \\
1 & 1996-97 & dale duguid & james kirkness & david nedohin & doug armstrong & none \\
2 & 1997-98 & david nedohin (fourth) & randy ferbey (skip) & carter rycroft & pat mccallum & none \\
3 & 1998-99 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & carter rycroft & none \\
4 & 2000-01 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & marcel rocque & 2001 alta., brier, wcc \\
5 & 2001-02 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & marcel rocque & 2002 alta., brier, wcc \\
6 & 2002-03 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & marcel rocque & 2003 alta., brier, wcc \\
7 & 2003-04 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & marcel rocque & 2004 alta., brier \\
8 & 2004-05 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & marcel rocque & 2005 alta., brier, wcc \\
9 & 2007-08 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & marcel rocque & 2008 alta \\
10 & 2008-09 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & marcel rocque & 2009 alta \\
11 & 2009-10 & david nedohin (fourth) & randy ferbey (skip) & scott pfeifer & marcel rocque & 2009 coct, 2010 alta \\
12 & 2010-11 & randy ferbey & david nedohin & blayne iskiw & david harper & 2011 alta \\
13 & 2011-12 & david nedohin (fourth) & randy ferbey (skip) & ted appelman & brendan melnyk & none \\
14 & 2012-13 & david nedohin & colin hodgson & mike westlund & tom sallows & none \\
15 & 2013-14 & kevin martin & david nedohin & marc kennedy & ben hebert & 2013 coct, 2014 alta \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "second" ) \\
\midrule
0 & 6 \\
\bottomrule
\end{tabular}
| select count ( second ) where events = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>skip</th>
<th>third</th>
<th>second</th>
<th>lead</th>
<th>events</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1995-96</td>
<td>arnold asham</td>
<td>david nedohin</td>
<td>sean nedohin</td>
<td>don rudd</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1996-97</td>
<td>dale duguid</td>
<td>james kirkness</td>
<td>david nedohin</td>
<td>doug armstrong</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1997-98</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>carter rycroft</td>
<td>pat mccallum</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1998-99</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>carter rycroft</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2000-01</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>marcel rocque</td>
<td>2001 alta., brier, wcc</td>
</tr>
<tr>
<th>5</th>
<td>2001-02</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>marcel rocque</td>
<td>2002 alta., brier, wcc</td>
</tr>
<tr>
<th>6</th>
<td>2002-03</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>marcel rocque</td>
<td>2003 alta., brier, wcc</td>
</tr>
<tr>
<th>7</th>
<td>2003-04</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>marcel rocque</td>
<td>2004 alta., brier</td>
</tr>
<tr>
<th>8</th>
<td>2004-05</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>marcel rocque</td>
<td>2005 alta., brier, wcc</td>
</tr>
<tr>
<th>9</th>
<td>2007-08</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>marcel rocque</td>
<td>2008 alta</td>
</tr>
<tr>
<th>10</th>
<td>2008-09</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>marcel rocque</td>
<td>2009 alta</td>
</tr>
<tr>
<th>11</th>
<td>2009-10</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>scott pfeifer</td>
<td>marcel rocque</td>
<td>2009 coct, 2010 alta</td>
</tr>
<tr>
<th>12</th>
<td>2010-11</td>
<td>randy ferbey</td>
<td>david nedohin</td>
<td>blayne iskiw</td>
<td>david harper</td>
<td>2011 alta</td>
</tr>
<tr>
<th>13</th>
<td>2011-12</td>
<td>david nedohin (fourth)</td>
<td>randy ferbey (skip)</td>
<td>ted appelman</td>
<td>brendan melnyk</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>2012-13</td>
<td>david nedohin</td>
<td>colin hodgson</td>
<td>mike westlund</td>
<td>tom sallows</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>2013-14</td>
<td>kevin martin</td>
<td>david nedohin</td>
<td>marc kennedy</td>
<td>ben hebert</td>
<td>2013 coct, 2014 alta</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "second" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>6</td>
</tr>
</tbody>
</table> | select count ( second ) where events = 'none' <table_name> : table | | season | skip | third | second | lead | events |
|---:|:---------|:-----------------------|:--------------------|:---------------|:---------------|:-----------------------|
| 0 | 1995-96 | arnold asham | david nedohin | sean nedohin | don rudd | none |
| 1 | 1996-97 | dale duguid | james kirkness | david nedohin | doug armstrong | none |
| 2 | 1997-98 | david nedohin (fourth) | randy ferbey (skip) | carter rycroft | pat mccallum | none |
| 3 | 1998-99 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | carter rycroft | none |
| 4 | 2000-01 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2001 alta., brier, wcc |
| 5 | 2001-02 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2002 alta., brier, wcc |
| 6 | 2002-03 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2003 alta., brier, wcc |
| 7 | 2003-04 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2004 alta., brier |
| 8 | 2004-05 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2005 alta., brier, wcc |
| 9 | 2007-08 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2008 alta |
| 10 | 2008-09 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2009 alta |
| 11 | 2009-10 | david nedohin (fourth) | randy ferbey (skip) | scott pfeifer | marcel rocque | 2009 coct, 2010 alta |
| 12 | 2010-11 | randy ferbey | david nedohin | blayne iskiw | david harper | 2011 alta |
| 13 | 2011-12 | david nedohin (fourth) | randy ferbey (skip) | ted appelman | brendan melnyk | none |
| 14 | 2012-13 | david nedohin | colin hodgson | mike westlund | tom sallows | none |
| 15 | 2013-14 | kevin martin | david nedohin | marc kennedy | ben hebert | 2013 coct, 2014 alta | | | | count ( "second" ) |
|---:|---------------------:|
| 0 | 6 | | [
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select region where format = 'digital download' col : region | date | format | version(s) | label row 1 : france | 2012-09-04 00:00:00 | digital download | main single inferno remix bluelight remix | sony music row 2 : germany | 2012-09-04 00:00:00 | digital download | inferno remix | sony music row 3 : united states | 2012-09-04 00:00:00 | digital download | main single inferno remix bluelight remix | rca records row 4 : united states | 2012-09-11 00:00:00 | rhythmic airplay urban airplay | inferno remix | rca records row 5 : united states | 2012-09-11 00:00:00 | urban ac airplay | bluelight remix | rca records row 6 : united states | 2012-10-16 00:00:00 | mainstream airplay | main single inferno remix | rca records row 7 : united states | 2012-10-16 00:00:00 | hot adult contemporary airplay | main single | rca records row 8 : germany | 2012-11-02 00:00:00 | cd single | main single inferno remix | sony music row 9 : united kingdom | 2012-11-18 00:00:00 | digital ep | main single bluelight remix inferno remix instrumental | rca records row 10 : united states | 2013-03-18 00:00:00 | adult contemporary airplay | main single | rca records | col : region row 1 : france row 2 : germany row 3 : united states | select region where format = 'digital download' <table_name> : table \begin{tabular}{llllll}
\toprule
& region & date & format & version(s) & label \\
\midrule
0 & france & 2012-09-04 00:00:00 & digital download & main single inferno remix bluelight remix & sony music \\
1 & germany & 2012-09-04 00:00:00 & digital download & inferno remix & sony music \\
2 & united states & 2012-09-04 00:00:00 & digital download & main single inferno remix bluelight remix & rca records \\
3 & united states & 2012-09-11 00:00:00 & rhythmic airplay urban airplay & inferno remix & rca records \\
4 & united states & 2012-09-11 00:00:00 & urban ac airplay & bluelight remix & rca records \\
5 & united states & 2012-10-16 00:00:00 & mainstream airplay & main single inferno remix & rca records \\
6 & united states & 2012-10-16 00:00:00 & hot adult contemporary airplay & main single & rca records \\
7 & germany & 2012-11-02 00:00:00 & cd single & main single inferno remix & sony music \\
8 & united kingdom & 2012-11-18 00:00:00 & digital ep & main single bluelight remix inferno remix instrumental & rca records \\
9 & united states & 2013-03-18 00:00:00 & adult contemporary airplay & main single & rca records \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& region \\
\midrule
0 & france \\
1 & germany \\
2 & united states \\
\bottomrule
\end{tabular}
| select region where format = 'digital download' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>region</th>
<th>date</th>
<th>format</th>
<th>version(s)</th>
<th>label</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>france</td>
<td>2012-09-04 00:00:00</td>
<td>digital download</td>
<td>main single inferno remix bluelight remix</td>
<td>sony music</td>
</tr>
<tr>
<th>1</th>
<td>germany</td>
<td>2012-09-04 00:00:00</td>
<td>digital download</td>
<td>inferno remix</td>
<td>sony music</td>
</tr>
<tr>
<th>2</th>
<td>united states</td>
<td>2012-09-04 00:00:00</td>
<td>digital download</td>
<td>main single inferno remix bluelight remix</td>
<td>rca records</td>
</tr>
<tr>
<th>3</th>
<td>united states</td>
<td>2012-09-11 00:00:00</td>
<td>rhythmic airplay urban airplay</td>
<td>inferno remix</td>
<td>rca records</td>
</tr>
<tr>
<th>4</th>
<td>united states</td>
<td>2012-09-11 00:00:00</td>
<td>urban ac airplay</td>
<td>bluelight remix</td>
<td>rca records</td>
</tr>
<tr>
<th>5</th>
<td>united states</td>
<td>2012-10-16 00:00:00</td>
<td>mainstream airplay</td>
<td>main single inferno remix</td>
<td>rca records</td>
</tr>
<tr>
<th>6</th>
<td>united states</td>
<td>2012-10-16 00:00:00</td>
<td>hot adult contemporary airplay</td>
<td>main single</td>
<td>rca records</td>
</tr>
<tr>
<th>7</th>
<td>germany</td>
<td>2012-11-02 00:00:00</td>
<td>cd single</td>
<td>main single inferno remix</td>
<td>sony music</td>
</tr>
<tr>
<th>8</th>
<td>united kingdom</td>
<td>2012-11-18 00:00:00</td>
<td>digital ep</td>
<td>main single bluelight remix inferno remix instrumental</td>
<td>rca records</td>
</tr>
<tr>
<th>9</th>
<td>united states</td>
<td>2013-03-18 00:00:00</td>
<td>adult contemporary airplay</td>
<td>main single</td>
<td>rca records</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>region</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>france</td>
</tr>
<tr>
<th>1</th>
<td>germany</td>
</tr>
<tr>
<th>2</th>
<td>united states</td>
</tr>
</tbody>
</table> | select region where format = 'digital download' <table_name> : table | | region | date | format | version(s) | label |
|---:|:---------------|:--------------------|:-------------------------------|:-------------------------------------------------------|:------------|
| 0 | france | 2012-09-04 00:00:00 | digital download | main single inferno remix bluelight remix | sony music |
| 1 | germany | 2012-09-04 00:00:00 | digital download | inferno remix | sony music |
| 2 | united states | 2012-09-04 00:00:00 | digital download | main single inferno remix bluelight remix | rca records |
| 3 | united states | 2012-09-11 00:00:00 | rhythmic airplay urban airplay | inferno remix | rca records |
| 4 | united states | 2012-09-11 00:00:00 | urban ac airplay | bluelight remix | rca records |
| 5 | united states | 2012-10-16 00:00:00 | mainstream airplay | main single inferno remix | rca records |
| 6 | united states | 2012-10-16 00:00:00 | hot adult contemporary airplay | main single | rca records |
| 7 | germany | 2012-11-02 00:00:00 | cd single | main single inferno remix | sony music |
| 8 | united kingdom | 2012-11-18 00:00:00 | digital ep | main single bluelight remix inferno remix instrumental | rca records |
| 9 | united states | 2013-03-18 00:00:00 | adult contemporary airplay | main single | rca records | | | | region |
|---:|:--------------|
| 0 | france |
| 1 | germany |
| 2 | united states | | [
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select count ( other ) where other = 'red with shimmering silver glitter' col : primary | other row 1 : black with glitzy gold glitter | black with glitzy gold glitter row 2 : #000000 | #e7c697 row 3 : blue green with glitzy gold glitter | blue green with glitzy gold glitter row 4 : #0d98ba | #e7c697 row 5 : green with twinkling turquoise glitter | green with twinkling turquoise glitter row 6 : #1cac78 | #77dde7 row 7 : orange with twinkling turquoise glitter | orange with twinkling turquoise glitter row 8 : #ff7538 | #77dde7 row 9 : red with shimmering silver glitter | red with shimmering silver glitter row 10 : #ee204d | #cdc5c2 row 11 : royal purple with ruby red glitter | royal purple with ruby red glitter row 12 : #7851a9 | #ee204d row 13 : white with confetti glitter | white with confetti glitter row 14 : #ffffff | various row 15 : yellow with rainbow glitter | yellow with rainbow glitter row 16 : #fce883 | various row 17 : blue with shimmering silver glitter | blue with shimmering silver glitter row 18 : #1f75fe | #cdc5c2 row 19 : carnation pink with lavender glitter | carnation pink with lavender glitter row 20 : #ffaacc | #fcb4d5 row 21 : maroon with glitzy gold glitter | maroon with glitzy gold glitter row 22 : #c8385a | #e7c697 row 23 : orchid with twinkling turquoise glitter | orchid with twinkling turquoise glitter row 24 : #e6a8d7 | #77dde7 row 25 : red violet with glitzy gold glitter | red violet with glitzy gold glitter row 26 : #c0448f | #e7c697 row 27 : sky blue with glitzy gold glitter | sky blue with glitzy gold glitter row 28 : #80daeb | #e7c697 row 29 : white with glitzy gold glitter | white with glitzy gold glitter row 30 : #ffffff | #e7c697 row 31 : yellow green with silver glitter | yellow green with silver glitter row 32 : #c5e384 | #cdc5c2 | col : count ( "other" ) row 1 : 1 | select count ( other ) where other = 'red with shimmering silver glitter' <table_name> : table \begin{tabular}{lll}
\toprule
& primary & other \\
\midrule
0 & black with glitzy gold glitter & black with glitzy gold glitter \\
1 & #000000 & #e7c697 \\
2 & blue green with glitzy gold glitter & blue green with glitzy gold glitter \\
3 & #0d98ba & #e7c697 \\
4 & green with twinkling turquoise glitter & green with twinkling turquoise glitter \\
5 & #1cac78 & #77dde7 \\
6 & orange with twinkling turquoise glitter & orange with twinkling turquoise glitter \\
7 & #ff7538 & #77dde7 \\
8 & red with shimmering silver glitter & red with shimmering silver glitter \\
9 & #ee204d & #cdc5c2 \\
10 & royal purple with ruby red glitter & royal purple with ruby red glitter \\
11 & #7851a9 & #ee204d \\
12 & white with confetti glitter & white with confetti glitter \\
13 & #ffffff & various \\
14 & yellow with rainbow glitter & yellow with rainbow glitter \\
15 & #fce883 & various \\
16 & blue with shimmering silver glitter & blue with shimmering silver glitter \\
17 & #1f75fe & #cdc5c2 \\
18 & carnation pink with lavender glitter & carnation pink with lavender glitter \\
19 & #ffaacc & #fcb4d5 \\
20 & maroon with glitzy gold glitter & maroon with glitzy gold glitter \\
21 & #c8385a & #e7c697 \\
22 & orchid with twinkling turquoise glitter & orchid with twinkling turquoise glitter \\
23 & #e6a8d7 & #77dde7 \\
24 & red violet with glitzy gold glitter & red violet with glitzy gold glitter \\
25 & #c0448f & #e7c697 \\
26 & sky blue with glitzy gold glitter & sky blue with glitzy gold glitter \\
27 & #80daeb & #e7c697 \\
28 & white with glitzy gold glitter & white with glitzy gold glitter \\
29 & #ffffff & #e7c697 \\
30 & yellow green with silver glitter & yellow green with silver glitter \\
31 & #c5e384 & #cdc5c2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "other" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( other ) where other = 'red with shimmering silver glitter' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>primary</th>
<th>other</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>black with glitzy gold glitter</td>
<td>black with glitzy gold glitter</td>
</tr>
<tr>
<th>1</th>
<td>#000000</td>
<td>#e7c697</td>
</tr>
<tr>
<th>2</th>
<td>blue green with glitzy gold glitter</td>
<td>blue green with glitzy gold glitter</td>
</tr>
<tr>
<th>3</th>
<td>#0d98ba</td>
<td>#e7c697</td>
</tr>
<tr>
<th>4</th>
<td>green with twinkling turquoise glitter</td>
<td>green with twinkling turquoise glitter</td>
</tr>
<tr>
<th>5</th>
<td>#1cac78</td>
<td>#77dde7</td>
</tr>
<tr>
<th>6</th>
<td>orange with twinkling turquoise glitter</td>
<td>orange with twinkling turquoise glitter</td>
</tr>
<tr>
<th>7</th>
<td>#ff7538</td>
<td>#77dde7</td>
</tr>
<tr>
<th>8</th>
<td>red with shimmering silver glitter</td>
<td>red with shimmering silver glitter</td>
</tr>
<tr>
<th>9</th>
<td>#ee204d</td>
<td>#cdc5c2</td>
</tr>
<tr>
<th>10</th>
<td>royal purple with ruby red glitter</td>
<td>royal purple with ruby red glitter</td>
</tr>
<tr>
<th>11</th>
<td>#7851a9</td>
<td>#ee204d</td>
</tr>
<tr>
<th>12</th>
<td>white with confetti glitter</td>
<td>white with confetti glitter</td>
</tr>
<tr>
<th>13</th>
<td>#ffffff</td>
<td>various</td>
</tr>
<tr>
<th>14</th>
<td>yellow with rainbow glitter</td>
<td>yellow with rainbow glitter</td>
</tr>
<tr>
<th>15</th>
<td>#fce883</td>
<td>various</td>
</tr>
<tr>
<th>16</th>
<td>blue with shimmering silver glitter</td>
<td>blue with shimmering silver glitter</td>
</tr>
<tr>
<th>17</th>
<td>#1f75fe</td>
<td>#cdc5c2</td>
</tr>
<tr>
<th>18</th>
<td>carnation pink with lavender glitter</td>
<td>carnation pink with lavender glitter</td>
</tr>
<tr>
<th>19</th>
<td>#ffaacc</td>
<td>#fcb4d5</td>
</tr>
<tr>
<th>20</th>
<td>maroon with glitzy gold glitter</td>
<td>maroon with glitzy gold glitter</td>
</tr>
<tr>
<th>21</th>
<td>#c8385a</td>
<td>#e7c697</td>
</tr>
<tr>
<th>22</th>
<td>orchid with twinkling turquoise glitter</td>
<td>orchid with twinkling turquoise glitter</td>
</tr>
<tr>
<th>23</th>
<td>#e6a8d7</td>
<td>#77dde7</td>
</tr>
<tr>
<th>24</th>
<td>red violet with glitzy gold glitter</td>
<td>red violet with glitzy gold glitter</td>
</tr>
<tr>
<th>25</th>
<td>#c0448f</td>
<td>#e7c697</td>
</tr>
<tr>
<th>26</th>
<td>sky blue with glitzy gold glitter</td>
<td>sky blue with glitzy gold glitter</td>
</tr>
<tr>
<th>27</th>
<td>#80daeb</td>
<td>#e7c697</td>
</tr>
<tr>
<th>28</th>
<td>white with glitzy gold glitter</td>
<td>white with glitzy gold glitter</td>
</tr>
<tr>
<th>29</th>
<td>#ffffff</td>
<td>#e7c697</td>
</tr>
<tr>
<th>30</th>
<td>yellow green with silver glitter</td>
<td>yellow green with silver glitter</td>
</tr>
<tr>
<th>31</th>
<td>#c5e384</td>
<td>#cdc5c2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "other" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( other ) where other = 'red with shimmering silver glitter' <table_name> : table | | primary | other |
|---:|:----------------------------------------|:----------------------------------------|
| 0 | black with glitzy gold glitter | black with glitzy gold glitter |
| 1 | #000000 | #e7c697 |
| 2 | blue green with glitzy gold glitter | blue green with glitzy gold glitter |
| 3 | #0d98ba | #e7c697 |
| 4 | green with twinkling turquoise glitter | green with twinkling turquoise glitter |
| 5 | #1cac78 | #77dde7 |
| 6 | orange with twinkling turquoise glitter | orange with twinkling turquoise glitter |
| 7 | #ff7538 | #77dde7 |
| 8 | red with shimmering silver glitter | red with shimmering silver glitter |
| 9 | #ee204d | #cdc5c2 |
| 10 | royal purple with ruby red glitter | royal purple with ruby red glitter |
| 11 | #7851a9 | #ee204d |
| 12 | white with confetti glitter | white with confetti glitter |
| 13 | #ffffff | various |
| 14 | yellow with rainbow glitter | yellow with rainbow glitter |
| 15 | #fce883 | various |
| 16 | blue with shimmering silver glitter | blue with shimmering silver glitter |
| 17 | #1f75fe | #cdc5c2 |
| 18 | carnation pink with lavender glitter | carnation pink with lavender glitter |
| 19 | #ffaacc | #fcb4d5 |
| 20 | maroon with glitzy gold glitter | maroon with glitzy gold glitter |
| 21 | #c8385a | #e7c697 |
| 22 | orchid with twinkling turquoise glitter | orchid with twinkling turquoise glitter |
| 23 | #e6a8d7 | #77dde7 |
| 24 | red violet with glitzy gold glitter | red violet with glitzy gold glitter |
| 25 | #c0448f | #e7c697 |
| 26 | sky blue with glitzy gold glitter | sky blue with glitzy gold glitter |
| 27 | #80daeb | #e7c697 |
| 28 | white with glitzy gold glitter | white with glitzy gold glitter |
| 29 | #ffffff | #e7c697 |
| 30 | yellow green with silver glitter | yellow green with silver glitter |
| 31 | #c5e384 | #cdc5c2 | | | | count ( "other" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select count ( award ) where year = 1999 col : year | award | category | title | result row 1 : 1955 | academy award | best actor | marty | won row 2 : 1955 | bafta award | best foreign actor | marty | won row 3 : 1955 | golden globe award | best actor - motion picture drama | marty | won row 4 : 1955 | nbr award | best actor | marty | won row 5 : 1955 | nyfcc award | best actor | marty | won row 6 : 1962 | emmy award | outstanding continued performance by an actor in a series (lead) | mchale's navy | nominated row 7 : 1979 | emmy award | outstanding supporting actor in a limited series or a special | all quiet on the western front | nominated row 8 : 1999 | daytime emmy award | outstanding performer in an animated program | all dogs go to heaven: the series | nominated row 9 : 2007 | golden globe award | best performance by an actor in a mini-series or a motion picture made for television | a grandpa for christmas | nominated row 10 : 2009 | emmy award | outstanding guest actor - drama | er | nominated row 11 : 2009 | lifetime achievement award | from the rhode island international film festival | none | won row 12 : 2011 | screen actors guild life achievement award | from the screen actors guild | none | won | col : count ( "award" ) row 1 : 1 | select count ( award ) where year = 1999 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & award & category & title & result \\
\midrule
0 & 1955 & academy award & best actor & marty & won \\
1 & 1955 & bafta award & best foreign actor & marty & won \\
2 & 1955 & golden globe award & best actor - motion picture drama & marty & won \\
3 & 1955 & nbr award & best actor & marty & won \\
4 & 1955 & nyfcc award & best actor & marty & won \\
5 & 1962 & emmy award & outstanding continued performance by an actor in a series (lead) & mchale's navy & nominated \\
6 & 1979 & emmy award & outstanding supporting actor in a limited series or a special & all quiet on the western front & nominated \\
7 & 1999 & daytime emmy award & outstanding performer in an animated program & all dogs go to heaven: the series & nominated \\
8 & 2007 & golden globe award & best performance by an actor in a mini-series or a motion picture made for television & a grandpa for christmas & nominated \\
9 & 2009 & emmy award & outstanding guest actor - drama & er & nominated \\
10 & 2009 & lifetime achievement award & from the rhode island international film festival & none & won \\
11 & 2011 & screen actors guild life achievement award & from the screen actors guild & none & won \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "award" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( award ) where year = 1999 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>award</th>
<th>category</th>
<th>title</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1955</td>
<td>academy award</td>
<td>best actor</td>
<td>marty</td>
<td>won</td>
</tr>
<tr>
<th>1</th>
<td>1955</td>
<td>bafta award</td>
<td>best foreign actor</td>
<td>marty</td>
<td>won</td>
</tr>
<tr>
<th>2</th>
<td>1955</td>
<td>golden globe award</td>
<td>best actor - motion picture drama</td>
<td>marty</td>
<td>won</td>
</tr>
<tr>
<th>3</th>
<td>1955</td>
<td>nbr award</td>
<td>best actor</td>
<td>marty</td>
<td>won</td>
</tr>
<tr>
<th>4</th>
<td>1955</td>
<td>nyfcc award</td>
<td>best actor</td>
<td>marty</td>
<td>won</td>
</tr>
<tr>
<th>5</th>
<td>1962</td>
<td>emmy award</td>
<td>outstanding continued performance by an actor in a series (lead)</td>
<td>mchale's navy</td>
<td>nominated</td>
</tr>
<tr>
<th>6</th>
<td>1979</td>
<td>emmy award</td>
<td>outstanding supporting actor in a limited series or a special</td>
<td>all quiet on the western front</td>
<td>nominated</td>
</tr>
<tr>
<th>7</th>
<td>1999</td>
<td>daytime emmy award</td>
<td>outstanding performer in an animated program</td>
<td>all dogs go to heaven: the series</td>
<td>nominated</td>
</tr>
<tr>
<th>8</th>
<td>2007</td>
<td>golden globe award</td>
<td>best performance by an actor in a mini-series or a motion picture made for television</td>
<td>a grandpa for christmas</td>
<td>nominated</td>
</tr>
<tr>
<th>9</th>
<td>2009</td>
<td>emmy award</td>
<td>outstanding guest actor - drama</td>
<td>er</td>
<td>nominated</td>
</tr>
<tr>
<th>10</th>
<td>2009</td>
<td>lifetime achievement award</td>
<td>from the rhode island international film festival</td>
<td>none</td>
<td>won</td>
</tr>
<tr>
<th>11</th>
<td>2011</td>
<td>screen actors guild life achievement award</td>
<td>from the screen actors guild</td>
<td>none</td>
<td>won</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "award" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( award ) where year = 1999 <table_name> : table | | year | award | category | title | result |
|---:|-------:|:-------------------------------------------|:--------------------------------------------------------------------------------------|:----------------------------------|:----------|
| 0 | 1955 | academy award | best actor | marty | won |
| 1 | 1955 | bafta award | best foreign actor | marty | won |
| 2 | 1955 | golden globe award | best actor - motion picture drama | marty | won |
| 3 | 1955 | nbr award | best actor | marty | won |
| 4 | 1955 | nyfcc award | best actor | marty | won |
| 5 | 1962 | emmy award | outstanding continued performance by an actor in a series (lead) | mchale's navy | nominated |
| 6 | 1979 | emmy award | outstanding supporting actor in a limited series or a special | all quiet on the western front | nominated |
| 7 | 1999 | daytime emmy award | outstanding performer in an animated program | all dogs go to heaven: the series | nominated |
| 8 | 2007 | golden globe award | best performance by an actor in a mini-series or a motion picture made for television | a grandpa for christmas | nominated |
| 9 | 2009 | emmy award | outstanding guest actor - drama | er | nominated |
| 10 | 2009 | lifetime achievement award | from the rhode island international film festival | none | won |
| 11 | 2011 | screen actors guild life achievement award | from the screen actors guild | none | won | | | | count ( "award" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select count ( game site ) where tv time > 1519 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 ( "game site" ) row 1 : 17 | select count ( game site ) where tv time > 1519 <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 ( "game site" ) \\
\midrule
0 & 17 \\
\bottomrule
\end{tabular}
| select count ( game site ) where tv time > 1519 <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 ( "game site" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>17</td>
</tr>
</tbody>
</table> | select count ( game site ) where tv time > 1519 <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 ( "game site" ) |
|---:|------------------------:|
| 0 | 17 | | [
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select region where region = 'west skane' order by region desc limit 1 col : region | population | area | density row 1 : danish capital region | 1823109 | 2,864 km2 | 636.5/km2 row 2 : remainder | 608036 | 6,970 km2 | 87.2/km2 row 3 : total for danish part: | 2431145 | 9,834 km2 | 247.2/km2 row 4 : south skane | 683886 | 2,680 km2 | 255.1/km2 row 5 : west skane | 305982 | 2,730 km2 | 112.1/km2 row 6 : north-east skane | 162829 | 3,705 km2 | 43.9/km2 row 7 : total for swedish part: | 1125697 | 11,035 km2 | 102.0/km2 row 8 : grand total | 3583842 | 20,869 km2 | 171.7/km2 | col : region row 1 : west skane | select region where region = 'west skane' order by region desc limit 1 <table_name> : table \begin{tabular}{lllll}
\toprule
& region & population & area & density \\
\midrule
0 & danish capital region & 1823109 & 2,864 km2 & 636.5/km2 \\
1 & remainder & 608036 & 6,970 km2 & 87.2/km2 \\
2 & total for danish part: & 2431145 & 9,834 km2 & 247.2/km2 \\
3 & south skane & 683886 & 2,680 km2 & 255.1/km2 \\
4 & west skane & 305982 & 2,730 km2 & 112.1/km2 \\
5 & north-east skane & 162829 & 3,705 km2 & 43.9/km2 \\
6 & total for swedish part: & 1125697 & 11,035 km2 & 102.0/km2 \\
7 & grand total & 3583842 & 20,869 km2 & 171.7/km2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& region \\
\midrule
0 & west skane \\
\bottomrule
\end{tabular}
| select region where region = 'west skane' order by region desc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>region</th>
<th>population</th>
<th>area</th>
<th>density</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>danish capital region</td>
<td>1823109</td>
<td>2,864 km2</td>
<td>636.5/km2</td>
</tr>
<tr>
<th>1</th>
<td>remainder</td>
<td>608036</td>
<td>6,970 km2</td>
<td>87.2/km2</td>
</tr>
<tr>
<th>2</th>
<td>total for danish part:</td>
<td>2431145</td>
<td>9,834 km2</td>
<td>247.2/km2</td>
</tr>
<tr>
<th>3</th>
<td>south skane</td>
<td>683886</td>
<td>2,680 km2</td>
<td>255.1/km2</td>
</tr>
<tr>
<th>4</th>
<td>west skane</td>
<td>305982</td>
<td>2,730 km2</td>
<td>112.1/km2</td>
</tr>
<tr>
<th>5</th>
<td>north-east skane</td>
<td>162829</td>
<td>3,705 km2</td>
<td>43.9/km2</td>
</tr>
<tr>
<th>6</th>
<td>total for swedish part:</td>
<td>1125697</td>
<td>11,035 km2</td>
<td>102.0/km2</td>
</tr>
<tr>
<th>7</th>
<td>grand total</td>
<td>3583842</td>
<td>20,869 km2</td>
<td>171.7/km2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>region</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>west skane</td>
</tr>
</tbody>
</table> | select region where region = 'west skane' order by region desc limit 1 <table_name> : table | | region | population | area | density |
|---:|:------------------------|-------------:|:-----------|:----------|
| 0 | danish capital region | 1823109 | 2,864 km2 | 636.5/km2 |
| 1 | remainder | 608036 | 6,970 km2 | 87.2/km2 |
| 2 | total for danish part: | 2431145 | 9,834 km2 | 247.2/km2 |
| 3 | south skane | 683886 | 2,680 km2 | 255.1/km2 |
| 4 | west skane | 305982 | 2,730 km2 | 112.1/km2 |
| 5 | north-east skane | 162829 | 3,705 km2 | 43.9/km2 |
| 6 | total for swedish part: | 1125697 | 11,035 km2 | 102.0/km2 |
| 7 | grand total | 3583842 | 20,869 km2 | 171.7/km2 | | | | region |
|---:|:-----------|
| 0 | west skane | | [
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] |
select count ( * ) where from = 1750 col : date | position | name | from | fee row 1 : 2001-07-05 00:00:00 | mf | andy hughes | notts county | £250,000 by a tribunal row 2 : 2001-07-05 00:00:00 | df | adrian whitbread | portsmouth | free row 3 : 2001-07-18 00:00:00 | df | alex smith | port vale | free row 4 : 2001-11-30 00:00:00 | gk | antony malessa | oxford united | free row 5 : 2002-01-28 00:00:00 | mf | john salako | charlton athletic | £50,000 row 6 : 2002-03-13 00:00:00 | gk | frank talia | sheffield united | free row 7 : 2002-03-15 00:00:00 | mf | kevin watson | charlton athletic | £150,000 | col : count ( "*" ) row 1 : 0 | select count ( * ) where from = 1750 <table_name> : table \begin{tabular}{llllll}
\toprule
& date & position & name & from & fee \\
\midrule
0 & 2001-07-05 00:00:00 & mf & andy hughes & notts county & £250,000 by a tribunal \\
1 & 2001-07-05 00:00:00 & df & adrian whitbread & portsmouth & free \\
2 & 2001-07-18 00:00:00 & df & alex smith & port vale & free \\
3 & 2001-11-30 00:00:00 & gk & antony malessa & oxford united & free \\
4 & 2002-01-28 00:00:00 & mf & john salako & charlton athletic & £50,000 \\
5 & 2002-03-13 00:00:00 & gk & frank talia & sheffield united & free \\
6 & 2002-03-15 00:00:00 & mf & kevin watson & charlton athletic & £150,000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where from = 1750 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>position</th>
<th>name</th>
<th>from</th>
<th>fee</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2001-07-05 00:00:00</td>
<td>mf</td>
<td>andy hughes</td>
<td>notts county</td>
<td>£250,000 by a tribunal</td>
</tr>
<tr>
<th>1</th>
<td>2001-07-05 00:00:00</td>
<td>df</td>
<td>adrian whitbread</td>
<td>portsmouth</td>
<td>free</td>
</tr>
<tr>
<th>2</th>
<td>2001-07-18 00:00:00</td>
<td>df</td>
<td>alex smith</td>
<td>port vale</td>
<td>free</td>
</tr>
<tr>
<th>3</th>
<td>2001-11-30 00:00:00</td>
<td>gk</td>
<td>antony malessa</td>
<td>oxford united</td>
<td>free</td>
</tr>
<tr>
<th>4</th>
<td>2002-01-28 00:00:00</td>
<td>mf</td>
<td>john salako</td>
<td>charlton athletic</td>
<td>£50,000</td>
</tr>
<tr>
<th>5</th>
<td>2002-03-13 00:00:00</td>
<td>gk</td>
<td>frank talia</td>
<td>sheffield united</td>
<td>free</td>
</tr>
<tr>
<th>6</th>
<td>2002-03-15 00:00:00</td>
<td>mf</td>
<td>kevin watson</td>
<td>charlton athletic</td>
<td>£150,000</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 from = 1750 <table_name> : table | | date | position | name | from | fee |
|---:|:--------------------|:-----------|:-----------------|:------------------|:-----------------------|
| 0 | 2001-07-05 00:00:00 | mf | andy hughes | notts county | £250,000 by a tribunal |
| 1 | 2001-07-05 00:00:00 | df | adrian whitbread | portsmouth | free |
| 2 | 2001-07-18 00:00:00 | df | alex smith | port vale | free |
| 3 | 2001-11-30 00:00:00 | gk | antony malessa | oxford united | free |
| 4 | 2002-01-28 00:00:00 | mf | john salako | charlton athletic | £50,000 |
| 5 | 2002-03-13 00:00:00 | gk | frank talia | sheffield united | free |
| 6 | 2002-03-15 00:00:00 | mf | kevin watson | charlton athletic | £150,000 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( * ) where institution = 'yale university' col : institution | location | athletic nickname | undergraduate enrollment | graduate enrollment | total enrollment | 2013 endowment (and us rank) | academic staff | motto row 1 : brown university | providence, rhode island | bears | 6316 | 2333 | 8649 | $2.7 billion (30th) | 736 | in deo speramus (in god we hope) row 2 : columbia university | new york, new york | lions | 7160 | 15760 | 22920 | $8.2 billion (9th) | 3763 | in lumine tuo videbimus lumen (in thy light shall we see the light) row 3 : cornell university | ithaca, new york | big red | 13931 | 6702 | 20633 | $5.3 billion (18th) | 2908 | i would found an institution where any person can find instruction in any study row 4 : dartmouth college | hanover, new hampshire | big green | 4248 | 1893 | 6141 | $3.7 billion (22nd) | 571 | vox clamantis in deserto (the voice of one crying in the wilderness) row 5 : harvard university | cambridge, massachusetts | crimson | 7181 | 14044 | 21225 | $32.3 billion (1st) | 4671 | veritas (truth) row 6 : princeton university | princeton, new jersey | tigers | 5113 | 2479 | 7592 | $18.2 billion (5th) | 1172 | dei sub numine viget (under god's power she flourishes) row 7 : university of pennsylvania | philadelphia, pennsylvania | quakers | 10337 | 10306 | 20643 | $7.7 billion (11th) | 4464 | leges sine moribus vanae (laws without morals are useless) row 8 : yale university | new haven, connecticut | bulldogs | 5275 | 6391 | 11666 | $20.8 billion (2nd) | 4140 | אורים ותומים lux et veritas (light and truth) | col : count ( "*" ) row 1 : 1 | select count ( * ) where institution = 'yale university' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& institution & location & athletic nickname & undergraduate enrollment & graduate enrollment & total enrollment & 2013 endowment (and us rank) & academic staff & motto \\
\midrule
0 & brown university & providence, rhode island & bears & 6316 & 2333 & 8649 & $2.7 billion (30th) & 736 & in deo speramus (in god we hope) \\
1 & columbia university & new york, new york & lions & 7160 & 15760 & 22920 & $8.2 billion (9th) & 3763 & in lumine tuo videbimus lumen (in thy light shall we see the light) \\
2 & cornell university & ithaca, new york & big red & 13931 & 6702 & 20633 & $5.3 billion (18th) & 2908 & i would found an institution where any person can find instruction in any study \\
3 & dartmouth college & hanover, new hampshire & big green & 4248 & 1893 & 6141 & $3.7 billion (22nd) & 571 & vox clamantis in deserto (the voice of one crying in the wilderness) \\
4 & harvard university & cambridge, massachusetts & crimson & 7181 & 14044 & 21225 & $32.3 billion (1st) & 4671 & veritas (truth) \\
5 & princeton university & princeton, new jersey & tigers & 5113 & 2479 & 7592 & $18.2 billion (5th) & 1172 & dei sub numine viget (under god's power she flourishes) \\
6 & university of pennsylvania & philadelphia, pennsylvania & quakers & 10337 & 10306 & 20643 & $7.7 billion (11th) & 4464 & leges sine moribus vanae (laws without morals are useless) \\
7 & yale university & new haven, connecticut & bulldogs & 5275 & 6391 & 11666 & $20.8 billion (2nd) & 4140 & אורים ותומים lux et veritas (light and truth) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where institution = 'yale university' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>institution</th>
<th>location</th>
<th>athletic nickname</th>
<th>undergraduate enrollment</th>
<th>graduate enrollment</th>
<th>total enrollment</th>
<th>2013 endowment (and us rank)</th>
<th>academic staff</th>
<th>motto</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>brown university</td>
<td>providence, rhode island</td>
<td>bears</td>
<td>6316</td>
<td>2333</td>
<td>8649</td>
<td>$2.7 billion (30th)</td>
<td>736</td>
<td>in deo speramus (in god we hope)</td>
</tr>
<tr>
<th>1</th>
<td>columbia university</td>
<td>new york, new york</td>
<td>lions</td>
<td>7160</td>
<td>15760</td>
<td>22920</td>
<td>$8.2 billion (9th)</td>
<td>3763</td>
<td>in lumine tuo videbimus lumen (in thy light shall we see the light)</td>
</tr>
<tr>
<th>2</th>
<td>cornell university</td>
<td>ithaca, new york</td>
<td>big red</td>
<td>13931</td>
<td>6702</td>
<td>20633</td>
<td>$5.3 billion (18th)</td>
<td>2908</td>
<td>i would found an institution where any person can find instruction in any study</td>
</tr>
<tr>
<th>3</th>
<td>dartmouth college</td>
<td>hanover, new hampshire</td>
<td>big green</td>
<td>4248</td>
<td>1893</td>
<td>6141</td>
<td>$3.7 billion (22nd)</td>
<td>571</td>
<td>vox clamantis in deserto (the voice of one crying in the wilderness)</td>
</tr>
<tr>
<th>4</th>
<td>harvard university</td>
<td>cambridge, massachusetts</td>
<td>crimson</td>
<td>7181</td>
<td>14044</td>
<td>21225</td>
<td>$32.3 billion (1st)</td>
<td>4671</td>
<td>veritas (truth)</td>
</tr>
<tr>
<th>5</th>
<td>princeton university</td>
<td>princeton, new jersey</td>
<td>tigers</td>
<td>5113</td>
<td>2479</td>
<td>7592</td>
<td>$18.2 billion (5th)</td>
<td>1172</td>
<td>dei sub numine viget (under god's power she flourishes)</td>
</tr>
<tr>
<th>6</th>
<td>university of pennsylvania</td>
<td>philadelphia, pennsylvania</td>
<td>quakers</td>
<td>10337</td>
<td>10306</td>
<td>20643</td>
<td>$7.7 billion (11th)</td>
<td>4464</td>
<td>leges sine moribus vanae (laws without morals are useless)</td>
</tr>
<tr>
<th>7</th>
<td>yale university</td>
<td>new haven, connecticut</td>
<td>bulldogs</td>
<td>5275</td>
<td>6391</td>
<td>11666</td>
<td>$20.8 billion (2nd)</td>
<td>4140</td>
<td>אורים ותומים lux et veritas (light and truth)</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 institution = 'yale university' <table_name> : table | | institution | location | athletic nickname | undergraduate enrollment | graduate enrollment | total enrollment | 2013 endowment (and us rank) | academic staff | motto |
|---:|:---------------------------|:---------------------------|:--------------------|---------------------------:|----------------------:|-------------------:|:-------------------------------|-----------------:|:--------------------------------------------------------------------------------|
| 0 | brown university | providence, rhode island | bears | 6316 | 2333 | 8649 | $2.7 billion (30th) | 736 | in deo speramus (in god we hope) |
| 1 | columbia university | new york, new york | lions | 7160 | 15760 | 22920 | $8.2 billion (9th) | 3763 | in lumine tuo videbimus lumen (in thy light shall we see the light) |
| 2 | cornell university | ithaca, new york | big red | 13931 | 6702 | 20633 | $5.3 billion (18th) | 2908 | i would found an institution where any person can find instruction in any study |
| 3 | dartmouth college | hanover, new hampshire | big green | 4248 | 1893 | 6141 | $3.7 billion (22nd) | 571 | vox clamantis in deserto (the voice of one crying in the wilderness) |
| 4 | harvard university | cambridge, massachusetts | crimson | 7181 | 14044 | 21225 | $32.3 billion (1st) | 4671 | veritas (truth) |
| 5 | princeton university | princeton, new jersey | tigers | 5113 | 2479 | 7592 | $18.2 billion (5th) | 1172 | dei sub numine viget (under god's power she flourishes) |
| 6 | university of pennsylvania | philadelphia, pennsylvania | quakers | 10337 | 10306 | 20643 | $7.7 billion (11th) | 4464 | leges sine moribus vanae (laws without morals are useless) |
| 7 | yale university | new haven, connecticut | bulldogs | 5275 | 6391 | 11666 | $20.8 billion (2nd) | 4140 | אורים ותומים lux et veritas (light and truth) | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select notes where position = '64th' col : year | competition | venue | position | event | notes row 1 : 1997 | central american games | san pedro sula, honduras | 2nd | 10,000 m | none row 2 : 2001 | central american and caribbean championships | guatemala city, guatemala | 6th | 5000 m | 14:57.04 row 3 : 2001 | central american and caribbean championships | guatemala city, guatemala | 3rd | 10,000 m | 30:53.52 row 4 : 2001 | central american games | guatemala city, guatemala | 1st | 5000 m | 14:28.91 a row 5 : 2001 | central american games | guatemala city, guatemala | 2nd | 10,000 m | 30:43.86 a row 6 : 2002 | central american championships | san jose, costa rica | 2nd | 5000 m | 14:30.14 row 7 : 2002 | central american championships | san jose, costa rica | 1st | 10,000 m | 30:05.31 row 8 : 2003 | central american championships | guatemala city, guatemala | 1st | 5000 m | 15:19.35 row 9 : 2003 | central american championships | guatemala city, guatemala | 1st | 10,000 m | 30:16.25 row 10 : 2003 | pan american games | santo domingo, dominican republic | none | 5000 m | dnf row 11 : 2003 | pan american games | santo domingo, dominican republic | 7th | 10,000 m | 30:26.61 row 12 : 2004 | olympic games | athens, greece | 64th | marathon | 2:27:13 row 13 : 2005 | central american championships | san jose, costa rica | 1st | 10,000 m | 30:11.54 row 14 : 2006 | ibero-american championships | ponce, puerto rico | 8th | 5000 m | 14:31.55 row 15 : 2006 | central american and caribbean games | cartagena, colombia | 6th | 5000 m | 14:27.54 row 16 : 2006 | central american and caribbean games | cartagena, colombia | 4th | 10,000 m | 30:09.31 row 17 : 2007 | central american championships | san jose, costa rica | 1st | 5000 m | 14:42.08 row 18 : 2007 | central american championships | san jose, costa rica | 1st | 10,000 m | 29:53.61 row 19 : 2007 | nacac championships | san salvador, el salvador | 1st | 5000 m | 14:33.31 row 20 : 2007 | nacac championships | san salvador, el salvador | 1st | 10,000 m | 29:42.11 row 21 : 2007 | pan american games | rio de janeiro, brazil | 2nd | marathon | 2:14:27 row 22 : 2008 | olympic games | beijing, pr china | 35th | marathon | 2:20:15 row 23 : 2009 | central american championships | guatemala city, guatemala | 1st | 5000 m | 14:55.44 row 24 : 2010 | central american and caribbean games | mayaguez, puerto rico | 1st | marathon | 2:21:35 row 25 : 2010 | central american championships | guatemala city, guatemala | 1st | 10,000 m | 32:06.26 row 26 : 2011 | pan american games | guadalajara, mexico | 5th | marathon | 2:20:27 sb row 27 : 2012 | olympic games | london, united kingdom | 38th | marathon | 2:18:23 | col : notes row 1 : 2:27:13 | select notes where position = '64th' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & competition & venue & position & event & notes \\
\midrule
0 & 1997 & central american games & san pedro sula, honduras & 2nd & 10,000 m & none \\
1 & 2001 & central american and caribbean championships & guatemala city, guatemala & 6th & 5000 m & 14:57.04 \\
2 & 2001 & central american and caribbean championships & guatemala city, guatemala & 3rd & 10,000 m & 30:53.52 \\
3 & 2001 & central american games & guatemala city, guatemala & 1st & 5000 m & 14:28.91 a \\
4 & 2001 & central american games & guatemala city, guatemala & 2nd & 10,000 m & 30:43.86 a \\
5 & 2002 & central american championships & san jose, costa rica & 2nd & 5000 m & 14:30.14 \\
6 & 2002 & central american championships & san jose, costa rica & 1st & 10,000 m & 30:05.31 \\
7 & 2003 & central american championships & guatemala city, guatemala & 1st & 5000 m & 15:19.35 \\
8 & 2003 & central american championships & guatemala city, guatemala & 1st & 10,000 m & 30:16.25 \\
9 & 2003 & pan american games & santo domingo, dominican republic & none & 5000 m & dnf \\
10 & 2003 & pan american games & santo domingo, dominican republic & 7th & 10,000 m & 30:26.61 \\
11 & 2004 & olympic games & athens, greece & 64th & marathon & 2:27:13 \\
12 & 2005 & central american championships & san jose, costa rica & 1st & 10,000 m & 30:11.54 \\
13 & 2006 & ibero-american championships & ponce, puerto rico & 8th & 5000 m & 14:31.55 \\
14 & 2006 & central american and caribbean games & cartagena, colombia & 6th & 5000 m & 14:27.54 \\
15 & 2006 & central american and caribbean games & cartagena, colombia & 4th & 10,000 m & 30:09.31 \\
16 & 2007 & central american championships & san jose, costa rica & 1st & 5000 m & 14:42.08 \\
17 & 2007 & central american championships & san jose, costa rica & 1st & 10,000 m & 29:53.61 \\
18 & 2007 & nacac championships & san salvador, el salvador & 1st & 5000 m & 14:33.31 \\
19 & 2007 & nacac championships & san salvador, el salvador & 1st & 10,000 m & 29:42.11 \\
20 & 2007 & pan american games & rio de janeiro, brazil & 2nd & marathon & 2:14:27 \\
21 & 2008 & olympic games & beijing, pr china & 35th & marathon & 2:20:15 \\
22 & 2009 & central american championships & guatemala city, guatemala & 1st & 5000 m & 14:55.44 \\
23 & 2010 & central american and caribbean games & mayaguez, puerto rico & 1st & marathon & 2:21:35 \\
24 & 2010 & central american championships & guatemala city, guatemala & 1st & 10,000 m & 32:06.26 \\
25 & 2011 & pan american games & guadalajara, mexico & 5th & marathon & 2:20:27 sb \\
26 & 2012 & olympic games & london, united kingdom & 38th & marathon & 2:18:23 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& notes \\
\midrule
0 & 2:27:13 \\
\bottomrule
\end{tabular}
| select notes where position = '64th' <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>1997</td>
<td>central american games</td>
<td>san pedro sula, honduras</td>
<td>2nd</td>
<td>10,000 m</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2001</td>
<td>central american and caribbean championships</td>
<td>guatemala city, guatemala</td>
<td>6th</td>
<td>5000 m</td>
<td>14:57.04</td>
</tr>
<tr>
<th>2</th>
<td>2001</td>
<td>central american and caribbean championships</td>
<td>guatemala city, guatemala</td>
<td>3rd</td>
<td>10,000 m</td>
<td>30:53.52</td>
</tr>
<tr>
<th>3</th>
<td>2001</td>
<td>central american games</td>
<td>guatemala city, guatemala</td>
<td>1st</td>
<td>5000 m</td>
<td>14:28.91 a</td>
</tr>
<tr>
<th>4</th>
<td>2001</td>
<td>central american games</td>
<td>guatemala city, guatemala</td>
<td>2nd</td>
<td>10,000 m</td>
<td>30:43.86 a</td>
</tr>
<tr>
<th>5</th>
<td>2002</td>
<td>central american championships</td>
<td>san jose, costa rica</td>
<td>2nd</td>
<td>5000 m</td>
<td>14:30.14</td>
</tr>
<tr>
<th>6</th>
<td>2002</td>
<td>central american championships</td>
<td>san jose, costa rica</td>
<td>1st</td>
<td>10,000 m</td>
<td>30:05.31</td>
</tr>
<tr>
<th>7</th>
<td>2003</td>
<td>central american championships</td>
<td>guatemala city, guatemala</td>
<td>1st</td>
<td>5000 m</td>
<td>15:19.35</td>
</tr>
<tr>
<th>8</th>
<td>2003</td>
<td>central american championships</td>
<td>guatemala city, guatemala</td>
<td>1st</td>
<td>10,000 m</td>
<td>30:16.25</td>
</tr>
<tr>
<th>9</th>
<td>2003</td>
<td>pan american games</td>
<td>santo domingo, dominican republic</td>
<td>none</td>
<td>5000 m</td>
<td>dnf</td>
</tr>
<tr>
<th>10</th>
<td>2003</td>
<td>pan american games</td>
<td>santo domingo, dominican republic</td>
<td>7th</td>
<td>10,000 m</td>
<td>30:26.61</td>
</tr>
<tr>
<th>11</th>
<td>2004</td>
<td>olympic games</td>
<td>athens, greece</td>
<td>64th</td>
<td>marathon</td>
<td>2:27:13</td>
</tr>
<tr>
<th>12</th>
<td>2005</td>
<td>central american championships</td>
<td>san jose, costa rica</td>
<td>1st</td>
<td>10,000 m</td>
<td>30:11.54</td>
</tr>
<tr>
<th>13</th>
<td>2006</td>
<td>ibero-american championships</td>
<td>ponce, puerto rico</td>
<td>8th</td>
<td>5000 m</td>
<td>14:31.55</td>
</tr>
<tr>
<th>14</th>
<td>2006</td>
<td>central american and caribbean games</td>
<td>cartagena, colombia</td>
<td>6th</td>
<td>5000 m</td>
<td>14:27.54</td>
</tr>
<tr>
<th>15</th>
<td>2006</td>
<td>central american and caribbean games</td>
<td>cartagena, colombia</td>
<td>4th</td>
<td>10,000 m</td>
<td>30:09.31</td>
</tr>
<tr>
<th>16</th>
<td>2007</td>
<td>central american championships</td>
<td>san jose, costa rica</td>
<td>1st</td>
<td>5000 m</td>
<td>14:42.08</td>
</tr>
<tr>
<th>17</th>
<td>2007</td>
<td>central american championships</td>
<td>san jose, costa rica</td>
<td>1st</td>
<td>10,000 m</td>
<td>29:53.61</td>
</tr>
<tr>
<th>18</th>
<td>2007</td>
<td>nacac championships</td>
<td>san salvador, el salvador</td>
<td>1st</td>
<td>5000 m</td>
<td>14:33.31</td>
</tr>
<tr>
<th>19</th>
<td>2007</td>
<td>nacac championships</td>
<td>san salvador, el salvador</td>
<td>1st</td>
<td>10,000 m</td>
<td>29:42.11</td>
</tr>
<tr>
<th>20</th>
<td>2007</td>
<td>pan american games</td>
<td>rio de janeiro, brazil</td>
<td>2nd</td>
<td>marathon</td>
<td>2:14:27</td>
</tr>
<tr>
<th>21</th>
<td>2008</td>
<td>olympic games</td>
<td>beijing, pr china</td>
<td>35th</td>
<td>marathon</td>
<td>2:20:15</td>
</tr>
<tr>
<th>22</th>
<td>2009</td>
<td>central american championships</td>
<td>guatemala city, guatemala</td>
<td>1st</td>
<td>5000 m</td>
<td>14:55.44</td>
</tr>
<tr>
<th>23</th>
<td>2010</td>
<td>central american and caribbean games</td>
<td>mayaguez, puerto rico</td>
<td>1st</td>
<td>marathon</td>
<td>2:21:35</td>
</tr>
<tr>
<th>24</th>
<td>2010</td>
<td>central american championships</td>
<td>guatemala city, guatemala</td>
<td>1st</td>
<td>10,000 m</td>
<td>32:06.26</td>
</tr>
<tr>
<th>25</th>
<td>2011</td>
<td>pan american games</td>
<td>guadalajara, mexico</td>
<td>5th</td>
<td>marathon</td>
<td>2:20:27 sb</td>
</tr>
<tr>
<th>26</th>
<td>2012</td>
<td>olympic games</td>
<td>london, united kingdom</td>
<td>38th</td>
<td>marathon</td>
<td>2:18:23</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2:27:13</td>
</tr>
</tbody>
</table> | select notes where position = '64th' <table_name> : table | | year | competition | venue | position | event | notes |
|---:|-------:|:---------------------------------------------|:----------------------------------|:-----------|:---------|:-----------|
| 0 | 1997 | central american games | san pedro sula, honduras | 2nd | 10,000 m | none |
| 1 | 2001 | central american and caribbean championships | guatemala city, guatemala | 6th | 5000 m | 14:57.04 |
| 2 | 2001 | central american and caribbean championships | guatemala city, guatemala | 3rd | 10,000 m | 30:53.52 |
| 3 | 2001 | central american games | guatemala city, guatemala | 1st | 5000 m | 14:28.91 a |
| 4 | 2001 | central american games | guatemala city, guatemala | 2nd | 10,000 m | 30:43.86 a |
| 5 | 2002 | central american championships | san jose, costa rica | 2nd | 5000 m | 14:30.14 |
| 6 | 2002 | central american championships | san jose, costa rica | 1st | 10,000 m | 30:05.31 |
| 7 | 2003 | central american championships | guatemala city, guatemala | 1st | 5000 m | 15:19.35 |
| 8 | 2003 | central american championships | guatemala city, guatemala | 1st | 10,000 m | 30:16.25 |
| 9 | 2003 | pan american games | santo domingo, dominican republic | none | 5000 m | dnf |
| 10 | 2003 | pan american games | santo domingo, dominican republic | 7th | 10,000 m | 30:26.61 |
| 11 | 2004 | olympic games | athens, greece | 64th | marathon | 2:27:13 |
| 12 | 2005 | central american championships | san jose, costa rica | 1st | 10,000 m | 30:11.54 |
| 13 | 2006 | ibero-american championships | ponce, puerto rico | 8th | 5000 m | 14:31.55 |
| 14 | 2006 | central american and caribbean games | cartagena, colombia | 6th | 5000 m | 14:27.54 |
| 15 | 2006 | central american and caribbean games | cartagena, colombia | 4th | 10,000 m | 30:09.31 |
| 16 | 2007 | central american championships | san jose, costa rica | 1st | 5000 m | 14:42.08 |
| 17 | 2007 | central american championships | san jose, costa rica | 1st | 10,000 m | 29:53.61 |
| 18 | 2007 | nacac championships | san salvador, el salvador | 1st | 5000 m | 14:33.31 |
| 19 | 2007 | nacac championships | san salvador, el salvador | 1st | 10,000 m | 29:42.11 |
| 20 | 2007 | pan american games | rio de janeiro, brazil | 2nd | marathon | 2:14:27 |
| 21 | 2008 | olympic games | beijing, pr china | 35th | marathon | 2:20:15 |
| 22 | 2009 | central american championships | guatemala city, guatemala | 1st | 5000 m | 14:55.44 |
| 23 | 2010 | central american and caribbean games | mayaguez, puerto rico | 1st | marathon | 2:21:35 |
| 24 | 2010 | central american championships | guatemala city, guatemala | 1st | 10,000 m | 32:06.26 |
| 25 | 2011 | pan american games | guadalajara, mexico | 5th | marathon | 2:20:27 sb |
| 26 | 2012 | olympic games | london, united kingdom | 38th | marathon | 2:18:23 | | | | notes |
|---:|:--------|
| 0 | 2:27:13 | | [
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select title where # = 3 col : # | title | producer(s) | performer(s) | length row 1 : 1 | "ova here" | da beatminerz | krs-one | 2:56 row 2 : 2 | "things is about to change" | creative minds combined | krs-one | 2:34 row 3 : 3 | "splash" | a-sharp, pleasure king | krs-one | 2:24 row 4 : 4 | "my people" | alumni | krs-one | 0:19 row 5 : 5 | "kreditz" | milann miles, rick long | krs-one | 2:02 row 6 : 6 | "i remember" | j-roc, mad lion | krs-one | 4:03 row 7 : 7 | "down the charts" | milann miles, rick long | krs-one | 2:10 row 8 : 8 | "you really don't want it" | jim bean | none | 3:29 row 9 : 9 | "womanology" | soul supreme | krs-one | 3:54 row 10 : 10 | "2nd kreditz" | none | krs-one | 0:46 row 11 : 11 | "stop it" | krs-one, mad lion | none | 1:38 row 12 : 12 | "problemz" | vanguard | krs-one | 3:15 row 13 : 13 | "believe it!" | soul supreme | krs-one | 3:59 | col : title row 1 : "splash" | select title where # = 3 <table_name> : table \begin{tabular}{llllll}
\toprule
& # & title & producer(s) & performer(s) & length \\
\midrule
0 & 1 & "ova here" & da beatminerz & krs-one & 2:56 \\
1 & 2 & "things is about to change" & creative minds combined & krs-one & 2:34 \\
2 & 3 & "splash" & a-sharp, pleasure king & krs-one & 2:24 \\
3 & 4 & "my people" & alumni & krs-one & 0:19 \\
4 & 5 & "kreditz" & milann miles, rick long & krs-one & 2:02 \\
5 & 6 & "i remember" & j-roc, mad lion & krs-one & 4:03 \\
6 & 7 & "down the charts" & milann miles, rick long & krs-one & 2:10 \\
7 & 8 & "you really don't want it" & jim bean & none & 3:29 \\
8 & 9 & "womanology" & soul supreme & krs-one & 3:54 \\
9 & 10 & "2nd kreditz" & none & krs-one & 0:46 \\
10 & 11 & "stop it" & krs-one, mad lion & none & 1:38 \\
11 & 12 & "problemz" & vanguard & krs-one & 3:15 \\
12 & 13 & "believe it!" & soul supreme & krs-one & 3:59 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& title \\
\midrule
0 & "splash" \\
\bottomrule
\end{tabular}
| select title where # = 3 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>title</th>
<th>producer(s)</th>
<th>performer(s)</th>
<th>length</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>"ova here"</td>
<td>da beatminerz</td>
<td>krs-one</td>
<td>2:56</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>"things is about to change"</td>
<td>creative minds combined</td>
<td>krs-one</td>
<td>2:34</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>"splash"</td>
<td>a-sharp, pleasure king</td>
<td>krs-one</td>
<td>2:24</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>"my people"</td>
<td>alumni</td>
<td>krs-one</td>
<td>0:19</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>"kreditz"</td>
<td>milann miles, rick long</td>
<td>krs-one</td>
<td>2:02</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>"i remember"</td>
<td>j-roc, mad lion</td>
<td>krs-one</td>
<td>4:03</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>"down the charts"</td>
<td>milann miles, rick long</td>
<td>krs-one</td>
<td>2:10</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>"you really don't want it"</td>
<td>jim bean</td>
<td>none</td>
<td>3:29</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>"womanology"</td>
<td>soul supreme</td>
<td>krs-one</td>
<td>3:54</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>"2nd kreditz"</td>
<td>none</td>
<td>krs-one</td>
<td>0:46</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>"stop it"</td>
<td>krs-one, mad lion</td>
<td>none</td>
<td>1:38</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>"problemz"</td>
<td>vanguard</td>
<td>krs-one</td>
<td>3:15</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>"believe it!"</td>
<td>soul supreme</td>
<td>krs-one</td>
<td>3:59</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>"splash"</td>
</tr>
</tbody>
</table> | select title where # = 3 <table_name> : table | | # | title | producer(s) | performer(s) | length |
|---:|----:|:----------------------------|:------------------------|:---------------|:---------|
| 0 | 1 | "ova here" | da beatminerz | krs-one | 2:56 |
| 1 | 2 | "things is about to change" | creative minds combined | krs-one | 2:34 |
| 2 | 3 | "splash" | a-sharp, pleasure king | krs-one | 2:24 |
| 3 | 4 | "my people" | alumni | krs-one | 0:19 |
| 4 | 5 | "kreditz" | milann miles, rick long | krs-one | 2:02 |
| 5 | 6 | "i remember" | j-roc, mad lion | krs-one | 4:03 |
| 6 | 7 | "down the charts" | milann miles, rick long | krs-one | 2:10 |
| 7 | 8 | "you really don't want it" | jim bean | none | 3:29 |
| 8 | 9 | "womanology" | soul supreme | krs-one | 3:54 |
| 9 | 10 | "2nd kreditz" | none | krs-one | 0:46 |
| 10 | 11 | "stop it" | krs-one, mad lion | none | 1:38 |
| 11 | 12 | "problemz" | vanguard | krs-one | 3:15 |
| 12 | 13 | "believe it!" | soul supreme | krs-one | 3:59 | | | | title |
|---:|:---------|
| 0 | "splash" | | [
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select count ( * ) where constructor = 'arrows' col : pos | no | driver | constructor | time | gap row 1 : 1 | 1 | mika hakkinen | mclaren-mercedes | 1:24.804 | none row 2 : 2 | 3 | michael schumacher | ferrari | 1:25.223 | +0.419 row 3 : 3 | 2 | david coulthard | mclaren-mercedes | 1:25.594 | +0.790 row 4 : 4 | 4 | eddie irvine | ferrari | 1:25.677 | +0.873 row 5 : 5 | 8 | heinz-harald frentzen | jordan-mugen-honda | 1:25.991 | +1.187 row 6 : 6 | 7 | damon hill | jordan-mugen-honda | 1:26.099 | +1.295 row 7 : 7 | 16 | rubens barrichello | stewart-ford | 1:26.194 | +1.390 row 8 : 8 | 6 | ralf schumacher | williams-supertec | 1:26.438 | +1.634 row 9 : 9 | 22 | jacques villeneuve | bar-supertec | 1:26.719 | +1.915 row 10 : 10 | 11 | jean alesi | sauber-petronas | 1:26.761 | +1.957 row 11 : 11 | 17 | johnny herbert | stewart-ford | 1:26.873 | +2.069 row 12 : 12 | 12 | pedro diniz | sauber-petronas | 1:27.196 | +2.392 row 13 : 13 | 5 | alessandro zanardi | williams-supertec | 1:27.223 | +2.419 row 14 : 14 | 19 | jarno trulli | prost-peugeot | 1:27.227 | +2.423 row 15 : 15 | 18 | olivier panis | prost-peugeot | 1:27.543 | +2.739 row 16 : 16 | 23 | ricardo zonta | bar-supertec | 1:27.699 | +2.895 row 17 : 17 | 9 | giancarlo fisichella | benetton-playlife | 1:27.857 | +3.053 row 18 : 18 | 10 | alexander wurz | benetton-playlife | 1:28.010 | +3.206 row 19 : 19 | 15 | toranosuke takagi | arrows | 1:28.037 | +3.233 row 20 : 20 | 14 | pedro de la rosa | arrows | 1:28.148 | +3.344 row 21 : 21 | 20 | luca badoer | minardi-ford | 1:28.695 | +3.891 row 22 : 22 | 21 | marc gene | minardi-ford | 1:28.772 | +3.968 | col : count ( "*" ) row 1 : 2 | select count ( * ) where constructor = 'arrows' <table_name> : table \begin{tabular}{lllllll}
\toprule
& pos & no & driver & constructor & time & gap \\
\midrule
0 & 1 & 1 & mika hakkinen & mclaren-mercedes & 1:24.804 & none \\
1 & 2 & 3 & michael schumacher & ferrari & 1:25.223 & +0.419 \\
2 & 3 & 2 & david coulthard & mclaren-mercedes & 1:25.594 & +0.790 \\
3 & 4 & 4 & eddie irvine & ferrari & 1:25.677 & +0.873 \\
4 & 5 & 8 & heinz-harald frentzen & jordan-mugen-honda & 1:25.991 & +1.187 \\
5 & 6 & 7 & damon hill & jordan-mugen-honda & 1:26.099 & +1.295 \\
6 & 7 & 16 & rubens barrichello & stewart-ford & 1:26.194 & +1.390 \\
7 & 8 & 6 & ralf schumacher & williams-supertec & 1:26.438 & +1.634 \\
8 & 9 & 22 & jacques villeneuve & bar-supertec & 1:26.719 & +1.915 \\
9 & 10 & 11 & jean alesi & sauber-petronas & 1:26.761 & +1.957 \\
10 & 11 & 17 & johnny herbert & stewart-ford & 1:26.873 & +2.069 \\
11 & 12 & 12 & pedro diniz & sauber-petronas & 1:27.196 & +2.392 \\
12 & 13 & 5 & alessandro zanardi & williams-supertec & 1:27.223 & +2.419 \\
13 & 14 & 19 & jarno trulli & prost-peugeot & 1:27.227 & +2.423 \\
14 & 15 & 18 & olivier panis & prost-peugeot & 1:27.543 & +2.739 \\
15 & 16 & 23 & ricardo zonta & bar-supertec & 1:27.699 & +2.895 \\
16 & 17 & 9 & giancarlo fisichella & benetton-playlife & 1:27.857 & +3.053 \\
17 & 18 & 10 & alexander wurz & benetton-playlife & 1:28.010 & +3.206 \\
18 & 19 & 15 & toranosuke takagi & arrows & 1:28.037 & +3.233 \\
19 & 20 & 14 & pedro de la rosa & arrows & 1:28.148 & +3.344 \\
20 & 21 & 20 & luca badoer & minardi-ford & 1:28.695 & +3.891 \\
21 & 22 & 21 & marc gene & minardi-ford & 1:28.772 & +3.968 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( * ) where constructor = 'arrows' <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>time</th>
<th>gap</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1</td>
<td>mika hakkinen</td>
<td>mclaren-mercedes</td>
<td>1:24.804</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>3</td>
<td>michael schumacher</td>
<td>ferrari</td>
<td>1:25.223</td>
<td>+0.419</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2</td>
<td>david coulthard</td>
<td>mclaren-mercedes</td>
<td>1:25.594</td>
<td>+0.790</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>4</td>
<td>eddie irvine</td>
<td>ferrari</td>
<td>1:25.677</td>
<td>+0.873</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>8</td>
<td>heinz-harald frentzen</td>
<td>jordan-mugen-honda</td>
<td>1:25.991</td>
<td>+1.187</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>7</td>
<td>damon hill</td>
<td>jordan-mugen-honda</td>
<td>1:26.099</td>
<td>+1.295</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>16</td>
<td>rubens barrichello</td>
<td>stewart-ford</td>
<td>1:26.194</td>
<td>+1.390</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>6</td>
<td>ralf schumacher</td>
<td>williams-supertec</td>
<td>1:26.438</td>
<td>+1.634</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>22</td>
<td>jacques villeneuve</td>
<td>bar-supertec</td>
<td>1:26.719</td>
<td>+1.915</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>11</td>
<td>jean alesi</td>
<td>sauber-petronas</td>
<td>1:26.761</td>
<td>+1.957</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>17</td>
<td>johnny herbert</td>
<td>stewart-ford</td>
<td>1:26.873</td>
<td>+2.069</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>12</td>
<td>pedro diniz</td>
<td>sauber-petronas</td>
<td>1:27.196</td>
<td>+2.392</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>5</td>
<td>alessandro zanardi</td>
<td>williams-supertec</td>
<td>1:27.223</td>
<td>+2.419</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>19</td>
<td>jarno trulli</td>
<td>prost-peugeot</td>
<td>1:27.227</td>
<td>+2.423</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>18</td>
<td>olivier panis</td>
<td>prost-peugeot</td>
<td>1:27.543</td>
<td>+2.739</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>23</td>
<td>ricardo zonta</td>
<td>bar-supertec</td>
<td>1:27.699</td>
<td>+2.895</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>9</td>
<td>giancarlo fisichella</td>
<td>benetton-playlife</td>
<td>1:27.857</td>
<td>+3.053</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>10</td>
<td>alexander wurz</td>
<td>benetton-playlife</td>
<td>1:28.010</td>
<td>+3.206</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>15</td>
<td>toranosuke takagi</td>
<td>arrows</td>
<td>1:28.037</td>
<td>+3.233</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>14</td>
<td>pedro de la rosa</td>
<td>arrows</td>
<td>1:28.148</td>
<td>+3.344</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>20</td>
<td>luca badoer</td>
<td>minardi-ford</td>
<td>1:28.695</td>
<td>+3.891</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>21</td>
<td>marc gene</td>
<td>minardi-ford</td>
<td>1:28.772</td>
<td>+3.968</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>2</td>
</tr>
</tbody>
</table> | select count ( * ) where constructor = 'arrows' <table_name> : table | | pos | no | driver | constructor | time | gap |
|---:|------:|-----:|:----------------------|:-------------------|:---------|:-------|
| 0 | 1 | 1 | mika hakkinen | mclaren-mercedes | 1:24.804 | none |
| 1 | 2 | 3 | michael schumacher | ferrari | 1:25.223 | +0.419 |
| 2 | 3 | 2 | david coulthard | mclaren-mercedes | 1:25.594 | +0.790 |
| 3 | 4 | 4 | eddie irvine | ferrari | 1:25.677 | +0.873 |
| 4 | 5 | 8 | heinz-harald frentzen | jordan-mugen-honda | 1:25.991 | +1.187 |
| 5 | 6 | 7 | damon hill | jordan-mugen-honda | 1:26.099 | +1.295 |
| 6 | 7 | 16 | rubens barrichello | stewart-ford | 1:26.194 | +1.390 |
| 7 | 8 | 6 | ralf schumacher | williams-supertec | 1:26.438 | +1.634 |
| 8 | 9 | 22 | jacques villeneuve | bar-supertec | 1:26.719 | +1.915 |
| 9 | 10 | 11 | jean alesi | sauber-petronas | 1:26.761 | +1.957 |
| 10 | 11 | 17 | johnny herbert | stewart-ford | 1:26.873 | +2.069 |
| 11 | 12 | 12 | pedro diniz | sauber-petronas | 1:27.196 | +2.392 |
| 12 | 13 | 5 | alessandro zanardi | williams-supertec | 1:27.223 | +2.419 |
| 13 | 14 | 19 | jarno trulli | prost-peugeot | 1:27.227 | +2.423 |
| 14 | 15 | 18 | olivier panis | prost-peugeot | 1:27.543 | +2.739 |
| 15 | 16 | 23 | ricardo zonta | bar-supertec | 1:27.699 | +2.895 |
| 16 | 17 | 9 | giancarlo fisichella | benetton-playlife | 1:27.857 | +3.053 |
| 17 | 18 | 10 | alexander wurz | benetton-playlife | 1:28.010 | +3.206 |
| 18 | 19 | 15 | toranosuke takagi | arrows | 1:28.037 | +3.233 |
| 19 | 20 | 14 | pedro de la rosa | arrows | 1:28.148 | +3.344 |
| 20 | 21 | 20 | luca badoer | minardi-ford | 1:28.695 | +3.891 |
| 21 | 22 | 21 | marc gene | minardi-ford | 1:28.772 | +3.968 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 2 | | [
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select year where model = 'd40' col : make/model | series | model | year | notes row 1 : new flyer | 101-135 | d40lfr | 2010 | none row 2 : new flyer | 140-169 | d40lfr | 2011 | 140-143 145-153 155-169 wrap for rt 144 and 154 lost there rt wraps row 3 : new flyer | 201-230 | d40lf | 2004 | 204 retired due to fire row 4 : new flyer | 231-260 | d40lf | 2005 | none row 5 : new flyer | 270-281 | d40lf | 2007 | none row 6 : mci | 301-334 | classic | 1988 | all retired row 7 : new flyer | 340-366 | d40 | 1992 | 365 remains, used only during rush hour row 8 : new flyer | 370-399 | d40 | 1994 | 370 371 372 373 374 379 380 390 395? 397 398 399 retired, used only during rush hour row 9 : new flyer | 401-443 | d40lf | 1998 | all have been rebuilt row 10 : new flyer | 444-504 | d40lf | 1999 | all have been rebuilt row 11 : new flyer | 510-561 | d40lf | 2002 | being rebuilt 510 513 515 516 517 519 520 521 522 529 532 534 536 537 539 540 545 row 12 : new flyer | 570-599 | d40lf | 2003 | none row 13 : new flyer | 601-640 | d40lfr | 2011 | 601 603 605 wrap for rt row 14 : new flyer | 671-699 | d40 | 1994 | 684 retired, used only during rush hour row 15 : new flyer | 701-733 | d40lfr | 2008 | none row 16 : new flyer | 735-799 | d40lfr | 2009 | none row 17 : new flyer | 800-829 | d40lfr | 2013 | 800-830 now inservice 822 had a fire row 18 : new flyer | 901-910 | invero/d40i | 2004 | ex701-710 only used for rush hour row 19 : new flyer | 911-925 | d30lf | 1996 | all rebuild row 20 : new flyer | 930-949 | d30lf | 2001 | 931 rebuild row 21 : new flyer | 971-990 | d60lf | 2003 | ex octranspo most units are between ex 6302-6338 971 973 976 977 979 are now in service row 22 : new flyer | 991-993 | d40lf | 1994 | all rebuilt, used only during rush hour | col : year row 1 : 1992 row 2 : 1994 row 3 : 1994 | select year where model = 'd40' <table_name> : table \begin{tabular}{llllll}
\toprule
& make/model & series & model & year & notes \\
\midrule
0 & new flyer & 101-135 & d40lfr & 2010 & none \\
1 & new flyer & 140-169 & d40lfr & 2011 & 140-143 145-153 155-169 wrap for rt 144 and 154 lost there rt wraps \\
2 & new flyer & 201-230 & d40lf & 2004 & 204 retired due to fire \\
3 & new flyer & 231-260 & d40lf & 2005 & none \\
4 & new flyer & 270-281 & d40lf & 2007 & none \\
5 & mci & 301-334 & classic & 1988 & all retired \\
6 & new flyer & 340-366 & d40 & 1992 & 365 remains, used only during rush hour \\
7 & new flyer & 370-399 & d40 & 1994 & 370 371 372 373 374 379 380 390 395? 397 398 399 retired, used only during rush hour \\
8 & new flyer & 401-443 & d40lf & 1998 & all have been rebuilt \\
9 & new flyer & 444-504 & d40lf & 1999 & all have been rebuilt \\
10 & new flyer & 510-561 & d40lf & 2002 & being rebuilt 510 513 515 516 517 519 520 521 522 529 532 534 536 537 539 540 545 \\
11 & new flyer & 570-599 & d40lf & 2003 & none \\
12 & new flyer & 601-640 & d40lfr & 2011 & 601 603 605 wrap for rt \\
13 & new flyer & 671-699 & d40 & 1994 & 684 retired, used only during rush hour \\
14 & new flyer & 701-733 & d40lfr & 2008 & none \\
15 & new flyer & 735-799 & d40lfr & 2009 & none \\
16 & new flyer & 800-829 & d40lfr & 2013 & 800-830 now inservice 822 had a fire \\
17 & new flyer & 901-910 & invero/d40i & 2004 & ex701-710 only used for rush hour \\
18 & new flyer & 911-925 & d30lf & 1996 & all rebuild \\
19 & new flyer & 930-949 & d30lf & 2001 & 931 rebuild \\
20 & new flyer & 971-990 & d60lf & 2003 & ex octranspo most units are between ex 6302-6338 971 973 976 977 979 are now in service \\
21 & new flyer & 991-993 & d40lf & 1994 & all rebuilt, used only during rush hour \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1992 \\
1 & 1994 \\
2 & 1994 \\
\bottomrule
\end{tabular}
| select year where model = 'd40' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>make/model</th>
<th>series</th>
<th>model</th>
<th>year</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>new flyer</td>
<td>101-135</td>
<td>d40lfr</td>
<td>2010</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>new flyer</td>
<td>140-169</td>
<td>d40lfr</td>
<td>2011</td>
<td>140-143 145-153 155-169 wrap for rt 144 and 154 lost there rt wraps</td>
</tr>
<tr>
<th>2</th>
<td>new flyer</td>
<td>201-230</td>
<td>d40lf</td>
<td>2004</td>
<td>204 retired due to fire</td>
</tr>
<tr>
<th>3</th>
<td>new flyer</td>
<td>231-260</td>
<td>d40lf</td>
<td>2005</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>new flyer</td>
<td>270-281</td>
<td>d40lf</td>
<td>2007</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>mci</td>
<td>301-334</td>
<td>classic</td>
<td>1988</td>
<td>all retired</td>
</tr>
<tr>
<th>6</th>
<td>new flyer</td>
<td>340-366</td>
<td>d40</td>
<td>1992</td>
<td>365 remains, used only during rush hour</td>
</tr>
<tr>
<th>7</th>
<td>new flyer</td>
<td>370-399</td>
<td>d40</td>
<td>1994</td>
<td>370 371 372 373 374 379 380 390 395? 397 398 399 retired, used only during rush hour</td>
</tr>
<tr>
<th>8</th>
<td>new flyer</td>
<td>401-443</td>
<td>d40lf</td>
<td>1998</td>
<td>all have been rebuilt</td>
</tr>
<tr>
<th>9</th>
<td>new flyer</td>
<td>444-504</td>
<td>d40lf</td>
<td>1999</td>
<td>all have been rebuilt</td>
</tr>
<tr>
<th>10</th>
<td>new flyer</td>
<td>510-561</td>
<td>d40lf</td>
<td>2002</td>
<td>being rebuilt 510 513 515 516 517 519 520 521 522 529 532 534 536 537 539 540 545</td>
</tr>
<tr>
<th>11</th>
<td>new flyer</td>
<td>570-599</td>
<td>d40lf</td>
<td>2003</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>new flyer</td>
<td>601-640</td>
<td>d40lfr</td>
<td>2011</td>
<td>601 603 605 wrap for rt</td>
</tr>
<tr>
<th>13</th>
<td>new flyer</td>
<td>671-699</td>
<td>d40</td>
<td>1994</td>
<td>684 retired, used only during rush hour</td>
</tr>
<tr>
<th>14</th>
<td>new flyer</td>
<td>701-733</td>
<td>d40lfr</td>
<td>2008</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>new flyer</td>
<td>735-799</td>
<td>d40lfr</td>
<td>2009</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>new flyer</td>
<td>800-829</td>
<td>d40lfr</td>
<td>2013</td>
<td>800-830 now inservice 822 had a fire</td>
</tr>
<tr>
<th>17</th>
<td>new flyer</td>
<td>901-910</td>
<td>invero/d40i</td>
<td>2004</td>
<td>ex701-710 only used for rush hour</td>
</tr>
<tr>
<th>18</th>
<td>new flyer</td>
<td>911-925</td>
<td>d30lf</td>
<td>1996</td>
<td>all rebuild</td>
</tr>
<tr>
<th>19</th>
<td>new flyer</td>
<td>930-949</td>
<td>d30lf</td>
<td>2001</td>
<td>931 rebuild</td>
</tr>
<tr>
<th>20</th>
<td>new flyer</td>
<td>971-990</td>
<td>d60lf</td>
<td>2003</td>
<td>ex octranspo most units are between ex 6302-6338 971 973 976 977 979 are now in service</td>
</tr>
<tr>
<th>21</th>
<td>new flyer</td>
<td>991-993</td>
<td>d40lf</td>
<td>1994</td>
<td>all rebuilt, used only during rush hour</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>1992</td>
</tr>
<tr>
<th>1</th>
<td>1994</td>
</tr>
<tr>
<th>2</th>
<td>1994</td>
</tr>
</tbody>
</table> | select year where model = 'd40' <table_name> : table | | make/model | series | model | year | notes |
|---:|:-------------|:---------|:------------|-------:|:----------------------------------------------------------------------------------------|
| 0 | new flyer | 101-135 | d40lfr | 2010 | none |
| 1 | new flyer | 140-169 | d40lfr | 2011 | 140-143 145-153 155-169 wrap for rt 144 and 154 lost there rt wraps |
| 2 | new flyer | 201-230 | d40lf | 2004 | 204 retired due to fire |
| 3 | new flyer | 231-260 | d40lf | 2005 | none |
| 4 | new flyer | 270-281 | d40lf | 2007 | none |
| 5 | mci | 301-334 | classic | 1988 | all retired |
| 6 | new flyer | 340-366 | d40 | 1992 | 365 remains, used only during rush hour |
| 7 | new flyer | 370-399 | d40 | 1994 | 370 371 372 373 374 379 380 390 395? 397 398 399 retired, used only during rush hour |
| 8 | new flyer | 401-443 | d40lf | 1998 | all have been rebuilt |
| 9 | new flyer | 444-504 | d40lf | 1999 | all have been rebuilt |
| 10 | new flyer | 510-561 | d40lf | 2002 | being rebuilt 510 513 515 516 517 519 520 521 522 529 532 534 536 537 539 540 545 |
| 11 | new flyer | 570-599 | d40lf | 2003 | none |
| 12 | new flyer | 601-640 | d40lfr | 2011 | 601 603 605 wrap for rt |
| 13 | new flyer | 671-699 | d40 | 1994 | 684 retired, used only during rush hour |
| 14 | new flyer | 701-733 | d40lfr | 2008 | none |
| 15 | new flyer | 735-799 | d40lfr | 2009 | none |
| 16 | new flyer | 800-829 | d40lfr | 2013 | 800-830 now inservice 822 had a fire |
| 17 | new flyer | 901-910 | invero/d40i | 2004 | ex701-710 only used for rush hour |
| 18 | new flyer | 911-925 | d30lf | 1996 | all rebuild |
| 19 | new flyer | 930-949 | d30lf | 2001 | 931 rebuild |
| 20 | new flyer | 971-990 | d60lf | 2003 | ex octranspo most units are between ex 6302-6338 971 973 976 977 979 are now in service |
| 21 | new flyer | 991-993 | d40lf | 1994 | all rebuilt, used only during rush hour | | | | year |
|---:|-------:|
| 0 | 1992 |
| 1 | 1994 |
| 2 | 1994 | | [
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select max ( time ) where date = 'september 12' col : date | time | opponent | site | tv | result | attendance row 1 : september 5 | 2:30 p.m | jackson state | davis wade stadium • starkville, ms | espnu | w 45-7 | 54232 row 2 : september 12 | 6:00 p.m | at auburn | jordan-hare stadium • auburn, al | secrn | l 24-49 | 85269 row 3 : september 19 | 6:00 p.m | at vanderbilt | vanderbilt stadium • nashville, tn | secrn | w 15-3 | 31840 row 4 : september 26 | 11:21 a.m | #7 lsu | davis wade stadium • starkville, ms | secn | l 26-30 | 53612 row 5 : october 3 | 6:30 p.m | #25 georgia tech | davis wade stadium • starkville, ms | css | l 31-42 | 50035 row 6 : october 10 | 11:30 a.m | houston | davis wade stadium • starkville, ms | espnu | l 24-31 | 48019 row 7 : october 17 | 11:30 a.m | at middle tennessee | johnny "red" floyd stadium • murfreesboro, tn | espnu | w 27-6 | 23882 row 8 : october 24 | 6:30 p.m | #1 florida | davis wade stadium • starkville, ms | espn | l 19-29 | 57178 row 9 : october 31 | 6:00 p.m | at kentucky | commonwealth stadium • lexington, ky | secrn | w 31-24 | 67953 row 10 : november 14 | 6:00 p.m | #2 alabama | davis wade stadium • starkville, ms (rivalry) | espn | l 3-31 | 58103 row 11 : november 21 | 11:21 a.m | at arkansas | war memorial stadium • little rock, ar | secn | l 21-42 | 55634 row 12 : november 28 | 11:21 a.m | #25 ole miss | davis wade stadium • starkville, ms (egg bowl) | secn | w 41-27 | 55365 | col : max ( "time" ) row 1 : 6:00 p.m | select max ( time ) where date = 'september 12' <table_name> : table \begin{tabular}{llllllll}
\toprule
& date & time & opponent & site & tv & result & attendance \\
\midrule
0 & september 5 & 2:30 p.m & jackson state & davis wade stadium • starkville, ms & espnu & w 45-7 & 54232 \\
1 & september 12 & 6:00 p.m & at auburn & jordan-hare stadium • auburn, al & secrn & l 24-49 & 85269 \\
2 & september 19 & 6:00 p.m & at vanderbilt & vanderbilt stadium • nashville, tn & secrn & w 15-3 & 31840 \\
3 & september 26 & 11:21 a.m & #7 lsu & davis wade stadium • starkville, ms & secn & l 26-30 & 53612 \\
4 & october 3 & 6:30 p.m & #25 georgia tech & davis wade stadium • starkville, ms & css & l 31-42 & 50035 \\
5 & october 10 & 11:30 a.m & houston & davis wade stadium • starkville, ms & espnu & l 24-31 & 48019 \\
6 & october 17 & 11:30 a.m & at middle tennessee & johnny "red" floyd stadium • murfreesboro, tn & espnu & w 27-6 & 23882 \\
7 & october 24 & 6:30 p.m & #1 florida & davis wade stadium • starkville, ms & espn & l 19-29 & 57178 \\
8 & october 31 & 6:00 p.m & at kentucky & commonwealth stadium • lexington, ky & secrn & w 31-24 & 67953 \\
9 & november 14 & 6:00 p.m & #2 alabama & davis wade stadium • starkville, ms (rivalry) & espn & l 3-31 & 58103 \\
10 & november 21 & 11:21 a.m & at arkansas & war memorial stadium • little rock, ar & secn & l 21-42 & 55634 \\
11 & november 28 & 11:21 a.m & #25 ole miss & davis wade stadium • starkville, ms (egg bowl) & secn & w 41-27 & 55365 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& max ( "time" ) \\
\midrule
0 & 6:00 p.m \\
\bottomrule
\end{tabular}
| select max ( time ) where date = 'september 12' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>time</th>
<th>opponent</th>
<th>site</th>
<th>tv</th>
<th>result</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>september 5</td>
<td>2:30 p.m</td>
<td>jackson state</td>
<td>davis wade stadium • starkville, ms</td>
<td>espnu</td>
<td>w 45-7</td>
<td>54232</td>
</tr>
<tr>
<th>1</th>
<td>september 12</td>
<td>6:00 p.m</td>
<td>at auburn</td>
<td>jordan-hare stadium • auburn, al</td>
<td>secrn</td>
<td>l 24-49</td>
<td>85269</td>
</tr>
<tr>
<th>2</th>
<td>september 19</td>
<td>6:00 p.m</td>
<td>at vanderbilt</td>
<td>vanderbilt stadium • nashville, tn</td>
<td>secrn</td>
<td>w 15-3</td>
<td>31840</td>
</tr>
<tr>
<th>3</th>
<td>september 26</td>
<td>11:21 a.m</td>
<td>#7 lsu</td>
<td>davis wade stadium • starkville, ms</td>
<td>secn</td>
<td>l 26-30</td>
<td>53612</td>
</tr>
<tr>
<th>4</th>
<td>october 3</td>
<td>6:30 p.m</td>
<td>#25 georgia tech</td>
<td>davis wade stadium • starkville, ms</td>
<td>css</td>
<td>l 31-42</td>
<td>50035</td>
</tr>
<tr>
<th>5</th>
<td>october 10</td>
<td>11:30 a.m</td>
<td>houston</td>
<td>davis wade stadium • starkville, ms</td>
<td>espnu</td>
<td>l 24-31</td>
<td>48019</td>
</tr>
<tr>
<th>6</th>
<td>october 17</td>
<td>11:30 a.m</td>
<td>at middle tennessee</td>
<td>johnny "red" floyd stadium • murfreesboro, tn</td>
<td>espnu</td>
<td>w 27-6</td>
<td>23882</td>
</tr>
<tr>
<th>7</th>
<td>october 24</td>
<td>6:30 p.m</td>
<td>#1 florida</td>
<td>davis wade stadium • starkville, ms</td>
<td>espn</td>
<td>l 19-29</td>
<td>57178</td>
</tr>
<tr>
<th>8</th>
<td>october 31</td>
<td>6:00 p.m</td>
<td>at kentucky</td>
<td>commonwealth stadium • lexington, ky</td>
<td>secrn</td>
<td>w 31-24</td>
<td>67953</td>
</tr>
<tr>
<th>9</th>
<td>november 14</td>
<td>6:00 p.m</td>
<td>#2 alabama</td>
<td>davis wade stadium • starkville, ms (rivalry)</td>
<td>espn</td>
<td>l 3-31</td>
<td>58103</td>
</tr>
<tr>
<th>10</th>
<td>november 21</td>
<td>11:21 a.m</td>
<td>at arkansas</td>
<td>war memorial stadium • little rock, ar</td>
<td>secn</td>
<td>l 21-42</td>
<td>55634</td>
</tr>
<tr>
<th>11</th>
<td>november 28</td>
<td>11:21 a.m</td>
<td>#25 ole miss</td>
<td>davis wade stadium • starkville, ms (egg bowl)</td>
<td>secn</td>
<td>w 41-27</td>
<td>55365</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>max ( "time" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>6:00 p.m</td>
</tr>
</tbody>
</table> | select max ( time ) where date = 'september 12' <table_name> : table | | date | time | opponent | site | tv | result | attendance |
|---:|:-------------|:----------|:--------------------|:-----------------------------------------------|:------|:---------|-------------:|
| 0 | september 5 | 2:30 p.m | jackson state | davis wade stadium • starkville, ms | espnu | w 45-7 | 54232 |
| 1 | september 12 | 6:00 p.m | at auburn | jordan-hare stadium • auburn, al | secrn | l 24-49 | 85269 |
| 2 | september 19 | 6:00 p.m | at vanderbilt | vanderbilt stadium • nashville, tn | secrn | w 15-3 | 31840 |
| 3 | september 26 | 11:21 a.m | #7 lsu | davis wade stadium • starkville, ms | secn | l 26-30 | 53612 |
| 4 | october 3 | 6:30 p.m | #25 georgia tech | davis wade stadium • starkville, ms | css | l 31-42 | 50035 |
| 5 | october 10 | 11:30 a.m | houston | davis wade stadium • starkville, ms | espnu | l 24-31 | 48019 |
| 6 | october 17 | 11:30 a.m | at middle tennessee | johnny "red" floyd stadium • murfreesboro, tn | espnu | w 27-6 | 23882 |
| 7 | october 24 | 6:30 p.m | #1 florida | davis wade stadium • starkville, ms | espn | l 19-29 | 57178 |
| 8 | october 31 | 6:00 p.m | at kentucky | commonwealth stadium • lexington, ky | secrn | w 31-24 | 67953 |
| 9 | november 14 | 6:00 p.m | #2 alabama | davis wade stadium • starkville, ms (rivalry) | espn | l 3-31 | 58103 |
| 10 | november 21 | 11:21 a.m | at arkansas | war memorial stadium • little rock, ar | secn | l 21-42 | 55634 |
| 11 | november 28 | 11:21 a.m | #25 ole miss | davis wade stadium • starkville, ms (egg bowl) | secn | w 41-27 | 55365 | | | | max ( "time" ) |
|---:|:-----------------|
| 0 | 6:00 p.m | | [
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select album where b-sides = b-sides col : year | title | album | uk | b-sides row 1 : 2004 | "kim wilde" (download-only) | grey will fade | none | none row 2 : 2004 | "summer" | grey will fade | 31 | commodore; smut row 3 : 2005 | "bastardo" | grey will fade | 31 | 3 minutes; i am a kamera row 4 : 2006 | "behave" | the deep blue | 168 | mr. ed; cousteau (extended version); behave (luke smith clor remix) row 5 : 2007 | "i want you to know" | the deep blue | 108 | sister universe; suspiria row 6 : 2007 | "siberia" | the deep blue | none | last night; this is pop; i don't need anyone row 7 : 2007 | "again" | the deep blue | none | again (acoustic) row 8 : 2007 | "ch v fd (deep blue remixes)" | non-album single | none | dawn treader (fredmix); it isn't over (fredmix) row 9 : 2009 | "white" | new worlds | none | white (squarepusher remix); white (adem remix); white (heartbeat remix) row 10 : 2009 | "alexander" | new worlds | none | alexander (radio edit); alexander (blacknred remix) | col : album row 1 : grey will fade row 2 : grey will fade row 3 : grey will fade row 4 : the deep blue row 5 : the deep blue row 6 : the deep blue row 7 : the deep blue row 8 : non-album single row 9 : new worlds row 10 : new worlds | select album where b-sides = b-sides <table_name> : table \begin{tabular}{llllll}
\toprule
& year & title & album & uk & b-sides \\
\midrule
0 & 2004 & "kim wilde" (download-only) & grey will fade & none & none \\
1 & 2004 & "summer" & grey will fade & 31 & commodore; smut \\
2 & 2005 & "bastardo" & grey will fade & 31 & 3 minutes; i am a kamera \\
3 & 2006 & "behave" & the deep blue & 168 & mr. ed; cousteau (extended version); behave (luke smith clor remix) \\
4 & 2007 & "i want you to know" & the deep blue & 108 & sister universe; suspiria \\
5 & 2007 & "siberia" & the deep blue & none & last night; this is pop; i don't need anyone \\
6 & 2007 & "again" & the deep blue & none & again (acoustic) \\
7 & 2007 & "ch v fd (deep blue remixes)" & non-album single & none & dawn treader (fredmix); it isn't over (fredmix) \\
8 & 2009 & "white" & new worlds & none & white (squarepusher remix); white (adem remix); white (heartbeat remix) \\
9 & 2009 & "alexander" & new worlds & none & alexander (radio edit); alexander (blacknred remix) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& album \\
\midrule
0 & grey will fade \\
1 & grey will fade \\
2 & grey will fade \\
3 & the deep blue \\
4 & the deep blue \\
5 & the deep blue \\
6 & the deep blue \\
7 & non-album single \\
8 & new worlds \\
9 & new worlds \\
\bottomrule
\end{tabular}
| select album where b-sides = b-sides <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>album</th>
<th>uk</th>
<th>b-sides</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004</td>
<td>"kim wilde" (download-only)</td>
<td>grey will fade</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2004</td>
<td>"summer"</td>
<td>grey will fade</td>
<td>31</td>
<td>commodore; smut</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>"bastardo"</td>
<td>grey will fade</td>
<td>31</td>
<td>3 minutes; i am a kamera</td>
</tr>
<tr>
<th>3</th>
<td>2006</td>
<td>"behave"</td>
<td>the deep blue</td>
<td>168</td>
<td>mr. ed; cousteau (extended version); behave (luke smith clor remix)</td>
</tr>
<tr>
<th>4</th>
<td>2007</td>
<td>"i want you to know"</td>
<td>the deep blue</td>
<td>108</td>
<td>sister universe; suspiria</td>
</tr>
<tr>
<th>5</th>
<td>2007</td>
<td>"siberia"</td>
<td>the deep blue</td>
<td>none</td>
<td>last night; this is pop; i don't need anyone</td>
</tr>
<tr>
<th>6</th>
<td>2007</td>
<td>"again"</td>
<td>the deep blue</td>
<td>none</td>
<td>again (acoustic)</td>
</tr>
<tr>
<th>7</th>
<td>2007</td>
<td>"ch v fd (deep blue remixes)"</td>
<td>non-album single</td>
<td>none</td>
<td>dawn treader (fredmix); it isn't over (fredmix)</td>
</tr>
<tr>
<th>8</th>
<td>2009</td>
<td>"white"</td>
<td>new worlds</td>
<td>none</td>
<td>white (squarepusher remix); white (adem remix); white (heartbeat remix)</td>
</tr>
<tr>
<th>9</th>
<td>2009</td>
<td>"alexander"</td>
<td>new worlds</td>
<td>none</td>
<td>alexander (radio edit); alexander (blacknred remix)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>grey will fade</td>
</tr>
<tr>
<th>1</th>
<td>grey will fade</td>
</tr>
<tr>
<th>2</th>
<td>grey will fade</td>
</tr>
<tr>
<th>3</th>
<td>the deep blue</td>
</tr>
<tr>
<th>4</th>
<td>the deep blue</td>
</tr>
<tr>
<th>5</th>
<td>the deep blue</td>
</tr>
<tr>
<th>6</th>
<td>the deep blue</td>
</tr>
<tr>
<th>7</th>
<td>non-album single</td>
</tr>
<tr>
<th>8</th>
<td>new worlds</td>
</tr>
<tr>
<th>9</th>
<td>new worlds</td>
</tr>
</tbody>
</table> | select album where b-sides = b-sides <table_name> : table | | year | title | album | uk | b-sides |
|---:|-------:|:------------------------------|:-----------------|:-----|:------------------------------------------------------------------------|
| 0 | 2004 | "kim wilde" (download-only) | grey will fade | none | none |
| 1 | 2004 | "summer" | grey will fade | 31 | commodore; smut |
| 2 | 2005 | "bastardo" | grey will fade | 31 | 3 minutes; i am a kamera |
| 3 | 2006 | "behave" | the deep blue | 168 | mr. ed; cousteau (extended version); behave (luke smith clor remix) |
| 4 | 2007 | "i want you to know" | the deep blue | 108 | sister universe; suspiria |
| 5 | 2007 | "siberia" | the deep blue | none | last night; this is pop; i don't need anyone |
| 6 | 2007 | "again" | the deep blue | none | again (acoustic) |
| 7 | 2007 | "ch v fd (deep blue remixes)" | non-album single | none | dawn treader (fredmix); it isn't over (fredmix) |
| 8 | 2009 | "white" | new worlds | none | white (squarepusher remix); white (adem remix); white (heartbeat remix) |
| 9 | 2009 | "alexander" | new worlds | none | alexander (radio edit); alexander (blacknred remix) | | | | album |
|---:|:-----------------|
| 0 | grey will fade |
| 1 | grey will fade |
| 2 | grey will fade |
| 3 | the deep blue |
| 4 | the deep blue |
| 5 | the deep blue |
| 6 | the deep blue |
| 7 | non-album single |
| 8 | new worlds |
| 9 | new worlds | | [
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select name where name = 'henry schulte' col : name | title | first year in this position | years at nebraska | alma mater row 1 : biff jones | head coach | 1937 | 1937-1941 | army row 2 : henry schulte | lineman coach | 1931 | 1919-1924, 1931-1937 | michigan row 3 : ed weir | freshmen coach | 1929 | 1926, 1929-1937, 1943 | nebraska row 4 : w. harold browne | assistant coach | 1930 | 1930-1940 | none row 5 : roy lyman | none | 1936 | 1936-1941 | none row 6 : adolph j. lewandowski | none | 1937 | 1937-1944 | nebraska row 7 : jerry adams | none | none | 1937 | none row 8 : charles armstrong | none | 1937 | 1937-1942, 1944 | none | col : name row 1 : henry schulte | select name where name = 'henry schulte' <table_name> : table \begin{tabular}{llllll}
\toprule
& name & title & first year in this position & years at nebraska & alma mater \\
\midrule
0 & biff jones & head coach & 1937 & 1937-1941 & army \\
1 & henry schulte & lineman coach & 1931 & 1919-1924, 1931-1937 & michigan \\
2 & ed weir & freshmen coach & 1929 & 1926, 1929-1937, 1943 & nebraska \\
3 & w. harold browne & assistant coach & 1930 & 1930-1940 & none \\
4 & roy lyman & none & 1936 & 1936-1941 & none \\
5 & adolph j. lewandowski & none & 1937 & 1937-1944 & nebraska \\
6 & jerry adams & none & none & 1937 & none \\
7 & charles armstrong & none & 1937 & 1937-1942, 1944 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& name \\
\midrule
0 & henry schulte \\
\bottomrule
\end{tabular}
| select name where name = 'henry schulte' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>title</th>
<th>first year in this position</th>
<th>years at nebraska</th>
<th>alma mater</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>biff jones</td>
<td>head coach</td>
<td>1937</td>
<td>1937-1941</td>
<td>army</td>
</tr>
<tr>
<th>1</th>
<td>henry schulte</td>
<td>lineman coach</td>
<td>1931</td>
<td>1919-1924, 1931-1937</td>
<td>michigan</td>
</tr>
<tr>
<th>2</th>
<td>ed weir</td>
<td>freshmen coach</td>
<td>1929</td>
<td>1926, 1929-1937, 1943</td>
<td>nebraska</td>
</tr>
<tr>
<th>3</th>
<td>w. harold browne</td>
<td>assistant coach</td>
<td>1930</td>
<td>1930-1940</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>roy lyman</td>
<td>none</td>
<td>1936</td>
<td>1936-1941</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>adolph j. lewandowski</td>
<td>none</td>
<td>1937</td>
<td>1937-1944</td>
<td>nebraska</td>
</tr>
<tr>
<th>6</th>
<td>jerry adams</td>
<td>none</td>
<td>none</td>
<td>1937</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>charles armstrong</td>
<td>none</td>
<td>1937</td>
<td>1937-1942, 1944</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>henry schulte</td>
</tr>
</tbody>
</table> | select name where name = 'henry schulte' <table_name> : table | | name | title | first year in this position | years at nebraska | alma mater |
|---:|:----------------------|:----------------|:------------------------------|:----------------------|:-------------|
| 0 | biff jones | head coach | 1937 | 1937-1941 | army |
| 1 | henry schulte | lineman coach | 1931 | 1919-1924, 1931-1937 | michigan |
| 2 | ed weir | freshmen coach | 1929 | 1926, 1929-1937, 1943 | nebraska |
| 3 | w. harold browne | assistant coach | 1930 | 1930-1940 | none |
| 4 | roy lyman | none | 1936 | 1936-1941 | none |
| 5 | adolph j. lewandowski | none | 1937 | 1937-1944 | nebraska |
| 6 | jerry adams | none | none | 1937 | none |
| 7 | charles armstrong | none | 1937 | 1937-1942, 1944 | none | | | | name |
|---:|:--------------|
| 0 | henry schulte | | [
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select count ( hanyu pinyin ) where area (km2) = 1108 col : category | # | name | hanzi | hanyu pinyin | population (2010 census) | area (km2) | density (/km2) row 1 : city proper | 1 | jianghai district | 江海区 | jianghai qu | 254365 | 107 | 2377.24 row 2 : city proper | 2 | pengjiang district | 蓬江区 | pengjiang qu | 719120 | 325 | 2212.67 row 3 : city proper | 3 | xinhui district | 新会区 | xinhui qu | 849155 | 1260 | 673.93 row 4 : satellite cities | 4 | enping | 恩平市 | enping shi | 492814 | 1698 | 290.23 row 5 : satellite cities | 5 | taishan | 台山市 | taishan shi | 941087 | 3286 | 286.39 row 6 : satellite cities | 6 | kaiping | 开平市 | kaiping shi | 697395 | 1659 | 420.37 row 7 : satellite cities | 7 | heshan | 鹤山市 | heshan shi | 494935 | 1108 | 446.69 | col : count ( "hanyu pinyin" ) row 1 : 1 | select count ( hanyu pinyin ) where area (km2) = 1108 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& category & # & name & hanzi & hanyu pinyin & population (2010 census) & area (km2) & density (/km2) \\
\midrule
0 & city proper & 1 & jianghai district & 江海区 & jianghai qu & 254365 & 107 & 2377.24 \\
1 & city proper & 2 & pengjiang district & 蓬江区 & pengjiang qu & 719120 & 325 & 2212.67 \\
2 & city proper & 3 & xinhui district & 新会区 & xinhui qu & 849155 & 1260 & 673.93 \\
3 & satellite cities & 4 & enping & 恩平市 & enping shi & 492814 & 1698 & 290.23 \\
4 & satellite cities & 5 & taishan & 台山市 & taishan shi & 941087 & 3286 & 286.39 \\
5 & satellite cities & 6 & kaiping & 开平市 & kaiping shi & 697395 & 1659 & 420.37 \\
6 & satellite cities & 7 & heshan & 鹤山市 & heshan shi & 494935 & 1108 & 446.69 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "hanyu pinyin" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( hanyu pinyin ) where area (km2) = 1108 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>category</th>
<th>#</th>
<th>name</th>
<th>hanzi</th>
<th>hanyu pinyin</th>
<th>population (2010 census)</th>
<th>area (km2)</th>
<th>density (/km2)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>city proper</td>
<td>1</td>
<td>jianghai district</td>
<td>江海区</td>
<td>jianghai qu</td>
<td>254365</td>
<td>107</td>
<td>2377.24</td>
</tr>
<tr>
<th>1</th>
<td>city proper</td>
<td>2</td>
<td>pengjiang district</td>
<td>蓬江区</td>
<td>pengjiang qu</td>
<td>719120</td>
<td>325</td>
<td>2212.67</td>
</tr>
<tr>
<th>2</th>
<td>city proper</td>
<td>3</td>
<td>xinhui district</td>
<td>新会区</td>
<td>xinhui qu</td>
<td>849155</td>
<td>1260</td>
<td>673.93</td>
</tr>
<tr>
<th>3</th>
<td>satellite cities</td>
<td>4</td>
<td>enping</td>
<td>恩平市</td>
<td>enping shi</td>
<td>492814</td>
<td>1698</td>
<td>290.23</td>
</tr>
<tr>
<th>4</th>
<td>satellite cities</td>
<td>5</td>
<td>taishan</td>
<td>台山市</td>
<td>taishan shi</td>
<td>941087</td>
<td>3286</td>
<td>286.39</td>
</tr>
<tr>
<th>5</th>
<td>satellite cities</td>
<td>6</td>
<td>kaiping</td>
<td>开平市</td>
<td>kaiping shi</td>
<td>697395</td>
<td>1659</td>
<td>420.37</td>
</tr>
<tr>
<th>6</th>
<td>satellite cities</td>
<td>7</td>
<td>heshan</td>
<td>鹤山市</td>
<td>heshan shi</td>
<td>494935</td>
<td>1108</td>
<td>446.69</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "hanyu pinyin" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( hanyu pinyin ) where area (km2) = 1108 <table_name> : table | | category | # | name | hanzi | hanyu pinyin | population (2010 census) | area (km2) | density (/km2) |
|---:|:-----------------|----:|:-------------------|:--------|:---------------|---------------------------:|-------------:|-----------------:|
| 0 | city proper | 1 | jianghai district | 江海区 | jianghai qu | 254365 | 107 | 2377.24 |
| 1 | city proper | 2 | pengjiang district | 蓬江区 | pengjiang qu | 719120 | 325 | 2212.67 |
| 2 | city proper | 3 | xinhui district | 新会区 | xinhui qu | 849155 | 1260 | 673.93 |
| 3 | satellite cities | 4 | enping | 恩平市 | enping shi | 492814 | 1698 | 290.23 |
| 4 | satellite cities | 5 | taishan | 台山市 | taishan shi | 941087 | 3286 | 286.39 |
| 5 | satellite cities | 6 | kaiping | 开平市 | kaiping shi | 697395 | 1659 | 420.37 |
| 6 | satellite cities | 7 | heshan | 鹤山市 | heshan shi | 494935 | 1108 | 446.69 | | | | count ( "hanyu pinyin" ) |
|---:|---------------------------:|
| 0 | 1 | | [
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select count ( party ) where ∆% = '5.78' col : party | candidate | votes | % | ∆% row 1 : conservative | joe daniel | 14422 | 36.78 | 5.78 row 2 : liberal | yasmin ratansi | 13552 | 34.56 | -13.51 row 3 : new democratic | mary trapani hynes | 9878 | 25.19 | 11.87 row 4 : green | akil sadikali | 1114 | 2.84 | -4.05 row 5 : christian heritage | ryan kidd | 246 | 0.63 | -0.07 row 6 : total valid votes | total valid votes | 39212 | 100 | none row 7 : total rejected ballots | total rejected ballots | 218 | 0.55 | none row 8 : turnout | turnout | 39430 | 57.24 | none row 9 : eligible voters | eligible voters | 68890 | none | none | col : count ( "party" ) row 1 : 1 | select count ( party ) where ∆% = '5.78' <table_name> : table \begin{tabular}{llllll}
\toprule
& party & candidate & votes & % & ∆% \\
\midrule
0 & conservative & joe daniel & 14422 & 36.78 & 5.78 \\
1 & liberal & yasmin ratansi & 13552 & 34.56 & -13.51 \\
2 & new democratic & mary trapani hynes & 9878 & 25.19 & 11.87 \\
3 & green & akil sadikali & 1114 & 2.84 & -4.05 \\
4 & christian heritage & ryan kidd & 246 & 0.63 & -0.07 \\
5 & total valid votes & total valid votes & 39212 & 100 & none \\
6 & total rejected ballots & total rejected ballots & 218 & 0.55 & none \\
7 & turnout & turnout & 39430 & 57.24 & none \\
8 & eligible voters & eligible voters & 68890 & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "party" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( party ) where ∆% = '5.78' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
<th>candidate</th>
<th>votes</th>
<th>%</th>
<th>∆%</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>conservative</td>
<td>joe daniel</td>
<td>14422</td>
<td>36.78</td>
<td>5.78</td>
</tr>
<tr>
<th>1</th>
<td>liberal</td>
<td>yasmin ratansi</td>
<td>13552</td>
<td>34.56</td>
<td>-13.51</td>
</tr>
<tr>
<th>2</th>
<td>new democratic</td>
<td>mary trapani hynes</td>
<td>9878</td>
<td>25.19</td>
<td>11.87</td>
</tr>
<tr>
<th>3</th>
<td>green</td>
<td>akil sadikali</td>
<td>1114</td>
<td>2.84</td>
<td>-4.05</td>
</tr>
<tr>
<th>4</th>
<td>christian heritage</td>
<td>ryan kidd</td>
<td>246</td>
<td>0.63</td>
<td>-0.07</td>
</tr>
<tr>
<th>5</th>
<td>total valid votes</td>
<td>total valid votes</td>
<td>39212</td>
<td>100</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>total rejected ballots</td>
<td>total rejected ballots</td>
<td>218</td>
<td>0.55</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>turnout</td>
<td>turnout</td>
<td>39430</td>
<td>57.24</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>eligible voters</td>
<td>eligible voters</td>
<td>68890</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 ( "party" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( party ) where ∆% = '5.78' <table_name> : table | | party | candidate | votes | % | ∆% |
|---:|:-----------------------|:-----------------------|--------:|:------|:-------|
| 0 | conservative | joe daniel | 14422 | 36.78 | 5.78 |
| 1 | liberal | yasmin ratansi | 13552 | 34.56 | -13.51 |
| 2 | new democratic | mary trapani hynes | 9878 | 25.19 | 11.87 |
| 3 | green | akil sadikali | 1114 | 2.84 | -4.05 |
| 4 | christian heritage | ryan kidd | 246 | 0.63 | -0.07 |
| 5 | total valid votes | total valid votes | 39212 | 100 | none |
| 6 | total rejected ballots | total rejected ballots | 218 | 0.55 | none |
| 7 | turnout | turnout | 39430 | 57.24 | none |
| 8 | eligible voters | eligible voters | 68890 | none | none | | | | count ( "party" ) |
|---:|--------------------:|
| 0 | 1 | | [
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] |
select count ( record ) where record = '15-2' 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 : count ( "record" ) row 1 : 1 | select count ( record ) where record = '15-2' <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
& count ( "record" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( record ) where record = '15-2' <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>count ( "record" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( record ) where record = '15-2' <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 | | | | count ( "record" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select award where year = 2009 col : year | award | category | nominated work | result row 1 : 2005 | mbc drama awards | best new actor | be strong, geum-soon! | won row 2 : 2005 | mbc drama awards | excellence award, actor | be strong, geum-soon! | won row 3 : 2007 | kbs drama awards | best couple award with han ji-min | capital scandal | won row 4 : 2007 | kbs drama awards | excellence award, actor in a miniseries | capital scandal | won row 5 : 2008 | 44th baeksang arts awards | popularity award | hong gil-dong | won row 6 : 2008 | 28th korean association of film critics awards | best new actor | rough cut | won row 7 : 2008 | 29th blue dragon film awards | best new actor | rough cut | won row 8 : 2008 | 7th korean film awards | best new actor | rough cut | won row 9 : 2008 | kbs drama awards | best couple award with sung yu-ri | hong gil-dong | won row 10 : 2008 | kbs drama awards | netizen award | hong gil-dong | won row 11 : 2009 | 45th baeksang arts awards | best new actor | rough cut | won row 12 : 2009 | 10th pusan film critics awards | best new actor | rough cut | won row 13 : 2009 | 46th grand bell awards | best new actor | my girlfriend is an agent | won row 14 : 2009 | 5th university film festival of korea | best new actor | my girlfriend is an agent | won row 15 : 2011 | 6th seoul international drama awards | outstanding korean actor | coffee house | nominated row 16 : 2011 | sbs drama awards | excellence award, actor in a special planning drama | lie to me | nominated row 17 : 2013 | sbs drama awards | top excellence award, actor in a drama special | incarnation of money | nominated row 18 : 2014 | 9th asia model festival awards | asia star award | none | won | col : award row 1 : 45th baeksang arts awards row 2 : 10th pusan film critics awards row 3 : 46th grand bell awards row 4 : 5th university film festival of korea | select award where year = 2009 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & award & category & nominated work & result \\
\midrule
0 & 2005 & mbc drama awards & best new actor & be strong, geum-soon! & won \\
1 & 2005 & mbc drama awards & excellence award, actor & be strong, geum-soon! & won \\
2 & 2007 & kbs drama awards & best couple award with han ji-min & capital scandal & won \\
3 & 2007 & kbs drama awards & excellence award, actor in a miniseries & capital scandal & won \\
4 & 2008 & 44th baeksang arts awards & popularity award & hong gil-dong & won \\
5 & 2008 & 28th korean association of film critics awards & best new actor & rough cut & won \\
6 & 2008 & 29th blue dragon film awards & best new actor & rough cut & won \\
7 & 2008 & 7th korean film awards & best new actor & rough cut & won \\
8 & 2008 & kbs drama awards & best couple award with sung yu-ri & hong gil-dong & won \\
9 & 2008 & kbs drama awards & netizen award & hong gil-dong & won \\
10 & 2009 & 45th baeksang arts awards & best new actor & rough cut & won \\
11 & 2009 & 10th pusan film critics awards & best new actor & rough cut & won \\
12 & 2009 & 46th grand bell awards & best new actor & my girlfriend is an agent & won \\
13 & 2009 & 5th university film festival of korea & best new actor & my girlfriend is an agent & won \\
14 & 2011 & 6th seoul international drama awards & outstanding korean actor & coffee house & nominated \\
15 & 2011 & sbs drama awards & excellence award, actor in a special planning drama & lie to me & nominated \\
16 & 2013 & sbs drama awards & top excellence award, actor in a drama special & incarnation of money & nominated \\
17 & 2014 & 9th asia model festival awards & asia star award & none & won \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& award \\
\midrule
0 & 45th baeksang arts awards \\
1 & 10th pusan film critics awards \\
2 & 46th grand bell awards \\
3 & 5th university film festival of korea \\
\bottomrule
\end{tabular}
| select award where year = 2009 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>award</th>
<th>category</th>
<th>nominated work</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2005</td>
<td>mbc drama awards</td>
<td>best new actor</td>
<td>be strong, geum-soon!</td>
<td>won</td>
</tr>
<tr>
<th>1</th>
<td>2005</td>
<td>mbc drama awards</td>
<td>excellence award, actor</td>
<td>be strong, geum-soon!</td>
<td>won</td>
</tr>
<tr>
<th>2</th>
<td>2007</td>
<td>kbs drama awards</td>
<td>best couple award with han ji-min</td>
<td>capital scandal</td>
<td>won</td>
</tr>
<tr>
<th>3</th>
<td>2007</td>
<td>kbs drama awards</td>
<td>excellence award, actor in a miniseries</td>
<td>capital scandal</td>
<td>won</td>
</tr>
<tr>
<th>4</th>
<td>2008</td>
<td>44th baeksang arts awards</td>
<td>popularity award</td>
<td>hong gil-dong</td>
<td>won</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>28th korean association of film critics awards</td>
<td>best new actor</td>
<td>rough cut</td>
<td>won</td>
</tr>
<tr>
<th>6</th>
<td>2008</td>
<td>29th blue dragon film awards</td>
<td>best new actor</td>
<td>rough cut</td>
<td>won</td>
</tr>
<tr>
<th>7</th>
<td>2008</td>
<td>7th korean film awards</td>
<td>best new actor</td>
<td>rough cut</td>
<td>won</td>
</tr>
<tr>
<th>8</th>
<td>2008</td>
<td>kbs drama awards</td>
<td>best couple award with sung yu-ri</td>
<td>hong gil-dong</td>
<td>won</td>
</tr>
<tr>
<th>9</th>
<td>2008</td>
<td>kbs drama awards</td>
<td>netizen award</td>
<td>hong gil-dong</td>
<td>won</td>
</tr>
<tr>
<th>10</th>
<td>2009</td>
<td>45th baeksang arts awards</td>
<td>best new actor</td>
<td>rough cut</td>
<td>won</td>
</tr>
<tr>
<th>11</th>
<td>2009</td>
<td>10th pusan film critics awards</td>
<td>best new actor</td>
<td>rough cut</td>
<td>won</td>
</tr>
<tr>
<th>12</th>
<td>2009</td>
<td>46th grand bell awards</td>
<td>best new actor</td>
<td>my girlfriend is an agent</td>
<td>won</td>
</tr>
<tr>
<th>13</th>
<td>2009</td>
<td>5th university film festival of korea</td>
<td>best new actor</td>
<td>my girlfriend is an agent</td>
<td>won</td>
</tr>
<tr>
<th>14</th>
<td>2011</td>
<td>6th seoul international drama awards</td>
<td>outstanding korean actor</td>
<td>coffee house</td>
<td>nominated</td>
</tr>
<tr>
<th>15</th>
<td>2011</td>
<td>sbs drama awards</td>
<td>excellence award, actor in a special planning drama</td>
<td>lie to me</td>
<td>nominated</td>
</tr>
<tr>
<th>16</th>
<td>2013</td>
<td>sbs drama awards</td>
<td>top excellence award, actor in a drama special</td>
<td>incarnation of money</td>
<td>nominated</td>
</tr>
<tr>
<th>17</th>
<td>2014</td>
<td>9th asia model festival awards</td>
<td>asia star award</td>
<td>none</td>
<td>won</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>award</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>45th baeksang arts awards</td>
</tr>
<tr>
<th>1</th>
<td>10th pusan film critics awards</td>
</tr>
<tr>
<th>2</th>
<td>46th grand bell awards</td>
</tr>
<tr>
<th>3</th>
<td>5th university film festival of korea</td>
</tr>
</tbody>
</table> | select award where year = 2009 <table_name> : table | | year | award | category | nominated work | result |
|---:|-------:|:-----------------------------------------------|:----------------------------------------------------|:--------------------------|:----------|
| 0 | 2005 | mbc drama awards | best new actor | be strong, geum-soon! | won |
| 1 | 2005 | mbc drama awards | excellence award, actor | be strong, geum-soon! | won |
| 2 | 2007 | kbs drama awards | best couple award with han ji-min | capital scandal | won |
| 3 | 2007 | kbs drama awards | excellence award, actor in a miniseries | capital scandal | won |
| 4 | 2008 | 44th baeksang arts awards | popularity award | hong gil-dong | won |
| 5 | 2008 | 28th korean association of film critics awards | best new actor | rough cut | won |
| 6 | 2008 | 29th blue dragon film awards | best new actor | rough cut | won |
| 7 | 2008 | 7th korean film awards | best new actor | rough cut | won |
| 8 | 2008 | kbs drama awards | best couple award with sung yu-ri | hong gil-dong | won |
| 9 | 2008 | kbs drama awards | netizen award | hong gil-dong | won |
| 10 | 2009 | 45th baeksang arts awards | best new actor | rough cut | won |
| 11 | 2009 | 10th pusan film critics awards | best new actor | rough cut | won |
| 12 | 2009 | 46th grand bell awards | best new actor | my girlfriend is an agent | won |
| 13 | 2009 | 5th university film festival of korea | best new actor | my girlfriend is an agent | won |
| 14 | 2011 | 6th seoul international drama awards | outstanding korean actor | coffee house | nominated |
| 15 | 2011 | sbs drama awards | excellence award, actor in a special planning drama | lie to me | nominated |
| 16 | 2013 | sbs drama awards | top excellence award, actor in a drama special | incarnation of money | nominated |
| 17 | 2014 | 9th asia model festival awards | asia star award | none | won | | | | award |
|---:|:--------------------------------------|
| 0 | 45th baeksang arts awards |
| 1 | 10th pusan film critics awards |
| 2 | 46th grand bell awards |
| 3 | 5th university film festival of korea | | [
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select count ( notes ) where pos. = '1a estatal' col : season | tier | division | pos. | notes row 1 : 2002-03 | 3 | 1a estatal | 9th | none row 2 : 2003-04 | 3 | 1a estatal | 3rd | none row 3 : 2004-05 | 3 | 1a estatal | 3rd | none row 4 : 2005-06 | 3 | 1a estatal | 2nd | promoted row 5 : 2006-07 | 2 | honor b | 10th | none row 6 : 2007-08 | 2 | honor b | 11th | none row 7 : 2008-09 | 2 | honor b | 11th | none row 8 : 2009-10 | 2 | plata | 5th | none row 9 : 2010-11 | 2 | plata | 9th | none row 10 : 2011-12 | 2 | plata | 2nd | promoted row 11 : 2012-13 | 1 | asobal | 16th | relegated row 12 : 2013-14 | 2 | plata | none | none | col : count ( "notes" ) row 1 : 0 | select count ( notes ) where pos. = '1a estatal' <table_name> : table \begin{tabular}{llllll}
\toprule
& season & tier & division & pos. & notes \\
\midrule
0 & 2002-03 & 3 & 1a estatal & 9th & none \\
1 & 2003-04 & 3 & 1a estatal & 3rd & none \\
2 & 2004-05 & 3 & 1a estatal & 3rd & none \\
3 & 2005-06 & 3 & 1a estatal & 2nd & promoted \\
4 & 2006-07 & 2 & honor b & 10th & none \\
5 & 2007-08 & 2 & honor b & 11th & none \\
6 & 2008-09 & 2 & honor b & 11th & none \\
7 & 2009-10 & 2 & plata & 5th & none \\
8 & 2010-11 & 2 & plata & 9th & none \\
9 & 2011-12 & 2 & plata & 2nd & promoted \\
10 & 2012-13 & 1 & asobal & 16th & relegated \\
11 & 2013-14 & 2 & plata & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "notes" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( notes ) where pos. = '1a estatal' <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>pos.</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2002-03</td>
<td>3</td>
<td>1a estatal</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2003-04</td>
<td>3</td>
<td>1a estatal</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2004-05</td>
<td>3</td>
<td>1a estatal</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2005-06</td>
<td>3</td>
<td>1a estatal</td>
<td>2nd</td>
<td>promoted</td>
</tr>
<tr>
<th>4</th>
<td>2006-07</td>
<td>2</td>
<td>honor b</td>
<td>10th</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2007-08</td>
<td>2</td>
<td>honor b</td>
<td>11th</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2008-09</td>
<td>2</td>
<td>honor b</td>
<td>11th</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>2009-10</td>
<td>2</td>
<td>plata</td>
<td>5th</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2010-11</td>
<td>2</td>
<td>plata</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>2011-12</td>
<td>2</td>
<td>plata</td>
<td>2nd</td>
<td>promoted</td>
</tr>
<tr>
<th>10</th>
<td>2012-13</td>
<td>1</td>
<td>asobal</td>
<td>16th</td>
<td>relegated</td>
</tr>
<tr>
<th>11</th>
<td>2013-14</td>
<td>2</td>
<td>plata</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 ( "notes" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( notes ) where pos. = '1a estatal' <table_name> : table | | season | tier | division | pos. | notes |
|---:|:---------|-------:|:-----------|:-------|:----------|
| 0 | 2002-03 | 3 | 1a estatal | 9th | none |
| 1 | 2003-04 | 3 | 1a estatal | 3rd | none |
| 2 | 2004-05 | 3 | 1a estatal | 3rd | none |
| 3 | 2005-06 | 3 | 1a estatal | 2nd | promoted |
| 4 | 2006-07 | 2 | honor b | 10th | none |
| 5 | 2007-08 | 2 | honor b | 11th | none |
| 6 | 2008-09 | 2 | honor b | 11th | none |
| 7 | 2009-10 | 2 | plata | 5th | none |
| 8 | 2010-11 | 2 | plata | 9th | none |
| 9 | 2011-12 | 2 | plata | 2nd | promoted |
| 10 | 2012-13 | 1 | asobal | 16th | relegated |
| 11 | 2013-14 | 2 | plata | none | none | | | | count ( "notes" ) |
|---:|--------------------:|
| 0 | 0 | | [
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select album where peak chart positions nld = 8 col : title | year | peak chart positions us | peak chart positions us alt. | peak chart positions us main. rock | peak chart positions aus | peak chart positions aut | peak chart positions fin | peak chart positions ger | peak chart positions nld | peak chart positions swi | peak chart positions uk | album row 1 : "toxic" | 1999 | none | none | none | none | none | none | none | none | none | none | the gift of game row 2 : "darkside" | 2000 | none | none | none | none | none | none | none | none | none | none | the gift of game row 3 : "butterfly" | 2000 | 1 | 1 | 21 | 4 | 1 | 2 | 1 | 8 | 1 | 3 | the gift of game row 4 : "revolving door" | 2001 | none | none | none | 76 | 29 | 19 | 26 | 71 | 43 | 23 | the gift of game row 5 : "drowning" | 2002 | none | 24 | 24 | none | 45 | none | 45 | none | none | 50 | darkhorse row 6 : "hurt you so bad" | 2003 | none | none | none | none | none | none | none | none | none | none | darkhorse | col : album row 1 : the gift of game | select album where peak chart positions nld = 8 <table_name> : table \begin{tabular}{llllllllllllll}
\toprule
& title & year & peak chart positions us & peak chart positions us alt. & peak chart positions us main. rock & peak chart positions aus & peak chart positions aut & peak chart positions fin & peak chart positions ger & peak chart positions nld & peak chart positions swi & peak chart positions uk & album \\
\midrule
0 & "toxic" & 1999 & none & none & none & none & none & none & none & none & none & none & the gift of game \\
1 & "darkside" & 2000 & none & none & none & none & none & none & none & none & none & none & the gift of game \\
2 & "butterfly" & 2000 & 1 & 1 & 21 & 4 & 1 & 2 & 1 & 8 & 1 & 3 & the gift of game \\
3 & "revolving door" & 2001 & none & none & none & 76 & 29 & 19 & 26 & 71 & 43 & 23 & the gift of game \\
4 & "drowning" & 2002 & none & 24 & 24 & none & 45 & none & 45 & none & none & 50 & darkhorse \\
5 & "hurt you so bad" & 2003 & none & none & none & none & none & none & none & none & none & none & darkhorse \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& album \\
\midrule
0 & the gift of game \\
\bottomrule
\end{tabular}
| select album where peak chart positions nld = 8 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>title</th>
<th>year</th>
<th>peak chart positions us</th>
<th>peak chart positions us alt.</th>
<th>peak chart positions us main. rock</th>
<th>peak chart positions aus</th>
<th>peak chart positions aut</th>
<th>peak chart positions fin</th>
<th>peak chart positions ger</th>
<th>peak chart positions nld</th>
<th>peak chart positions swi</th>
<th>peak chart positions uk</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>"toxic"</td>
<td>1999</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>the gift of game</td>
</tr>
<tr>
<th>1</th>
<td>"darkside"</td>
<td>2000</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>the gift of game</td>
</tr>
<tr>
<th>2</th>
<td>"butterfly"</td>
<td>2000</td>
<td>1</td>
<td>1</td>
<td>21</td>
<td>4</td>
<td>1</td>
<td>2</td>
<td>1</td>
<td>8</td>
<td>1</td>
<td>3</td>
<td>the gift of game</td>
</tr>
<tr>
<th>3</th>
<td>"revolving door"</td>
<td>2001</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>76</td>
<td>29</td>
<td>19</td>
<td>26</td>
<td>71</td>
<td>43</td>
<td>23</td>
<td>the gift of game</td>
</tr>
<tr>
<th>4</th>
<td>"drowning"</td>
<td>2002</td>
<td>none</td>
<td>24</td>
<td>24</td>
<td>none</td>
<td>45</td>
<td>none</td>
<td>45</td>
<td>none</td>
<td>none</td>
<td>50</td>
<td>darkhorse</td>
</tr>
<tr>
<th>5</th>
<td>"hurt you so bad"</td>
<td>2003</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>darkhorse</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>the gift of game</td>
</tr>
</tbody>
</table> | select album where peak chart positions nld = 8 <table_name> : table | | title | year | peak chart positions us | peak chart positions us alt. | peak chart positions us main. rock | peak chart positions aus | peak chart positions aut | peak chart positions fin | peak chart positions ger | peak chart positions nld | peak chart positions swi | peak chart positions uk | album |
|---:|:------------------|-------:|:--------------------------|:-------------------------------|:-------------------------------------|:---------------------------|:---------------------------|:---------------------------|:---------------------------|:---------------------------|:---------------------------|:--------------------------|:-----------------|
| 0 | "toxic" | 1999 | none | none | none | none | none | none | none | none | none | none | the gift of game |
| 1 | "darkside" | 2000 | none | none | none | none | none | none | none | none | none | none | the gift of game |
| 2 | "butterfly" | 2000 | 1 | 1 | 21 | 4 | 1 | 2 | 1 | 8 | 1 | 3 | the gift of game |
| 3 | "revolving door" | 2001 | none | none | none | 76 | 29 | 19 | 26 | 71 | 43 | 23 | the gift of game |
| 4 | "drowning" | 2002 | none | 24 | 24 | none | 45 | none | 45 | none | none | 50 | darkhorse |
| 5 | "hurt you so bad" | 2003 | none | none | none | none | none | none | none | none | none | none | darkhorse | | | | album |
|---:|:-----------------|
| 0 | the gift of game | | [
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select count ( * ) where competitors = 'oganeditse moseki, johnson kubisa, california molefe, kagiso kilego' col : rank | heat | nation | competitors | time | notes row 1 : 1 | 2 | united states | kelly willie, derrick brew, andrew rock, darold williamson | 2:59.30 | q row 2 : 2 | 2 | nigeria | james godday, musa audu, saul weigopwa, enefiok udo-obong | 3:01.60 | q, sb row 3 : 3 | 2 | bahamas | andrae williams, dennis darling, nathaniel mckinney, christopher brown | 3:01.74 | q, sb row 4 : 4 | 1 | great britain | timothy benjamin, sean baldock, malachi davis, matthew elias | 3:02.40 | q, sb row 5 : 5 | 1 | japan | yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato | 3:02.71 | q row 6 : 6 | 1 | germany | ingo schultz, kamghe gaba, ruwen faller, bastian swillims | 3:02.77 | q row 7 : 7 | 1 | australia | john steffensen, clinton hill, patrick dwyer, mark ormrod | 3:03.06 | q row 8 : 8 | 1 | botswana | oganeditse moseki, johnson kubisa, california molefe, kagiso kilego | 3:03.32 | q, sb row 9 : 9 | 2 | russia | aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko | 3:03.35 | none row 10 : 10 | 2 | poland | piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo | 3:03.69 | none row 11 : 11 | 2 | ukraine | volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup | 3:04.01 | none row 12 : 12 | 1 | greece | stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis | 3:04.27 | sb row 13 : 13 | 1 | france | ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone | 3:04.39 | none row 14 : 14 | 2 | spain | eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina | 3:05.03 | sb row 15 : none | 2 | south africa | marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe | dnf | none row 16 : none | 1 | jamaica | michael campbell, michael blackwood, jermaine gonzales, davian clarke | dsq | none | col : count ( "*" ) row 1 : 1 | select count ( * ) where competitors = 'oganeditse moseki, johnson kubisa, california molefe, kagiso kilego' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & heat & nation & competitors & time & notes \\
\midrule
0 & 1 & 2 & united states & kelly willie, derrick brew, andrew rock, darold williamson & 2:59.30 & q \\
1 & 2 & 2 & nigeria & james godday, musa audu, saul weigopwa, enefiok udo-obong & 3:01.60 & q, sb \\
2 & 3 & 2 & bahamas & andrae williams, dennis darling, nathaniel mckinney, christopher brown & 3:01.74 & q, sb \\
3 & 4 & 1 & great britain & timothy benjamin, sean baldock, malachi davis, matthew elias & 3:02.40 & q, sb \\
4 & 5 & 1 & japan & yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato & 3:02.71 & q \\
5 & 6 & 1 & germany & ingo schultz, kamghe gaba, ruwen faller, bastian swillims & 3:02.77 & q \\
6 & 7 & 1 & australia & john steffensen, clinton hill, patrick dwyer, mark ormrod & 3:03.06 & q \\
7 & 8 & 1 & botswana & oganeditse moseki, johnson kubisa, california molefe, kagiso kilego & 3:03.32 & q, sb \\
8 & 9 & 2 & russia & aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko & 3:03.35 & none \\
9 & 10 & 2 & poland & piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo & 3:03.69 & none \\
10 & 11 & 2 & ukraine & volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup & 3:04.01 & none \\
11 & 12 & 1 & greece & stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis & 3:04.27 & sb \\
12 & 13 & 1 & france & ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone & 3:04.39 & none \\
13 & 14 & 2 & spain & eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina & 3:05.03 & sb \\
14 & none & 2 & south africa & marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe & dnf & none \\
15 & none & 1 & jamaica & michael campbell, michael blackwood, jermaine gonzales, davian clarke & dsq & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where competitors = 'oganeditse moseki, johnson kubisa, california molefe, kagiso kilego' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>heat</th>
<th>nation</th>
<th>competitors</th>
<th>time</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2</td>
<td>united states</td>
<td>kelly willie, derrick brew, andrew rock, darold williamson</td>
<td>2:59.30</td>
<td>q</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2</td>
<td>nigeria</td>
<td>james godday, musa audu, saul weigopwa, enefiok udo-obong</td>
<td>3:01.60</td>
<td>q, sb</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2</td>
<td>bahamas</td>
<td>andrae williams, dennis darling, nathaniel mckinney, christopher brown</td>
<td>3:01.74</td>
<td>q, sb</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1</td>
<td>great britain</td>
<td>timothy benjamin, sean baldock, malachi davis, matthew elias</td>
<td>3:02.40</td>
<td>q, sb</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1</td>
<td>japan</td>
<td>yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato</td>
<td>3:02.71</td>
<td>q</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>1</td>
<td>germany</td>
<td>ingo schultz, kamghe gaba, ruwen faller, bastian swillims</td>
<td>3:02.77</td>
<td>q</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>1</td>
<td>australia</td>
<td>john steffensen, clinton hill, patrick dwyer, mark ormrod</td>
<td>3:03.06</td>
<td>q</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>1</td>
<td>botswana</td>
<td>oganeditse moseki, johnson kubisa, california molefe, kagiso kilego</td>
<td>3:03.32</td>
<td>q, sb</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2</td>
<td>russia</td>
<td>aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko</td>
<td>3:03.35</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2</td>
<td>poland</td>
<td>piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo</td>
<td>3:03.69</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>2</td>
<td>ukraine</td>
<td>volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup</td>
<td>3:04.01</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>1</td>
<td>greece</td>
<td>stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis</td>
<td>3:04.27</td>
<td>sb</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>1</td>
<td>france</td>
<td>ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone</td>
<td>3:04.39</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>2</td>
<td>spain</td>
<td>eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina</td>
<td>3:05.03</td>
<td>sb</td>
</tr>
<tr>
<th>14</th>
<td>none</td>
<td>2</td>
<td>south africa</td>
<td>marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe</td>
<td>dnf</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>none</td>
<td>1</td>
<td>jamaica</td>
<td>michael campbell, michael blackwood, jermaine gonzales, davian clarke</td>
<td>dsq</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 competitors = 'oganeditse moseki, johnson kubisa, california molefe, kagiso kilego' <table_name> : table | | rank | heat | nation | competitors | time | notes |
|---:|:-------|-------:|:--------------|:------------------------------------------------------------------------------|:--------|:--------|
| 0 | 1 | 2 | united states | kelly willie, derrick brew, andrew rock, darold williamson | 2:59.30 | q |
| 1 | 2 | 2 | nigeria | james godday, musa audu, saul weigopwa, enefiok udo-obong | 3:01.60 | q, sb |
| 2 | 3 | 2 | bahamas | andrae williams, dennis darling, nathaniel mckinney, christopher brown | 3:01.74 | q, sb |
| 3 | 4 | 1 | great britain | timothy benjamin, sean baldock, malachi davis, matthew elias | 3:02.40 | q, sb |
| 4 | 5 | 1 | japan | yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato | 3:02.71 | q |
| 5 | 6 | 1 | germany | ingo schultz, kamghe gaba, ruwen faller, bastian swillims | 3:02.77 | q |
| 6 | 7 | 1 | australia | john steffensen, clinton hill, patrick dwyer, mark ormrod | 3:03.06 | q |
| 7 | 8 | 1 | botswana | oganeditse moseki, johnson kubisa, california molefe, kagiso kilego | 3:03.32 | q, sb |
| 8 | 9 | 2 | russia | aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko | 3:03.35 | none |
| 9 | 10 | 2 | poland | piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo | 3:03.69 | none |
| 10 | 11 | 2 | ukraine | volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup | 3:04.01 | none |
| 11 | 12 | 1 | greece | stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis | 3:04.27 | sb |
| 12 | 13 | 1 | france | ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone | 3:04.39 | none |
| 13 | 14 | 2 | spain | eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina | 3:05.03 | sb |
| 14 | none | 2 | south africa | marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe | dnf | none |
| 15 | none | 1 | jamaica | michael campbell, michael blackwood, jermaine gonzales, davian clarke | dsq | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( distinct title ) where title = 'self portrait' col : year | title | image | dimensions | collection | comments row 1 : 1942 | assassination of heydrich (c. 1942; originally may have been untitled), oil on canvas on board | view | 61.4 × 76.1 cm. (24.2 × 30 in.) | the national archives, kew, richmond, uk | subject: ss-general reinhard heydrich (1904-1942; operation anthropoid). artwork created for ministry of information during second world war. inf 3/24 row 2 : 1944 | production of tanks (original may have been untitled), oil on canvas | view | 51.3 × 61.5 cm. (20.2 × 24.2 in.) | the national archives, kew, richmond, uk | scene: workers manufacture churchill tanks on a factory production line. artwork created for ministry of information during second world war. inf 3/17 row 3 : 1968 | express engines at tyseley, oil on canvas | view view | 75 × 100 cm. (29.5 × 39.4 in.) | none | scene: rolling stock-london, midland and scottish railway no.5593/45593 jubilee kolhapur and great western railway no.7029 clun castle- at tyseley locomotive works, birmingham, west midlands row 4 : 1972 | field marshall viscount montgomery of alamein, oil on canvas | view | 125 × 100 cm. (49.2 × 39.4 in.) | defence academy of the united kingdom, shrivenham, oxfordshire | subject: field marshal bernard law montgomery (1887-1976), 1st viscount montgomery of alamein, gcb, dso. artwork commissioned by the army staff college, 1971 row 5 : 1971 | sir edward heath | view | 123 × 99 cm. (48.4 × 39 in.) | balliol college, university of oxford, oxford | subject: sir edward heath (1916-2005), kg, organ scholar (1935-1939), honorary fellow (1969), prime minister (1970-1974) row 6 : 1972 | self portrait | none | none | none | none row 7 : none | her majesty the queen with her dogs at frogmore | see cuneo society website | none | none | subject: queen elizabeth ii (b. 1926) row 8 : none | bentley vs the blue train | view see cuneo society website | none | none | scene: 1930 cannes to calais maritime race | col : count ( "distinct title" ) row 1 : 1 | select count ( distinct title ) where title = 'self portrait' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & title & image & dimensions & collection & comments \\
\midrule
0 & 1942 & assassination of heydrich (c. 1942; originally may have been untitled), oil on canvas on board & view & 61.4 × 76.1 cm. (24.2 × 30 in.) & the national archives, kew, richmond, uk & subject: ss-general reinhard heydrich (1904-1942; operation anthropoid). artwork created for ministry of information during second world war. inf 3/24 \\
1 & 1944 & production of tanks (original may have been untitled), oil on canvas & view & 51.3 × 61.5 cm. (20.2 × 24.2 in.) & the national archives, kew, richmond, uk & scene: workers manufacture churchill tanks on a factory production line. artwork created for ministry of information during second world war. inf 3/17 \\
2 & 1968 & express engines at tyseley, oil on canvas & view view & 75 × 100 cm. (29.5 × 39.4 in.) & none & scene: rolling stock-london, midland and scottish railway no.5593/45593 jubilee kolhapur and great western railway no.7029 clun castle- at tyseley locomotive works, birmingham, west midlands \\
3 & 1972 & field marshall viscount montgomery of alamein, oil on canvas & view & 125 × 100 cm. (49.2 × 39.4 in.) & defence academy of the united kingdom, shrivenham, oxfordshire & subject: field marshal bernard law montgomery (1887-1976), 1st viscount montgomery of alamein, gcb, dso. artwork commissioned by the army staff college, 1971 \\
4 & 1971 & sir edward heath & view & 123 × 99 cm. (48.4 × 39 in.) & balliol college, university of oxford, oxford & subject: sir edward heath (1916-2005), kg, organ scholar (1935-1939), honorary fellow (1969), prime minister (1970-1974) \\
5 & 1972 & self portrait & none & none & none & none \\
6 & none & her majesty the queen with her dogs at frogmore & see cuneo society website & none & none & subject: queen elizabeth ii (b. 1926) \\
7 & none & bentley vs the blue train & view see cuneo society website & none & none & scene: 1930 cannes to calais maritime race \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "distinct title" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( distinct title ) where title = 'self portrait' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>image</th>
<th>dimensions</th>
<th>collection</th>
<th>comments</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1942</td>
<td>assassination of heydrich (c. 1942; originally may have been untitled), oil on canvas on board</td>
<td>view</td>
<td>61.4 × 76.1 cm. (24.2 × 30 in.)</td>
<td>the national archives, kew, richmond, uk</td>
<td>subject: ss-general reinhard heydrich (1904-1942; operation anthropoid). artwork created for ministry of information during second world war. inf 3/24</td>
</tr>
<tr>
<th>1</th>
<td>1944</td>
<td>production of tanks (original may have been untitled), oil on canvas</td>
<td>view</td>
<td>51.3 × 61.5 cm. (20.2 × 24.2 in.)</td>
<td>the national archives, kew, richmond, uk</td>
<td>scene: workers manufacture churchill tanks on a factory production line. artwork created for ministry of information during second world war. inf 3/17</td>
</tr>
<tr>
<th>2</th>
<td>1968</td>
<td>express engines at tyseley, oil on canvas</td>
<td>view view</td>
<td>75 × 100 cm. (29.5 × 39.4 in.)</td>
<td>none</td>
<td>scene: rolling stock-london, midland and scottish railway no.5593/45593 jubilee kolhapur and great western railway no.7029 clun castle- at tyseley locomotive works, birmingham, west midlands</td>
</tr>
<tr>
<th>3</th>
<td>1972</td>
<td>field marshall viscount montgomery of alamein, oil on canvas</td>
<td>view</td>
<td>125 × 100 cm. (49.2 × 39.4 in.)</td>
<td>defence academy of the united kingdom, shrivenham, oxfordshire</td>
<td>subject: field marshal bernard law montgomery (1887-1976), 1st viscount montgomery of alamein, gcb, dso. artwork commissioned by the army staff college, 1971</td>
</tr>
<tr>
<th>4</th>
<td>1971</td>
<td>sir edward heath</td>
<td>view</td>
<td>123 × 99 cm. (48.4 × 39 in.)</td>
<td>balliol college, university of oxford, oxford</td>
<td>subject: sir edward heath (1916-2005), kg, organ scholar (1935-1939), honorary fellow (1969), prime minister (1970-1974)</td>
</tr>
<tr>
<th>5</th>
<td>1972</td>
<td>self portrait</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>none</td>
<td>her majesty the queen with her dogs at frogmore</td>
<td>see cuneo society website</td>
<td>none</td>
<td>none</td>
<td>subject: queen elizabeth ii (b. 1926)</td>
</tr>
<tr>
<th>7</th>
<td>none</td>
<td>bentley vs the blue train</td>
<td>view see cuneo society website</td>
<td>none</td>
<td>none</td>
<td>scene: 1930 cannes to calais maritime race</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "distinct title" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( distinct title ) where title = 'self portrait' <table_name> : table | | year | title | image | dimensions | collection | comments |
|---:|:-------|:-----------------------------------------------------------------------------------------------|:-------------------------------|:----------------------------------|:---------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 1942 | assassination of heydrich (c. 1942; originally may have been untitled), oil on canvas on board | view | 61.4 × 76.1 cm. (24.2 × 30 in.) | the national archives, kew, richmond, uk | subject: ss-general reinhard heydrich (1904-1942; operation anthropoid). artwork created for ministry of information during second world war. inf 3/24 |
| 1 | 1944 | production of tanks (original may have been untitled), oil on canvas | view | 51.3 × 61.5 cm. (20.2 × 24.2 in.) | the national archives, kew, richmond, uk | scene: workers manufacture churchill tanks on a factory production line. artwork created for ministry of information during second world war. inf 3/17 |
| 2 | 1968 | express engines at tyseley, oil on canvas | view view | 75 × 100 cm. (29.5 × 39.4 in.) | none | scene: rolling stock-london, midland and scottish railway no.5593/45593 jubilee kolhapur and great western railway no.7029 clun castle- at tyseley locomotive works, birmingham, west midlands |
| 3 | 1972 | field marshall viscount montgomery of alamein, oil on canvas | view | 125 × 100 cm. (49.2 × 39.4 in.) | defence academy of the united kingdom, shrivenham, oxfordshire | subject: field marshal bernard law montgomery (1887-1976), 1st viscount montgomery of alamein, gcb, dso. artwork commissioned by the army staff college, 1971 |
| 4 | 1971 | sir edward heath | view | 123 × 99 cm. (48.4 × 39 in.) | balliol college, university of oxford, oxford | subject: sir edward heath (1916-2005), kg, organ scholar (1935-1939), honorary fellow (1969), prime minister (1970-1974) |
| 5 | 1972 | self portrait | none | none | none | none |
| 6 | none | her majesty the queen with her dogs at frogmore | see cuneo society website | none | none | subject: queen elizabeth ii (b. 1926) |
| 7 | none | bentley vs the blue train | view see cuneo society website | none | none | scene: 1930 cannes to calais maritime race | | | | count ( "distinct title" ) |
|---:|-----------------------------:|
| 0 | 1 | | [
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select count ( implied probability ) where encoding = 0 col : number | encoding | implied probability row 1 : 1 = 20 + 0 | 1 | 1/2 row 2 : 2 = 21 + 0 | 10 | 1/8 row 3 : 3 = 21 + 1 | 11 | 1/8 row 4 : 4 = 22 + 0 | 100 | 1/32 row 5 : 5 = 22 + 1 | 101 | 1/32 row 6 : 6 = 22 + 2 | 110 | 1/32 row 7 : 7 = 22 + 3 | 111 | 1/32 row 8 : 8 = 23 + 0 | 1000 | 1/128 row 9 : 9 = 23 + 1 | 1001 | 1/128 row 10 : 10 = 23 + 2 | 1010 | 1/128 row 11 : 11 = 23 + 3 | 1011 | 1/128 row 12 : 12 = 23 + 4 | 1100 | 1/128 row 13 : 13 = 23 + 5 | 1101 | 1/128 row 14 : 14 = 23 + 6 | 1110 | 1/128 row 15 : 15 = 23 + 7 | 1111 | 1/128 row 16 : 16 = 24 + 0 | 10000 | 1/512 row 17 : 17 = 24 + 1 | 10001 | 1/512 | col : count ( "implied probability" ) row 1 : 0 | select count ( implied probability ) where encoding = 0 <table_name> : table \begin{tabular}{llll}
\toprule
& number & encoding & implied probability \\
\midrule
0 & 1 = 20 + 0 & 1 & 1/2 \\
1 & 2 = 21 + 0 & 10 & 1/8 \\
2 & 3 = 21 + 1 & 11 & 1/8 \\
3 & 4 = 22 + 0 & 100 & 1/32 \\
4 & 5 = 22 + 1 & 101 & 1/32 \\
5 & 6 = 22 + 2 & 110 & 1/32 \\
6 & 7 = 22 + 3 & 111 & 1/32 \\
7 & 8 = 23 + 0 & 1000 & 1/128 \\
8 & 9 = 23 + 1 & 1001 & 1/128 \\
9 & 10 = 23 + 2 & 1010 & 1/128 \\
10 & 11 = 23 + 3 & 1011 & 1/128 \\
11 & 12 = 23 + 4 & 1100 & 1/128 \\
12 & 13 = 23 + 5 & 1101 & 1/128 \\
13 & 14 = 23 + 6 & 1110 & 1/128 \\
14 & 15 = 23 + 7 & 1111 & 1/128 \\
15 & 16 = 24 + 0 & 10000 & 1/512 \\
16 & 17 = 24 + 1 & 10001 & 1/512 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "implied probability" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( implied probability ) where encoding = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>number</th>
<th>encoding</th>
<th>implied probability</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1 = 20 + 0</td>
<td>1</td>
<td>1/2</td>
</tr>
<tr>
<th>1</th>
<td>2 = 21 + 0</td>
<td>10</td>
<td>1/8</td>
</tr>
<tr>
<th>2</th>
<td>3 = 21 + 1</td>
<td>11</td>
<td>1/8</td>
</tr>
<tr>
<th>3</th>
<td>4 = 22 + 0</td>
<td>100</td>
<td>1/32</td>
</tr>
<tr>
<th>4</th>
<td>5 = 22 + 1</td>
<td>101</td>
<td>1/32</td>
</tr>
<tr>
<th>5</th>
<td>6 = 22 + 2</td>
<td>110</td>
<td>1/32</td>
</tr>
<tr>
<th>6</th>
<td>7 = 22 + 3</td>
<td>111</td>
<td>1/32</td>
</tr>
<tr>
<th>7</th>
<td>8 = 23 + 0</td>
<td>1000</td>
<td>1/128</td>
</tr>
<tr>
<th>8</th>
<td>9 = 23 + 1</td>
<td>1001</td>
<td>1/128</td>
</tr>
<tr>
<th>9</th>
<td>10 = 23 + 2</td>
<td>1010</td>
<td>1/128</td>
</tr>
<tr>
<th>10</th>
<td>11 = 23 + 3</td>
<td>1011</td>
<td>1/128</td>
</tr>
<tr>
<th>11</th>
<td>12 = 23 + 4</td>
<td>1100</td>
<td>1/128</td>
</tr>
<tr>
<th>12</th>
<td>13 = 23 + 5</td>
<td>1101</td>
<td>1/128</td>
</tr>
<tr>
<th>13</th>
<td>14 = 23 + 6</td>
<td>1110</td>
<td>1/128</td>
</tr>
<tr>
<th>14</th>
<td>15 = 23 + 7</td>
<td>1111</td>
<td>1/128</td>
</tr>
<tr>
<th>15</th>
<td>16 = 24 + 0</td>
<td>10000</td>
<td>1/512</td>
</tr>
<tr>
<th>16</th>
<td>17 = 24 + 1</td>
<td>10001</td>
<td>1/512</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "implied probability" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( implied probability ) where encoding = 0 <table_name> : table | | number | encoding | implied probability |
|---:|:------------|-----------:|:----------------------|
| 0 | 1 = 20 + 0 | 1 | 1/2 |
| 1 | 2 = 21 + 0 | 10 | 1/8 |
| 2 | 3 = 21 + 1 | 11 | 1/8 |
| 3 | 4 = 22 + 0 | 100 | 1/32 |
| 4 | 5 = 22 + 1 | 101 | 1/32 |
| 5 | 6 = 22 + 2 | 110 | 1/32 |
| 6 | 7 = 22 + 3 | 111 | 1/32 |
| 7 | 8 = 23 + 0 | 1000 | 1/128 |
| 8 | 9 = 23 + 1 | 1001 | 1/128 |
| 9 | 10 = 23 + 2 | 1010 | 1/128 |
| 10 | 11 = 23 + 3 | 1011 | 1/128 |
| 11 | 12 = 23 + 4 | 1100 | 1/128 |
| 12 | 13 = 23 + 5 | 1101 | 1/128 |
| 13 | 14 = 23 + 6 | 1110 | 1/128 |
| 14 | 15 = 23 + 7 | 1111 | 1/128 |
| 15 | 16 = 24 + 0 | 10000 | 1/512 |
| 16 | 17 = 24 + 1 | 10001 | 1/512 | | | | count ( "implied probability" ) |
|---:|----------------------------------:|
| 0 | 0 | | [
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select count ( results final score ) where date = 'saturday, june 2' col : week | date | kickoff | opponent | results final score | results team record | game site | attendance row 1 : 1 | saturday, april 14 | 7:00 p.m | at rhein fire | w 15-3 | 1-0 | ltu arena | 30355 row 2 : 2 | sunday, april 22 | 4:00 p.m | hamburg sea devils | l 7-16 | 1-1 | olympic stadium | 30657 row 3 : 3 | saturday, april 28 | 6:00 p.m | amsterdam admirals | l 10-14 | 1-2 | olympic stadium | 11942 row 4 : 4 | saturday, may 5 | 6:00 p.m | at cologne centurions | w 31-28 | 2-2 | rheinenergiestadion | 10084 row 5 : 5 | sunday, may 13 | 4:00 p.m | cologne centurions | l 10-24 | 2-3 | olympic stadium | 11995 row 6 : 6 | sunday, may 20 | 5:00 p.m | at frankfurt galaxy | l 7-35 | 2-4 | commerzbank-arena | 30125 row 7 : 7 | saturday, may 26 | 6:00 p.m | at hamburg sea devils | l 7-17 | 2-5 | aol arena | 18337 row 8 : 8 | saturday, june 2 | 6:00 p.m | frankfurt galaxy | l 22-25 | 2-6 | olympic stadium | 11882 row 9 : 9 | friday, june 8 | 7:00 p.m | rhein fire | l 17-24 | 2-7 | olympic stadium | 12114 row 10 : 10 | friday, june 15 | 8:00 p.m | at amsterdam admirals | l 20-21 | 2-8 | olympic stadium | 11893 | col : count ( "results final score" ) row 1 : 1 | select count ( results final score ) where date = 'saturday, june 2' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& week & date & kickoff & opponent & results final score & results team record & game site & attendance \\
\midrule
0 & 1 & saturday, april 14 & 7:00 p.m & at rhein fire & w 15-3 & 1-0 & ltu arena & 30355 \\
1 & 2 & sunday, april 22 & 4:00 p.m & hamburg sea devils & l 7-16 & 1-1 & olympic stadium & 30657 \\
2 & 3 & saturday, april 28 & 6:00 p.m & amsterdam admirals & l 10-14 & 1-2 & olympic stadium & 11942 \\
3 & 4 & saturday, may 5 & 6:00 p.m & at cologne centurions & w 31-28 & 2-2 & rheinenergiestadion & 10084 \\
4 & 5 & sunday, may 13 & 4:00 p.m & cologne centurions & l 10-24 & 2-3 & olympic stadium & 11995 \\
5 & 6 & sunday, may 20 & 5:00 p.m & at frankfurt galaxy & l 7-35 & 2-4 & commerzbank-arena & 30125 \\
6 & 7 & saturday, may 26 & 6:00 p.m & at hamburg sea devils & l 7-17 & 2-5 & aol arena & 18337 \\
7 & 8 & saturday, june 2 & 6:00 p.m & frankfurt galaxy & l 22-25 & 2-6 & olympic stadium & 11882 \\
8 & 9 & friday, june 8 & 7:00 p.m & rhein fire & l 17-24 & 2-7 & olympic stadium & 12114 \\
9 & 10 & friday, june 15 & 8:00 p.m & at amsterdam admirals & l 20-21 & 2-8 & olympic stadium & 11893 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "results final score" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( results final score ) where date = 'saturday, june 2' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>date</th>
<th>kickoff</th>
<th>opponent</th>
<th>results final score</th>
<th>results team record</th>
<th>game site</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>saturday, april 14</td>
<td>7:00 p.m</td>
<td>at rhein fire</td>
<td>w 15-3</td>
<td>1-0</td>
<td>ltu arena</td>
<td>30355</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>sunday, april 22</td>
<td>4:00 p.m</td>
<td>hamburg sea devils</td>
<td>l 7-16</td>
<td>1-1</td>
<td>olympic stadium</td>
<td>30657</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>saturday, april 28</td>
<td>6:00 p.m</td>
<td>amsterdam admirals</td>
<td>l 10-14</td>
<td>1-2</td>
<td>olympic stadium</td>
<td>11942</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>saturday, may 5</td>
<td>6:00 p.m</td>
<td>at cologne centurions</td>
<td>w 31-28</td>
<td>2-2</td>
<td>rheinenergiestadion</td>
<td>10084</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>sunday, may 13</td>
<td>4:00 p.m</td>
<td>cologne centurions</td>
<td>l 10-24</td>
<td>2-3</td>
<td>olympic stadium</td>
<td>11995</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>sunday, may 20</td>
<td>5:00 p.m</td>
<td>at frankfurt galaxy</td>
<td>l 7-35</td>
<td>2-4</td>
<td>commerzbank-arena</td>
<td>30125</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>saturday, may 26</td>
<td>6:00 p.m</td>
<td>at hamburg sea devils</td>
<td>l 7-17</td>
<td>2-5</td>
<td>aol arena</td>
<td>18337</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>saturday, june 2</td>
<td>6:00 p.m</td>
<td>frankfurt galaxy</td>
<td>l 22-25</td>
<td>2-6</td>
<td>olympic stadium</td>
<td>11882</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>friday, june 8</td>
<td>7:00 p.m</td>
<td>rhein fire</td>
<td>l 17-24</td>
<td>2-7</td>
<td>olympic stadium</td>
<td>12114</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>friday, june 15</td>
<td>8:00 p.m</td>
<td>at amsterdam admirals</td>
<td>l 20-21</td>
<td>2-8</td>
<td>olympic stadium</td>
<td>11893</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "results final score" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( results final score ) where date = 'saturday, june 2' <table_name> : table | | week | date | kickoff | opponent | results final score | results team record | game site | attendance |
|---:|-------:|:-------------------|:----------|:----------------------|:----------------------|:----------------------|:--------------------|-------------:|
| 0 | 1 | saturday, april 14 | 7:00 p.m | at rhein fire | w 15-3 | 1-0 | ltu arena | 30355 |
| 1 | 2 | sunday, april 22 | 4:00 p.m | hamburg sea devils | l 7-16 | 1-1 | olympic stadium | 30657 |
| 2 | 3 | saturday, april 28 | 6:00 p.m | amsterdam admirals | l 10-14 | 1-2 | olympic stadium | 11942 |
| 3 | 4 | saturday, may 5 | 6:00 p.m | at cologne centurions | w 31-28 | 2-2 | rheinenergiestadion | 10084 |
| 4 | 5 | sunday, may 13 | 4:00 p.m | cologne centurions | l 10-24 | 2-3 | olympic stadium | 11995 |
| 5 | 6 | sunday, may 20 | 5:00 p.m | at frankfurt galaxy | l 7-35 | 2-4 | commerzbank-arena | 30125 |
| 6 | 7 | saturday, may 26 | 6:00 p.m | at hamburg sea devils | l 7-17 | 2-5 | aol arena | 18337 |
| 7 | 8 | saturday, june 2 | 6:00 p.m | frankfurt galaxy | l 22-25 | 2-6 | olympic stadium | 11882 |
| 8 | 9 | friday, june 8 | 7:00 p.m | rhein fire | l 17-24 | 2-7 | olympic stadium | 12114 |
| 9 | 10 | friday, june 15 | 8:00 p.m | at amsterdam admirals | l 20-21 | 2-8 | olympic stadium | 11893 | | | | count ( "results final score" ) |
|---:|----------------------------------:|
| 0 | 1 | | [
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select year - year where winner = 'citation' col : year | winner | jockey | trainer | owner | breeder row 1 : 1919 | sir barton | johnny loftus | h. guy bedwell | j. k. l. ross | none row 2 : 1930 | gallant fox | earl sande | jim fitzsimmons | belair stud | belair stud row 3 : 1935 | omaha | willie saunders | jim fitzsimmons | belair stud | belair stud row 4 : 1937 | war admiral | charley kurtsinger | george h. conway | samuel d. riddle | samuel d. riddle row 5 : 1941 | whirlaway | eddie arcaro | ben a. jones | calumet farm | calumet farm row 6 : 1943 | count fleet | johnny longden | don cameron | fannie hertz | fannie hertz row 7 : 1946 | assault | warren mehrtens | max hirsch | king ranch | king ranch row 8 : 1948 | citation | eddie arcaro | horace a. jones | calumet farm | calumet farm row 9 : 1973 | secretariat | ron turcotte | lucien laurin | meadow stable | meadow stud row 10 : 1977 | seattle slew | jean cruguet | william h. turner, jr | karen l. taylor | ben s. castleman row 11 : 1978 | affirmed | steve cauthen | laz barrera | harbor view farm | harbor view farm | col : "year - year" row 1 : year - year | select year - year where winner = 'citation' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & winner & jockey & trainer & owner & breeder \\
\midrule
0 & 1919 & sir barton & johnny loftus & h. guy bedwell & j. k. l. ross & none \\
1 & 1930 & gallant fox & earl sande & jim fitzsimmons & belair stud & belair stud \\
2 & 1935 & omaha & willie saunders & jim fitzsimmons & belair stud & belair stud \\
3 & 1937 & war admiral & charley kurtsinger & george h. conway & samuel d. riddle & samuel d. riddle \\
4 & 1941 & whirlaway & eddie arcaro & ben a. jones & calumet farm & calumet farm \\
5 & 1943 & count fleet & johnny longden & don cameron & fannie hertz & fannie hertz \\
6 & 1946 & assault & warren mehrtens & max hirsch & king ranch & king ranch \\
7 & 1948 & citation & eddie arcaro & horace a. jones & calumet farm & calumet farm \\
8 & 1973 & secretariat & ron turcotte & lucien laurin & meadow stable & meadow stud \\
9 & 1977 & seattle slew & jean cruguet & william h. turner, jr & karen l. taylor & ben s. castleman \\
10 & 1978 & affirmed & steve cauthen & laz barrera & harbor view farm & harbor view farm \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "year - year" \\
\midrule
0 & year - year \\
\bottomrule
\end{tabular}
| select year - year where winner = 'citation' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>winner</th>
<th>jockey</th>
<th>trainer</th>
<th>owner</th>
<th>breeder</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1919</td>
<td>sir barton</td>
<td>johnny loftus</td>
<td>h. guy bedwell</td>
<td>j. k. l. ross</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1930</td>
<td>gallant fox</td>
<td>earl sande</td>
<td>jim fitzsimmons</td>
<td>belair stud</td>
<td>belair stud</td>
</tr>
<tr>
<th>2</th>
<td>1935</td>
<td>omaha</td>
<td>willie saunders</td>
<td>jim fitzsimmons</td>
<td>belair stud</td>
<td>belair stud</td>
</tr>
<tr>
<th>3</th>
<td>1937</td>
<td>war admiral</td>
<td>charley kurtsinger</td>
<td>george h. conway</td>
<td>samuel d. riddle</td>
<td>samuel d. riddle</td>
</tr>
<tr>
<th>4</th>
<td>1941</td>
<td>whirlaway</td>
<td>eddie arcaro</td>
<td>ben a. jones</td>
<td>calumet farm</td>
<td>calumet farm</td>
</tr>
<tr>
<th>5</th>
<td>1943</td>
<td>count fleet</td>
<td>johnny longden</td>
<td>don cameron</td>
<td>fannie hertz</td>
<td>fannie hertz</td>
</tr>
<tr>
<th>6</th>
<td>1946</td>
<td>assault</td>
<td>warren mehrtens</td>
<td>max hirsch</td>
<td>king ranch</td>
<td>king ranch</td>
</tr>
<tr>
<th>7</th>
<td>1948</td>
<td>citation</td>
<td>eddie arcaro</td>
<td>horace a. jones</td>
<td>calumet farm</td>
<td>calumet farm</td>
</tr>
<tr>
<th>8</th>
<td>1973</td>
<td>secretariat</td>
<td>ron turcotte</td>
<td>lucien laurin</td>
<td>meadow stable</td>
<td>meadow stud</td>
</tr>
<tr>
<th>9</th>
<td>1977</td>
<td>seattle slew</td>
<td>jean cruguet</td>
<td>william h. turner, jr</td>
<td>karen l. taylor</td>
<td>ben s. castleman</td>
</tr>
<tr>
<th>10</th>
<td>1978</td>
<td>affirmed</td>
<td>steve cauthen</td>
<td>laz barrera</td>
<td>harbor view farm</td>
<td>harbor view farm</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"year - year"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>year - year</td>
</tr>
</tbody>
</table> | select year - year where winner = 'citation' <table_name> : table | | year | winner | jockey | trainer | owner | breeder |
|---:|-------:|:-------------|:-------------------|:----------------------|:-----------------|:-----------------|
| 0 | 1919 | sir barton | johnny loftus | h. guy bedwell | j. k. l. ross | none |
| 1 | 1930 | gallant fox | earl sande | jim fitzsimmons | belair stud | belair stud |
| 2 | 1935 | omaha | willie saunders | jim fitzsimmons | belair stud | belair stud |
| 3 | 1937 | war admiral | charley kurtsinger | george h. conway | samuel d. riddle | samuel d. riddle |
| 4 | 1941 | whirlaway | eddie arcaro | ben a. jones | calumet farm | calumet farm |
| 5 | 1943 | count fleet | johnny longden | don cameron | fannie hertz | fannie hertz |
| 6 | 1946 | assault | warren mehrtens | max hirsch | king ranch | king ranch |
| 7 | 1948 | citation | eddie arcaro | horace a. jones | calumet farm | calumet farm |
| 8 | 1973 | secretariat | ron turcotte | lucien laurin | meadow stable | meadow stud |
| 9 | 1977 | seattle slew | jean cruguet | william h. turner, jr | karen l. taylor | ben s. castleman |
| 10 | 1978 | affirmed | steve cauthen | laz barrera | harbor view farm | harbor view farm | | | | "year - year" |
|---:|:----------------|
| 0 | year - year | | [
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select round where wins = 6 col : year | round | position | matches | wins | draws | losses | gf | ga row 1 : 1930 to 1990 | competed as part of yugoslavia | none | none | none | none | none | none | none row 2 : 1994 | could not enter | none | none | none | none | none | none | none row 3 : 1998 | third place | 3 | 7 | 5 | 0 | 2 | 11 | 5 row 4 : / 2002 | group stage | 23 | 3 | 1 | 0 | 2 | 2 | 3 row 5 : 2006 | group stage | 22 | 3 | 0 | 2 | 1 | 2 | 3 row 6 : 2010 | did not qualify | none | none | none | none | none | none | none row 7 : 2014 | qualified | none | none | none | none | none | none | none row 8 : total | 4/5 | none | 13 | 6 | 2 | 5 | 15 | 11 | col : round row 1 : 4/5 | select round where wins = 6 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& year & round & position & matches & wins & draws & losses & gf & ga \\
\midrule
0 & 1930 to 1990 & competed as part of yugoslavia & none & none & none & none & none & none & none \\
1 & 1994 & could not enter & none & none & none & none & none & none & none \\
2 & 1998 & third place & 3 & 7 & 5 & 0 & 2 & 11 & 5 \\
3 & / 2002 & group stage & 23 & 3 & 1 & 0 & 2 & 2 & 3 \\
4 & 2006 & group stage & 22 & 3 & 0 & 2 & 1 & 2 & 3 \\
5 & 2010 & did not qualify & none & none & none & none & none & none & none \\
6 & 2014 & qualified & none & none & none & none & none & none & none \\
7 & total & 4/5 & none & 13 & 6 & 2 & 5 & 15 & 11 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& round \\
\midrule
0 & 4/5 \\
\bottomrule
\end{tabular}
| select round where wins = 6 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>round</th>
<th>position</th>
<th>matches</th>
<th>wins</th>
<th>draws</th>
<th>losses</th>
<th>gf</th>
<th>ga</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1930 to 1990</td>
<td>competed as part of yugoslavia</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1994</td>
<td>could not enter</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1998</td>
<td>third place</td>
<td>3</td>
<td>7</td>
<td>5</td>
<td>0</td>
<td>2</td>
<td>11</td>
<td>5</td>
</tr>
<tr>
<th>3</th>
<td>/ 2002</td>
<td>group stage</td>
<td>23</td>
<td>3</td>
<td>1</td>
<td>0</td>
<td>2</td>
<td>2</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>2006</td>
<td>group stage</td>
<td>22</td>
<td>3</td>
<td>0</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>3</td>
</tr>
<tr>
<th>5</th>
<td>2010</td>
<td>did not qualify</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2014</td>
<td>qualified</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>total</td>
<td>4/5</td>
<td>none</td>
<td>13</td>
<td>6</td>
<td>2</td>
<td>5</td>
<td>15</td>
<td>11</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>round</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4/5</td>
</tr>
</tbody>
</table> | select round where wins = 6 <table_name> : table | | year | round | position | matches | wins | draws | losses | gf | ga |
|---:|:-------------|:-------------------------------|:-----------|:----------|:-------|:--------|:---------|:-----|:-----|
| 0 | 1930 to 1990 | competed as part of yugoslavia | none | none | none | none | none | none | none |
| 1 | 1994 | could not enter | none | none | none | none | none | none | none |
| 2 | 1998 | third place | 3 | 7 | 5 | 0 | 2 | 11 | 5 |
| 3 | / 2002 | group stage | 23 | 3 | 1 | 0 | 2 | 2 | 3 |
| 4 | 2006 | group stage | 22 | 3 | 0 | 2 | 1 | 2 | 3 |
| 5 | 2010 | did not qualify | none | none | none | none | none | none | none |
| 6 | 2014 | qualified | none | none | none | none | none | none | none |
| 7 | total | 4/5 | none | 13 | 6 | 2 | 5 | 15 | 11 | | | | round |
|---:|:--------|
| 0 | 4/5 | | [
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] |
select last team where size = '1,84 m' 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 : last team row 1 : ssc karlsruhe | select last team where size = '1,84 m' <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
& last team \\
\midrule
0 & ssc karlsruhe \\
\bottomrule
\end{tabular}
| select last team where size = '1,84 m' <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>last team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>ssc karlsruhe</td>
</tr>
</tbody>
</table> | select last team where size = '1,84 m' <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 | | | | last team |
|---:|:--------------|
| 0 | ssc karlsruhe | | [
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select count ( cabinet ) where vote % > 0 col : year | vote % | place -1 | seats | place -2 | cabinet row 1 : 1945 | none | none | 25 | 1st | yes row 2 : 1948 | none | none | 22 | 1st | yes row 3 : 1951 | none | none | 21 | 1st | yes row 4 : 1954 | 42.4 | 1st | 26 | 1st | yes row 5 : 1959 | 36.9 | 1st | 21 | 1st | yes row 6 : 1964 | 33.3 | 2nd | 22 | 1st | yes row 7 : 1968 | 35.2 | 1st | 21 | 1st | yes row 8 : 1974 | 27.6 | 2nd | 18 | 1st | no row 9 : 1979 | 34.5 | 1st | 24 | 1st | yes row 10 : 1984 | 34.9 | 1st | 25 | 1st | yes row 11 : 1989 | 32.4 | 1st | 22 | 1st | yes row 12 : 1994 | 30.3 | 1st | 21 | 1st | yes row 13 : 1999 | 30.1 | 1st | 19 | 1st | yes row 14 : 2004 | 36.1 | 1st | 24 | 1st | yes row 15 : 2009 | 38 | 1st | 26 | 1st | yes row 16 : 2013 | 33.6 | 1st | 23 | 1st | no | col : count ( "cabinet" ) row 1 : 16 | select count ( cabinet ) where vote % > 0 <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & vote % & place -1 & seats & place -2 & cabinet \\
\midrule
0 & 1945 & none & none & 25 & 1st & yes \\
1 & 1948 & none & none & 22 & 1st & yes \\
2 & 1951 & none & none & 21 & 1st & yes \\
3 & 1954 & 42.4 & 1st & 26 & 1st & yes \\
4 & 1959 & 36.9 & 1st & 21 & 1st & yes \\
5 & 1964 & 33.3 & 2nd & 22 & 1st & yes \\
6 & 1968 & 35.2 & 1st & 21 & 1st & yes \\
7 & 1974 & 27.6 & 2nd & 18 & 1st & no \\
8 & 1979 & 34.5 & 1st & 24 & 1st & yes \\
9 & 1984 & 34.9 & 1st & 25 & 1st & yes \\
10 & 1989 & 32.4 & 1st & 22 & 1st & yes \\
11 & 1994 & 30.3 & 1st & 21 & 1st & yes \\
12 & 1999 & 30.1 & 1st & 19 & 1st & yes \\
13 & 2004 & 36.1 & 1st & 24 & 1st & yes \\
14 & 2009 & 38 & 1st & 26 & 1st & yes \\
15 & 2013 & 33.6 & 1st & 23 & 1st & no \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "cabinet" ) \\
\midrule
0 & 16 \\
\bottomrule
\end{tabular}
| select count ( cabinet ) where vote % > 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>vote %</th>
<th>place -1</th>
<th>seats</th>
<th>place -2</th>
<th>cabinet</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1945</td>
<td>none</td>
<td>none</td>
<td>25</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>1</th>
<td>1948</td>
<td>none</td>
<td>none</td>
<td>22</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>2</th>
<td>1951</td>
<td>none</td>
<td>none</td>
<td>21</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>3</th>
<td>1954</td>
<td>42.4</td>
<td>1st</td>
<td>26</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>4</th>
<td>1959</td>
<td>36.9</td>
<td>1st</td>
<td>21</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>5</th>
<td>1964</td>
<td>33.3</td>
<td>2nd</td>
<td>22</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>6</th>
<td>1968</td>
<td>35.2</td>
<td>1st</td>
<td>21</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>7</th>
<td>1974</td>
<td>27.6</td>
<td>2nd</td>
<td>18</td>
<td>1st</td>
<td>no</td>
</tr>
<tr>
<th>8</th>
<td>1979</td>
<td>34.5</td>
<td>1st</td>
<td>24</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>9</th>
<td>1984</td>
<td>34.9</td>
<td>1st</td>
<td>25</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>10</th>
<td>1989</td>
<td>32.4</td>
<td>1st</td>
<td>22</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>11</th>
<td>1994</td>
<td>30.3</td>
<td>1st</td>
<td>21</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>12</th>
<td>1999</td>
<td>30.1</td>
<td>1st</td>
<td>19</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>13</th>
<td>2004</td>
<td>36.1</td>
<td>1st</td>
<td>24</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>14</th>
<td>2009</td>
<td>38</td>
<td>1st</td>
<td>26</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>15</th>
<td>2013</td>
<td>33.6</td>
<td>1st</td>
<td>23</td>
<td>1st</td>
<td>no</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "cabinet" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>16</td>
</tr>
</tbody>
</table> | select count ( cabinet ) where vote % > 0 <table_name> : table | | year | vote % | place -1 | seats | place -2 | cabinet |
|---:|-------:|:---------|:-----------|--------:|:-----------|:----------|
| 0 | 1945 | none | none | 25 | 1st | yes |
| 1 | 1948 | none | none | 22 | 1st | yes |
| 2 | 1951 | none | none | 21 | 1st | yes |
| 3 | 1954 | 42.4 | 1st | 26 | 1st | yes |
| 4 | 1959 | 36.9 | 1st | 21 | 1st | yes |
| 5 | 1964 | 33.3 | 2nd | 22 | 1st | yes |
| 6 | 1968 | 35.2 | 1st | 21 | 1st | yes |
| 7 | 1974 | 27.6 | 2nd | 18 | 1st | no |
| 8 | 1979 | 34.5 | 1st | 24 | 1st | yes |
| 9 | 1984 | 34.9 | 1st | 25 | 1st | yes |
| 10 | 1989 | 32.4 | 1st | 22 | 1st | yes |
| 11 | 1994 | 30.3 | 1st | 21 | 1st | yes |
| 12 | 1999 | 30.1 | 1st | 19 | 1st | yes |
| 13 | 2004 | 36.1 | 1st | 24 | 1st | yes |
| 14 | 2009 | 38 | 1st | 26 | 1st | yes |
| 15 | 2013 | 33.6 | 1st | 23 | 1st | no | | | | count ( "cabinet" ) |
|---:|----------------------:|
| 0 | 16 | | [
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] |
select title where music = 'mike e. clark' col : # | title | time | lyrics | music | producer(s) | performer(s) row 1 : 1 | "intro" | 1:16 | none | none | none | none row 2 : 2 | "seven" | 3:30 | boondox | mike e. clark | boondox | boondox row 3 : 3 | "out here" | 3:18 | boondox | mike e. clark tino grosse | boondox | boondox row 4 : 4 | "it ain't a thang" | 3:45 | boondox | mike e. clark | boondox | boondox row 5 : 5 | "digging" | 3:04 | boondox | kuma | boondox | boondox row 6 : 6 | "lady in the jaguar" | 3:55 | boondox icp | mike e. clark | boondox icp | boondox icp row 7 : 7 | "they pray with snakes" | 3:56 | boondox | kuma | boondox | boondox row 8 : 8 | "rollin hard" | 4:07 | boondox | mike e. clark | boondox | boondox row 9 : 9 | "the harvest" | 3:53 | boondox amb | kuma | boondox amb | boondox axe murder boyz row 10 : 10 | "sippin" | 3:16 | boondox | mike e. clark | boondox | boondox row 11 : 11 | "lake of fire" | 4:12 | boondox | mike e. clark | boondox | boondox row 12 : 12 | "red mist" | 3:54 | boondox | mike e. clark | boondox | boondox blaze ya dead homie twiztid row 13 : 13 | "angel like" | 3:42 | boondox | mike e. clark | boondox | boondox | col : title row 1 : "seven" row 2 : "it ain't a thang" row 3 : "lady in the jaguar" row 4 : "rollin hard" row 5 : "sippin" row 6 : "lake of fire" row 7 : "red mist" row 8 : "angel like" | select title where music = 'mike e. clark' <table_name> : table \begin{tabular}{llllllll}
\toprule
& # & title & time & lyrics & music & producer(s) & performer(s) \\
\midrule
0 & 1 & "intro" & 1:16 & none & none & none & none \\
1 & 2 & "seven" & 3:30 & boondox & mike e. clark & boondox & boondox \\
2 & 3 & "out here" & 3:18 & boondox & mike e. clark tino grosse & boondox & boondox \\
3 & 4 & "it ain't a thang" & 3:45 & boondox & mike e. clark & boondox & boondox \\
4 & 5 & "digging" & 3:04 & boondox & kuma & boondox & boondox \\
5 & 6 & "lady in the jaguar" & 3:55 & boondox icp & mike e. clark & boondox icp & boondox icp \\
6 & 7 & "they pray with snakes" & 3:56 & boondox & kuma & boondox & boondox \\
7 & 8 & "rollin hard" & 4:07 & boondox & mike e. clark & boondox & boondox \\
8 & 9 & "the harvest" & 3:53 & boondox amb & kuma & boondox amb & boondox axe murder boyz \\
9 & 10 & "sippin" & 3:16 & boondox & mike e. clark & boondox & boondox \\
10 & 11 & "lake of fire" & 4:12 & boondox & mike e. clark & boondox & boondox \\
11 & 12 & "red mist" & 3:54 & boondox & mike e. clark & boondox & boondox blaze ya dead homie twiztid \\
12 & 13 & "angel like" & 3:42 & boondox & mike e. clark & boondox & boondox \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& title \\
\midrule
0 & "seven" \\
1 & "it ain't a thang" \\
2 & "lady in the jaguar" \\
3 & "rollin hard" \\
4 & "sippin" \\
5 & "lake of fire" \\
6 & "red mist" \\
7 & "angel like" \\
\bottomrule
\end{tabular}
| select title where music = 'mike e. clark' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>title</th>
<th>time</th>
<th>lyrics</th>
<th>music</th>
<th>producer(s)</th>
<th>performer(s)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>"intro"</td>
<td>1:16</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>"seven"</td>
<td>3:30</td>
<td>boondox</td>
<td>mike e. clark</td>
<td>boondox</td>
<td>boondox</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>"out here"</td>
<td>3:18</td>
<td>boondox</td>
<td>mike e. clark tino grosse</td>
<td>boondox</td>
<td>boondox</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>"it ain't a thang"</td>
<td>3:45</td>
<td>boondox</td>
<td>mike e. clark</td>
<td>boondox</td>
<td>boondox</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>"digging"</td>
<td>3:04</td>
<td>boondox</td>
<td>kuma</td>
<td>boondox</td>
<td>boondox</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>"lady in the jaguar"</td>
<td>3:55</td>
<td>boondox icp</td>
<td>mike e. clark</td>
<td>boondox icp</td>
<td>boondox icp</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>"they pray with snakes"</td>
<td>3:56</td>
<td>boondox</td>
<td>kuma</td>
<td>boondox</td>
<td>boondox</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>"rollin hard"</td>
<td>4:07</td>
<td>boondox</td>
<td>mike e. clark</td>
<td>boondox</td>
<td>boondox</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>"the harvest"</td>
<td>3:53</td>
<td>boondox amb</td>
<td>kuma</td>
<td>boondox amb</td>
<td>boondox axe murder boyz</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>"sippin"</td>
<td>3:16</td>
<td>boondox</td>
<td>mike e. clark</td>
<td>boondox</td>
<td>boondox</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>"lake of fire"</td>
<td>4:12</td>
<td>boondox</td>
<td>mike e. clark</td>
<td>boondox</td>
<td>boondox</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>"red mist"</td>
<td>3:54</td>
<td>boondox</td>
<td>mike e. clark</td>
<td>boondox</td>
<td>boondox blaze ya dead homie twiztid</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>"angel like"</td>
<td>3:42</td>
<td>boondox</td>
<td>mike e. clark</td>
<td>boondox</td>
<td>boondox</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>"seven"</td>
</tr>
<tr>
<th>1</th>
<td>"it ain't a thang"</td>
</tr>
<tr>
<th>2</th>
<td>"lady in the jaguar"</td>
</tr>
<tr>
<th>3</th>
<td>"rollin hard"</td>
</tr>
<tr>
<th>4</th>
<td>"sippin"</td>
</tr>
<tr>
<th>5</th>
<td>"lake of fire"</td>
</tr>
<tr>
<th>6</th>
<td>"red mist"</td>
</tr>
<tr>
<th>7</th>
<td>"angel like"</td>
</tr>
</tbody>
</table> | select title where music = 'mike e. clark' <table_name> : table | | # | title | time | lyrics | music | producer(s) | performer(s) |
|---:|----:|:------------------------|:-------|:------------|:--------------------------|:--------------|:------------------------------------|
| 0 | 1 | "intro" | 1:16 | none | none | none | none |
| 1 | 2 | "seven" | 3:30 | boondox | mike e. clark | boondox | boondox |
| 2 | 3 | "out here" | 3:18 | boondox | mike e. clark tino grosse | boondox | boondox |
| 3 | 4 | "it ain't a thang" | 3:45 | boondox | mike e. clark | boondox | boondox |
| 4 | 5 | "digging" | 3:04 | boondox | kuma | boondox | boondox |
| 5 | 6 | "lady in the jaguar" | 3:55 | boondox icp | mike e. clark | boondox icp | boondox icp |
| 6 | 7 | "they pray with snakes" | 3:56 | boondox | kuma | boondox | boondox |
| 7 | 8 | "rollin hard" | 4:07 | boondox | mike e. clark | boondox | boondox |
| 8 | 9 | "the harvest" | 3:53 | boondox amb | kuma | boondox amb | boondox axe murder boyz |
| 9 | 10 | "sippin" | 3:16 | boondox | mike e. clark | boondox | boondox |
| 10 | 11 | "lake of fire" | 4:12 | boondox | mike e. clark | boondox | boondox |
| 11 | 12 | "red mist" | 3:54 | boondox | mike e. clark | boondox | boondox blaze ya dead homie twiztid |
| 12 | 13 | "angel like" | 3:42 | boondox | mike e. clark | boondox | boondox | | | | title |
|---:|:---------------------|
| 0 | "seven" |
| 1 | "it ain't a thang" |
| 2 | "lady in the jaguar" |
| 3 | "rollin hard" |
| 4 | "sippin" |
| 5 | "lake of fire" |
| 6 | "red mist" |
| 7 | "angel like" | | [
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select date of birth where 2008 club = 'finasa' col : no | name | date of birth | height | weight | spike | block | 2008 club row 1 : 1 | oliveira walewska | 1 october 1979 | 1.90 m (6 ft 3 in) | 73 kg (161 lb) | 310 cm (120 in) | 290 cm (110 in) | cav murcia row 2 : 2 | carolina albuquerque | 25 july 1977 | 1.82 m (6 ft 0 in) | 76 kg (168 lb) | 289 cm (114 in) | 279 cm (110 in) | finasa row 3 : 3 | marianne steinbrecher | 23 august 1983 | 1.88 m (6 ft 2 in) | 70 kg (150 lb) | 310 cm (120 in) | 290 cm (110 in) | scavolini pesaro row 4 : 4 | paula pequeno | 22 january 1982 | 1.84 m (6 ft 0 in) | 74 kg (163 lb) | 302 cm (119 in) | 285 cm (112 in) | finasa row 5 : 6 | thaisa menezes | 15 may 1987 | 1.96 m (6 ft 5 in) | 79 kg (174 lb) | 316 cm (124 in) | 301 cm (119 in) | rexona ades row 6 : 7 | helia souza | 3 october 1970 | 1.73 m (5 ft 8 in) | 63 kg (139 lb) | 283 cm (111 in) | 264 cm (104 in) | cav murcia row 7 : 8 | valeska menezes | 23 april 1976 | 1.80 m (5 ft 11 in) | 62 kg (137 lb) | 302 cm (119 in) | 290 cm (110 in) | asystel novara row 8 : 9 | fabiana claudino | 24 january 1984 | 1.93 m (6 ft 4 in) | 76 kg (168 lb) | 314 cm (124 in) | 293 cm (115 in) | rexona ades row 9 : 10 | welissa gonzaga | 9 september 1982 | 1.79 m (5 ft 10 in) | 76 kg (168 lb) | 300 cm (120 in) | 287 cm (113 in) | rexona ades row 10 : 12 | jacqueline carvalho | 31 december 1983 | 1.86 m (6 ft 1 in) | 70 kg (150 lb) | 302 cm (119 in) | 286 cm (113 in) | cav murcia row 11 : 13 | sheilla castro | 1 july 1983 | 1.85 m (6 ft 1 in) | 64 kg (141 lb) | 302 cm (119 in) | 284 cm (112 in) | scavolini pesaro row 12 : 14 | fabiana de oliveira | 7 march 1980 | 1.69 m (5 ft 7 in) | 59 kg (130 lb) | 276 cm (109 in) | 266 cm (105 in) | rexona ades | col : date of birth row 1 : 25 july 1977 row 2 : 22 january 1982 | select date of birth where 2008 club = 'finasa' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& no & name & date of birth & height & weight & spike & block & 2008 club \\
\midrule
0 & 1 & oliveira walewska & 1 october 1979 & 1.90 m (6 ft 3 in) & 73 kg (161 lb) & 310 cm (120 in) & 290 cm (110 in) & cav murcia \\
1 & 2 & carolina albuquerque & 25 july 1977 & 1.82 m (6 ft 0 in) & 76 kg (168 lb) & 289 cm (114 in) & 279 cm (110 in) & finasa \\
2 & 3 & marianne steinbrecher & 23 august 1983 & 1.88 m (6 ft 2 in) & 70 kg (150 lb) & 310 cm (120 in) & 290 cm (110 in) & scavolini pesaro \\
3 & 4 & paula pequeno & 22 january 1982 & 1.84 m (6 ft 0 in) & 74 kg (163 lb) & 302 cm (119 in) & 285 cm (112 in) & finasa \\
4 & 6 & thaisa menezes & 15 may 1987 & 1.96 m (6 ft 5 in) & 79 kg (174 lb) & 316 cm (124 in) & 301 cm (119 in) & rexona ades \\
5 & 7 & helia souza & 3 october 1970 & 1.73 m (5 ft 8 in) & 63 kg (139 lb) & 283 cm (111 in) & 264 cm (104 in) & cav murcia \\
6 & 8 & valeska menezes & 23 april 1976 & 1.80 m (5 ft 11 in) & 62 kg (137 lb) & 302 cm (119 in) & 290 cm (110 in) & asystel novara \\
7 & 9 & fabiana claudino & 24 january 1984 & 1.93 m (6 ft 4 in) & 76 kg (168 lb) & 314 cm (124 in) & 293 cm (115 in) & rexona ades \\
8 & 10 & welissa gonzaga & 9 september 1982 & 1.79 m (5 ft 10 in) & 76 kg (168 lb) & 300 cm (120 in) & 287 cm (113 in) & rexona ades \\
9 & 12 & jacqueline carvalho & 31 december 1983 & 1.86 m (6 ft 1 in) & 70 kg (150 lb) & 302 cm (119 in) & 286 cm (113 in) & cav murcia \\
10 & 13 & sheilla castro & 1 july 1983 & 1.85 m (6 ft 1 in) & 64 kg (141 lb) & 302 cm (119 in) & 284 cm (112 in) & scavolini pesaro \\
11 & 14 & fabiana de oliveira & 7 march 1980 & 1.69 m (5 ft 7 in) & 59 kg (130 lb) & 276 cm (109 in) & 266 cm (105 in) & rexona ades \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& date of birth \\
\midrule
0 & 25 july 1977 \\
1 & 22 january 1982 \\
\bottomrule
\end{tabular}
| select date of birth where 2008 club = 'finasa' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no</th>
<th>name</th>
<th>date of birth</th>
<th>height</th>
<th>weight</th>
<th>spike</th>
<th>block</th>
<th>2008 club</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>oliveira walewska</td>
<td>1 october 1979</td>
<td>1.90 m (6 ft 3 in)</td>
<td>73 kg (161 lb)</td>
<td>310 cm (120 in)</td>
<td>290 cm (110 in)</td>
<td>cav murcia</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>carolina albuquerque</td>
<td>25 july 1977</td>
<td>1.82 m (6 ft 0 in)</td>
<td>76 kg (168 lb)</td>
<td>289 cm (114 in)</td>
<td>279 cm (110 in)</td>
<td>finasa</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>marianne steinbrecher</td>
<td>23 august 1983</td>
<td>1.88 m (6 ft 2 in)</td>
<td>70 kg (150 lb)</td>
<td>310 cm (120 in)</td>
<td>290 cm (110 in)</td>
<td>scavolini pesaro</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>paula pequeno</td>
<td>22 january 1982</td>
<td>1.84 m (6 ft 0 in)</td>
<td>74 kg (163 lb)</td>
<td>302 cm (119 in)</td>
<td>285 cm (112 in)</td>
<td>finasa</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>thaisa menezes</td>
<td>15 may 1987</td>
<td>1.96 m (6 ft 5 in)</td>
<td>79 kg (174 lb)</td>
<td>316 cm (124 in)</td>
<td>301 cm (119 in)</td>
<td>rexona ades</td>
</tr>
<tr>
<th>5</th>
<td>7</td>
<td>helia souza</td>
<td>3 october 1970</td>
<td>1.73 m (5 ft 8 in)</td>
<td>63 kg (139 lb)</td>
<td>283 cm (111 in)</td>
<td>264 cm (104 in)</td>
<td>cav murcia</td>
</tr>
<tr>
<th>6</th>
<td>8</td>
<td>valeska menezes</td>
<td>23 april 1976</td>
<td>1.80 m (5 ft 11 in)</td>
<td>62 kg (137 lb)</td>
<td>302 cm (119 in)</td>
<td>290 cm (110 in)</td>
<td>asystel novara</td>
</tr>
<tr>
<th>7</th>
<td>9</td>
<td>fabiana claudino</td>
<td>24 january 1984</td>
<td>1.93 m (6 ft 4 in)</td>
<td>76 kg (168 lb)</td>
<td>314 cm (124 in)</td>
<td>293 cm (115 in)</td>
<td>rexona ades</td>
</tr>
<tr>
<th>8</th>
<td>10</td>
<td>welissa gonzaga</td>
<td>9 september 1982</td>
<td>1.79 m (5 ft 10 in)</td>
<td>76 kg (168 lb)</td>
<td>300 cm (120 in)</td>
<td>287 cm (113 in)</td>
<td>rexona ades</td>
</tr>
<tr>
<th>9</th>
<td>12</td>
<td>jacqueline carvalho</td>
<td>31 december 1983</td>
<td>1.86 m (6 ft 1 in)</td>
<td>70 kg (150 lb)</td>
<td>302 cm (119 in)</td>
<td>286 cm (113 in)</td>
<td>cav murcia</td>
</tr>
<tr>
<th>10</th>
<td>13</td>
<td>sheilla castro</td>
<td>1 july 1983</td>
<td>1.85 m (6 ft 1 in)</td>
<td>64 kg (141 lb)</td>
<td>302 cm (119 in)</td>
<td>284 cm (112 in)</td>
<td>scavolini pesaro</td>
</tr>
<tr>
<th>11</th>
<td>14</td>
<td>fabiana de oliveira</td>
<td>7 march 1980</td>
<td>1.69 m (5 ft 7 in)</td>
<td>59 kg (130 lb)</td>
<td>276 cm (109 in)</td>
<td>266 cm (105 in)</td>
<td>rexona ades</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date of birth</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>25 july 1977</td>
</tr>
<tr>
<th>1</th>
<td>22 january 1982</td>
</tr>
</tbody>
</table> | select date of birth where 2008 club = 'finasa' <table_name> : table | | no | name | date of birth | height | weight | spike | block | 2008 club |
|---:|-----:|:----------------------|:-----------------|:--------------------|:---------------|:----------------|:----------------|:-----------------|
| 0 | 1 | oliveira walewska | 1 october 1979 | 1.90 m (6 ft 3 in) | 73 kg (161 lb) | 310 cm (120 in) | 290 cm (110 in) | cav murcia |
| 1 | 2 | carolina albuquerque | 25 july 1977 | 1.82 m (6 ft 0 in) | 76 kg (168 lb) | 289 cm (114 in) | 279 cm (110 in) | finasa |
| 2 | 3 | marianne steinbrecher | 23 august 1983 | 1.88 m (6 ft 2 in) | 70 kg (150 lb) | 310 cm (120 in) | 290 cm (110 in) | scavolini pesaro |
| 3 | 4 | paula pequeno | 22 january 1982 | 1.84 m (6 ft 0 in) | 74 kg (163 lb) | 302 cm (119 in) | 285 cm (112 in) | finasa |
| 4 | 6 | thaisa menezes | 15 may 1987 | 1.96 m (6 ft 5 in) | 79 kg (174 lb) | 316 cm (124 in) | 301 cm (119 in) | rexona ades |
| 5 | 7 | helia souza | 3 october 1970 | 1.73 m (5 ft 8 in) | 63 kg (139 lb) | 283 cm (111 in) | 264 cm (104 in) | cav murcia |
| 6 | 8 | valeska menezes | 23 april 1976 | 1.80 m (5 ft 11 in) | 62 kg (137 lb) | 302 cm (119 in) | 290 cm (110 in) | asystel novara |
| 7 | 9 | fabiana claudino | 24 january 1984 | 1.93 m (6 ft 4 in) | 76 kg (168 lb) | 314 cm (124 in) | 293 cm (115 in) | rexona ades |
| 8 | 10 | welissa gonzaga | 9 september 1982 | 1.79 m (5 ft 10 in) | 76 kg (168 lb) | 300 cm (120 in) | 287 cm (113 in) | rexona ades |
| 9 | 12 | jacqueline carvalho | 31 december 1983 | 1.86 m (6 ft 1 in) | 70 kg (150 lb) | 302 cm (119 in) | 286 cm (113 in) | cav murcia |
| 10 | 13 | sheilla castro | 1 july 1983 | 1.85 m (6 ft 1 in) | 64 kg (141 lb) | 302 cm (119 in) | 284 cm (112 in) | scavolini pesaro |
| 11 | 14 | fabiana de oliveira | 7 march 1980 | 1.69 m (5 ft 7 in) | 59 kg (130 lb) | 276 cm (109 in) | 266 cm (105 in) | rexona ades | | | | date of birth |
|---:|:----------------|
| 0 | 25 july 1977 |
| 1 | 22 january 1982 | | [
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select count ( name ) where name = 'gil kerlikowske' col : no. | name | term of office | president(s) served under row 1 : 1 | william bennett | 1989 - 1991 | george h. w. bush row 2 : 2 | bob martinez | march 28, 1991 - january 20, 1993 | george h. w. bush row 3 : 3 | lee p. brown | january 1993 - december 12, 1995 | bill clinton row 4 : 4 | barry mccaffrey | february 29, 1996 - january 4, 2001 | bill clinton row 5 : 5 | john p. walters | december 7, 2001 - january 19, 2009 | george w. bush row 6 : 6 | gil kerlikowske | may 7, 2009 - march 6, 2014 | barack obama row 7 : acting | michael botticelli | march 6, 2014 - | barack obama | col : count ( "name" ) row 1 : 1 | select count ( name ) where name = 'gil kerlikowske' <table_name> : table \begin{tabular}{lllll}
\toprule
& no. & name & term of office & president(s) served under \\
\midrule
0 & 1 & william bennett & 1989 - 1991 & george h. w. bush \\
1 & 2 & bob martinez & march 28, 1991 - january 20, 1993 & george h. w. bush \\
2 & 3 & lee p. brown & january 1993 - december 12, 1995 & bill clinton \\
3 & 4 & barry mccaffrey & february 29, 1996 - january 4, 2001 & bill clinton \\
4 & 5 & john p. walters & december 7, 2001 - january 19, 2009 & george w. bush \\
5 & 6 & gil kerlikowske & may 7, 2009 - march 6, 2014 & barack obama \\
6 & acting & michael botticelli & march 6, 2014 - & barack obama \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "name" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( name ) where name = 'gil kerlikowske' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no.</th>
<th>name</th>
<th>term of office</th>
<th>president(s) served under</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>william bennett</td>
<td>1989 - 1991</td>
<td>george h. w. bush</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>bob martinez</td>
<td>march 28, 1991 - january 20, 1993</td>
<td>george h. w. bush</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>lee p. brown</td>
<td>january 1993 - december 12, 1995</td>
<td>bill clinton</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>barry mccaffrey</td>
<td>february 29, 1996 - january 4, 2001</td>
<td>bill clinton</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>john p. walters</td>
<td>december 7, 2001 - january 19, 2009</td>
<td>george w. bush</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>gil kerlikowske</td>
<td>may 7, 2009 - march 6, 2014</td>
<td>barack obama</td>
</tr>
<tr>
<th>6</th>
<td>acting</td>
<td>michael botticelli</td>
<td>march 6, 2014 -</td>
<td>barack obama</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "name" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( name ) where name = 'gil kerlikowske' <table_name> : table | | no. | name | term of office | president(s) served under |
|---:|:-------|:-------------------|:------------------------------------|:----------------------------|
| 0 | 1 | william bennett | 1989 - 1991 | george h. w. bush |
| 1 | 2 | bob martinez | march 28, 1991 - january 20, 1993 | george h. w. bush |
| 2 | 3 | lee p. brown | january 1993 - december 12, 1995 | bill clinton |
| 3 | 4 | barry mccaffrey | february 29, 1996 - january 4, 2001 | bill clinton |
| 4 | 5 | john p. walters | december 7, 2001 - january 19, 2009 | george w. bush |
| 5 | 6 | gil kerlikowske | may 7, 2009 - march 6, 2014 | barack obama |
| 6 | acting | michael botticelli | march 6, 2014 - | barack obama | | | | count ( "name" ) |
|---:|-------------------:|
| 0 | 1 | | [
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select count ( show ) where show = 'saregamapa challenge' col : year | show | role | channel | extra row 1 : 2004 | boogie woogie-chalo america | dance contestant | set (sony entertainment television) | finalist (top 5) row 2 : 2007 (may-october) | saregamapa challenge | singing contestant | zee network | finalist (top 7) row 3 : 2008 (march-may) | rock n roll family | host | zee network | none row 4 : 2010 ( released dec. 5th) | ek anhonee (tele-film) | lead role (divyani) | zoom | none row 5 : 2011 (june-july) | khatron ke khiladi season 4 | celebrity contestant | colors | finalist (top 2) row 6 : 2012 (feb) | kahani comedy circus ki | guest appearance (15 episodes) | set (sony entertainment television) | none row 7 : 2013 (feb) | welcome - baazi mehmaan-nawaazi ki | herself | life ok | none | col : count ( "show" ) row 1 : 1 | select count ( show ) where show = 'saregamapa challenge' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & show & role & channel & extra \\
\midrule
0 & 2004 & boogie woogie-chalo america & dance contestant & set (sony entertainment television) & finalist (top 5) \\
1 & 2007 (may-october) & saregamapa challenge & singing contestant & zee network & finalist (top 7) \\
2 & 2008 (march-may) & rock n roll family & host & zee network & none \\
3 & 2010 ( released dec. 5th) & ek anhonee (tele-film) & lead role (divyani) & zoom & none \\
4 & 2011 (june-july) & khatron ke khiladi season 4 & celebrity contestant & colors & finalist (top 2) \\
5 & 2012 (feb) & kahani comedy circus ki & guest appearance (15 episodes) & set (sony entertainment television) & none \\
6 & 2013 (feb) & welcome - baazi mehmaan-nawaazi ki & herself & life ok & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "show" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( show ) where show = 'saregamapa challenge' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>show</th>
<th>role</th>
<th>channel</th>
<th>extra</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004</td>
<td>boogie woogie-chalo america</td>
<td>dance contestant</td>
<td>set (sony entertainment television)</td>
<td>finalist (top 5)</td>
</tr>
<tr>
<th>1</th>
<td>2007 (may-october)</td>
<td>saregamapa challenge</td>
<td>singing contestant</td>
<td>zee network</td>
<td>finalist (top 7)</td>
</tr>
<tr>
<th>2</th>
<td>2008 (march-may)</td>
<td>rock n roll family</td>
<td>host</td>
<td>zee network</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2010 ( released dec. 5th)</td>
<td>ek anhonee (tele-film)</td>
<td>lead role (divyani)</td>
<td>zoom</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2011 (june-july)</td>
<td>khatron ke khiladi season 4</td>
<td>celebrity contestant</td>
<td>colors</td>
<td>finalist (top 2)</td>
</tr>
<tr>
<th>5</th>
<td>2012 (feb)</td>
<td>kahani comedy circus ki</td>
<td>guest appearance (15 episodes)</td>
<td>set (sony entertainment television)</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2013 (feb)</td>
<td>welcome - baazi mehmaan-nawaazi ki</td>
<td>herself</td>
<td>life ok</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "show" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( show ) where show = 'saregamapa challenge' <table_name> : table | | year | show | role | channel | extra |
|---:|:--------------------------|:-----------------------------------|:-------------------------------|:------------------------------------|:-----------------|
| 0 | 2004 | boogie woogie-chalo america | dance contestant | set (sony entertainment television) | finalist (top 5) |
| 1 | 2007 (may-october) | saregamapa challenge | singing contestant | zee network | finalist (top 7) |
| 2 | 2008 (march-may) | rock n roll family | host | zee network | none |
| 3 | 2010 ( released dec. 5th) | ek anhonee (tele-film) | lead role (divyani) | zoom | none |
| 4 | 2011 (june-july) | khatron ke khiladi season 4 | celebrity contestant | colors | finalist (top 2) |
| 5 | 2012 (feb) | kahani comedy circus ki | guest appearance (15 episodes) | set (sony entertainment television) | none |
| 6 | 2013 (feb) | welcome - baazi mehmaan-nawaazi ki | herself | life ok | none | | | | count ( "show" ) |
|---:|-------------------:|
| 0 | 1 | | [
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select # of party list votes - +/- where # of overall seats won = '218 / 497' col : election year | # of constituency votes | # of party list votes | % of party list votes | # of overall seats won | +/- row 1 : 1949 | none | 6934975 | 29.2 | 131 / 402 | none row 2 : 1953 | 8131257 | 7944943 | 28.8 | 162 / 509 | 22 row 3 : 1957 | 11975400 | 11875339 | 39.7 | 181 / 519 | 19 row 4 : 1961 | 11672057 | 11427355 | 36.2 | 203 / 521 | 22 row 5 : 1965 | 12998474 | 12813186 | 39.3 | 217 / 518 | 14 row 6 : 1969 | 14402374 | 14065716 | 42.7 | 237 / 518 | 20 row 7 : 1972 | 18228239 | 17175169 | 45.8 | 242 / 518 | 5 row 8 : 1976 | 16471321 | 16099019 | 42.6 | 224 / 518 | 18 row 9 : 1980 | 16808861 | 16260677 | 42.9 | 218 / 497 | 6 row 10 : 1983 | 15686033 | 14865807 | 38.2 | 193 / 498 | 25 row 11 : 1987 | 14787953 | 14025763 | 37.0 | 186 / 497 | 7 row 12 : 1990 | 16279980 | 15545366 | 33.5 | 239 / 662 | 53 row 13 : 1994 | 17966813 | 17140354 | 36.4 | 252 / 672 | 13 row 14 : 1998 | 21535893 | 20181269 | 40.9 | 298 / 669 | 43 row 15 : 2002 | 20059967 | 18484560 | 38.5 | 251 / 603 | 47 row 16 : 2005 | 18129100 | 16194665 | 34.2 | 222 / 614 | 29 row 17 : 2009 | 12077437 | 9988843 | 23.0 | 146 / 620 | 76 row 18 : 2013 | 12835933 | 11247283 | 25.7 | 193 / 631 | 42 | col : "# of party list votes - +/-" row 1 : # of party list votes - +/- | select # of party list votes - +/- where # of overall seats won = '218 / 497' <table_name> : table \begin{tabular}{lllllll}
\toprule
& election year & # of constituency votes & # of party list votes & % of party list votes & # of overall seats won & +/- \\
\midrule
0 & 1949 & none & 6934975 & 29.2 & 131 / 402 & none \\
1 & 1953 & 8131257 & 7944943 & 28.8 & 162 / 509 & 22 \\
2 & 1957 & 11975400 & 11875339 & 39.7 & 181 / 519 & 19 \\
3 & 1961 & 11672057 & 11427355 & 36.2 & 203 / 521 & 22 \\
4 & 1965 & 12998474 & 12813186 & 39.3 & 217 / 518 & 14 \\
5 & 1969 & 14402374 & 14065716 & 42.7 & 237 / 518 & 20 \\
6 & 1972 & 18228239 & 17175169 & 45.8 & 242 / 518 & 5 \\
7 & 1976 & 16471321 & 16099019 & 42.6 & 224 / 518 & 18 \\
8 & 1980 & 16808861 & 16260677 & 42.9 & 218 / 497 & 6 \\
9 & 1983 & 15686033 & 14865807 & 38.2 & 193 / 498 & 25 \\
10 & 1987 & 14787953 & 14025763 & 37.0 & 186 / 497 & 7 \\
11 & 1990 & 16279980 & 15545366 & 33.5 & 239 / 662 & 53 \\
12 & 1994 & 17966813 & 17140354 & 36.4 & 252 / 672 & 13 \\
13 & 1998 & 21535893 & 20181269 & 40.9 & 298 / 669 & 43 \\
14 & 2002 & 20059967 & 18484560 & 38.5 & 251 / 603 & 47 \\
15 & 2005 & 18129100 & 16194665 & 34.2 & 222 / 614 & 29 \\
16 & 2009 & 12077437 & 9988843 & 23.0 & 146 / 620 & 76 \\
17 & 2013 & 12835933 & 11247283 & 25.7 & 193 / 631 & 42 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "# of party list votes - +/-" \\
\midrule
0 & # of party list votes - +/- \\
\bottomrule
\end{tabular}
| select # of party list votes - +/- where # of overall seats won = '218 / 497' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>election year</th>
<th># of constituency votes</th>
<th># of party list votes</th>
<th>% of party list votes</th>
<th># of overall seats won</th>
<th>+/-</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1949</td>
<td>none</td>
<td>6934975</td>
<td>29.2</td>
<td>131 / 402</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1953</td>
<td>8131257</td>
<td>7944943</td>
<td>28.8</td>
<td>162 / 509</td>
<td>22</td>
</tr>
<tr>
<th>2</th>
<td>1957</td>
<td>11975400</td>
<td>11875339</td>
<td>39.7</td>
<td>181 / 519</td>
<td>19</td>
</tr>
<tr>
<th>3</th>
<td>1961</td>
<td>11672057</td>
<td>11427355</td>
<td>36.2</td>
<td>203 / 521</td>
<td>22</td>
</tr>
<tr>
<th>4</th>
<td>1965</td>
<td>12998474</td>
<td>12813186</td>
<td>39.3</td>
<td>217 / 518</td>
<td>14</td>
</tr>
<tr>
<th>5</th>
<td>1969</td>
<td>14402374</td>
<td>14065716</td>
<td>42.7</td>
<td>237 / 518</td>
<td>20</td>
</tr>
<tr>
<th>6</th>
<td>1972</td>
<td>18228239</td>
<td>17175169</td>
<td>45.8</td>
<td>242 / 518</td>
<td>5</td>
</tr>
<tr>
<th>7</th>
<td>1976</td>
<td>16471321</td>
<td>16099019</td>
<td>42.6</td>
<td>224 / 518</td>
<td>18</td>
</tr>
<tr>
<th>8</th>
<td>1980</td>
<td>16808861</td>
<td>16260677</td>
<td>42.9</td>
<td>218 / 497</td>
<td>6</td>
</tr>
<tr>
<th>9</th>
<td>1983</td>
<td>15686033</td>
<td>14865807</td>
<td>38.2</td>
<td>193 / 498</td>
<td>25</td>
</tr>
<tr>
<th>10</th>
<td>1987</td>
<td>14787953</td>
<td>14025763</td>
<td>37.0</td>
<td>186 / 497</td>
<td>7</td>
</tr>
<tr>
<th>11</th>
<td>1990</td>
<td>16279980</td>
<td>15545366</td>
<td>33.5</td>
<td>239 / 662</td>
<td>53</td>
</tr>
<tr>
<th>12</th>
<td>1994</td>
<td>17966813</td>
<td>17140354</td>
<td>36.4</td>
<td>252 / 672</td>
<td>13</td>
</tr>
<tr>
<th>13</th>
<td>1998</td>
<td>21535893</td>
<td>20181269</td>
<td>40.9</td>
<td>298 / 669</td>
<td>43</td>
</tr>
<tr>
<th>14</th>
<td>2002</td>
<td>20059967</td>
<td>18484560</td>
<td>38.5</td>
<td>251 / 603</td>
<td>47</td>
</tr>
<tr>
<th>15</th>
<td>2005</td>
<td>18129100</td>
<td>16194665</td>
<td>34.2</td>
<td>222 / 614</td>
<td>29</td>
</tr>
<tr>
<th>16</th>
<td>2009</td>
<td>12077437</td>
<td>9988843</td>
<td>23.0</td>
<td>146 / 620</td>
<td>76</td>
</tr>
<tr>
<th>17</th>
<td>2013</td>
<td>12835933</td>
<td>11247283</td>
<td>25.7</td>
<td>193 / 631</td>
<td>42</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"# of party list votes - +/-"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td># of party list votes - +/-</td>
</tr>
</tbody>
</table> | select # of party list votes - +/- where # of overall seats won = '218 / 497' <table_name> : table | | election year | # of constituency votes | # of party list votes | % of party list votes | # of overall seats won | +/- |
|---:|----------------:|:--------------------------|------------------------:|------------------------:|:-------------------------|:------|
| 0 | 1949 | none | 6934975 | 29.2 | 131 / 402 | none |
| 1 | 1953 | 8131257 | 7944943 | 28.8 | 162 / 509 | 22 |
| 2 | 1957 | 11975400 | 11875339 | 39.7 | 181 / 519 | 19 |
| 3 | 1961 | 11672057 | 11427355 | 36.2 | 203 / 521 | 22 |
| 4 | 1965 | 12998474 | 12813186 | 39.3 | 217 / 518 | 14 |
| 5 | 1969 | 14402374 | 14065716 | 42.7 | 237 / 518 | 20 |
| 6 | 1972 | 18228239 | 17175169 | 45.8 | 242 / 518 | 5 |
| 7 | 1976 | 16471321 | 16099019 | 42.6 | 224 / 518 | 18 |
| 8 | 1980 | 16808861 | 16260677 | 42.9 | 218 / 497 | 6 |
| 9 | 1983 | 15686033 | 14865807 | 38.2 | 193 / 498 | 25 |
| 10 | 1987 | 14787953 | 14025763 | 37 | 186 / 497 | 7 |
| 11 | 1990 | 16279980 | 15545366 | 33.5 | 239 / 662 | 53 |
| 12 | 1994 | 17966813 | 17140354 | 36.4 | 252 / 672 | 13 |
| 13 | 1998 | 21535893 | 20181269 | 40.9 | 298 / 669 | 43 |
| 14 | 2002 | 20059967 | 18484560 | 38.5 | 251 / 603 | 47 |
| 15 | 2005 | 18129100 | 16194665 | 34.2 | 222 / 614 | 29 |
| 16 | 2009 | 12077437 | 9988843 | 23 | 146 / 620 | 76 |
| 17 | 2013 | 12835933 | 11247283 | 25.7 | 193 / 631 | 42 | | | | "# of party list votes - +/-" |
|---:|:--------------------------------|
| 0 | # of party list votes - +/- | | [
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select date where home/away = 'away' order by date limit 1290 col : week | date | opponent | home/away | result | bye row 1 : 1 | february 8 | new orleans voodoo | home | l 42-34 | 0 row 2 : 2 | february 15 | dallas desperados | away | l 51-47 | 0 row 3 : 3 | february 21 | columbus destroyers | home | w 56-34 | 0 row 4 : 4 | february 29 | tampa bay storm | away | l 40-37 | 0 row 5 : 5 | march 7 | chicago rush | home | w 53-47 | 0 row 6 : 6 | march 13 | columbus destroyers | away | l 43-41 | 0 row 7 : 7 | march 21 | colorado crush | home | l 40-33 | 0 row 8 : 8 | march 28 | austin wranglers | away | w 65-60 | 0 row 9 : 9 | april 4 | dallas desperados | home | w 47-31 | 0 row 10 : 10 | none | none | week | none | 1 row 11 : 11 | april 17 | carolina cobras | away | l 63-59 | 0 row 12 : 12 | april 24 | new york dragons | home | w 60-58 | 0 row 13 : 13 | may 1 | colorado crush | away | l 58-40 | 0 row 14 : 14 | may 8 | las vegas gladiators | home | l 63-35 | 0 row 15 : 15 | may 15 | carolina cobras | home | l 46-43 | 0 row 16 : 16 | may 22 | san jose sabercats | away | l 48-36 | 0 row 17 : 17 | may 30 | new york dragons | away | l 69-54 | 0 | col : date row 1 : april 17 row 2 : february 15 row 3 : february 29 row 4 : march 13 row 5 : march 28 row 6 : may 1 row 7 : may 22 row 8 : may 30 | select date where home/away = 'away' order by date limit 1290 <table_name> : table \begin{tabular}{lllllll}
\toprule
& week & date & opponent & home/away & result & bye \\
\midrule
0 & 1 & february 8 & new orleans voodoo & home & l 42-34 & 0 \\
1 & 2 & february 15 & dallas desperados & away & l 51-47 & 0 \\
2 & 3 & february 21 & columbus destroyers & home & w 56-34 & 0 \\
3 & 4 & february 29 & tampa bay storm & away & l 40-37 & 0 \\
4 & 5 & march 7 & chicago rush & home & w 53-47 & 0 \\
5 & 6 & march 13 & columbus destroyers & away & l 43-41 & 0 \\
6 & 7 & march 21 & colorado crush & home & l 40-33 & 0 \\
7 & 8 & march 28 & austin wranglers & away & w 65-60 & 0 \\
8 & 9 & april 4 & dallas desperados & home & w 47-31 & 0 \\
9 & 10 & none & none & week & none & 1 \\
10 & 11 & april 17 & carolina cobras & away & l 63-59 & 0 \\
11 & 12 & april 24 & new york dragons & home & w 60-58 & 0 \\
12 & 13 & may 1 & colorado crush & away & l 58-40 & 0 \\
13 & 14 & may 8 & las vegas gladiators & home & l 63-35 & 0 \\
14 & 15 & may 15 & carolina cobras & home & l 46-43 & 0 \\
15 & 16 & may 22 & san jose sabercats & away & l 48-36 & 0 \\
16 & 17 & may 30 & new york dragons & away & l 69-54 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& date \\
\midrule
0 & april 17 \\
1 & february 15 \\
2 & february 29 \\
3 & march 13 \\
4 & march 28 \\
5 & may 1 \\
6 & may 22 \\
7 & may 30 \\
\bottomrule
\end{tabular}
| select date where home/away = 'away' order by date limit 1290 <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>home/away</th>
<th>result</th>
<th>bye</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>february 8</td>
<td>new orleans voodoo</td>
<td>home</td>
<td>l 42-34</td>
<td>0</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>february 15</td>
<td>dallas desperados</td>
<td>away</td>
<td>l 51-47</td>
<td>0</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>february 21</td>
<td>columbus destroyers</td>
<td>home</td>
<td>w 56-34</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>february 29</td>
<td>tampa bay storm</td>
<td>away</td>
<td>l 40-37</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>march 7</td>
<td>chicago rush</td>
<td>home</td>
<td>w 53-47</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>march 13</td>
<td>columbus destroyers</td>
<td>away</td>
<td>l 43-41</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>march 21</td>
<td>colorado crush</td>
<td>home</td>
<td>l 40-33</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>march 28</td>
<td>austin wranglers</td>
<td>away</td>
<td>w 65-60</td>
<td>0</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>april 4</td>
<td>dallas desperados</td>
<td>home</td>
<td>w 47-31</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>none</td>
<td>none</td>
<td>week</td>
<td>none</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>april 17</td>
<td>carolina cobras</td>
<td>away</td>
<td>l 63-59</td>
<td>0</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>april 24</td>
<td>new york dragons</td>
<td>home</td>
<td>w 60-58</td>
<td>0</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>may 1</td>
<td>colorado crush</td>
<td>away</td>
<td>l 58-40</td>
<td>0</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>may 8</td>
<td>las vegas gladiators</td>
<td>home</td>
<td>l 63-35</td>
<td>0</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>may 15</td>
<td>carolina cobras</td>
<td>home</td>
<td>l 46-43</td>
<td>0</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>may 22</td>
<td>san jose sabercats</td>
<td>away</td>
<td>l 48-36</td>
<td>0</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>may 30</td>
<td>new york dragons</td>
<td>away</td>
<td>l 69-54</td>
<td>0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>april 17</td>
</tr>
<tr>
<th>1</th>
<td>february 15</td>
</tr>
<tr>
<th>2</th>
<td>february 29</td>
</tr>
<tr>
<th>3</th>
<td>march 13</td>
</tr>
<tr>
<th>4</th>
<td>march 28</td>
</tr>
<tr>
<th>5</th>
<td>may 1</td>
</tr>
<tr>
<th>6</th>
<td>may 22</td>
</tr>
<tr>
<th>7</th>
<td>may 30</td>
</tr>
</tbody>
</table> | select date where home/away = 'away' order by date limit 1290 <table_name> : table | | week | date | opponent | home/away | result | bye |
|---:|-------:|:------------|:---------------------|:------------|:---------|------:|
| 0 | 1 | february 8 | new orleans voodoo | home | l 42-34 | 0 |
| 1 | 2 | february 15 | dallas desperados | away | l 51-47 | 0 |
| 2 | 3 | february 21 | columbus destroyers | home | w 56-34 | 0 |
| 3 | 4 | february 29 | tampa bay storm | away | l 40-37 | 0 |
| 4 | 5 | march 7 | chicago rush | home | w 53-47 | 0 |
| 5 | 6 | march 13 | columbus destroyers | away | l 43-41 | 0 |
| 6 | 7 | march 21 | colorado crush | home | l 40-33 | 0 |
| 7 | 8 | march 28 | austin wranglers | away | w 65-60 | 0 |
| 8 | 9 | april 4 | dallas desperados | home | w 47-31 | 0 |
| 9 | 10 | none | none | week | none | 1 |
| 10 | 11 | april 17 | carolina cobras | away | l 63-59 | 0 |
| 11 | 12 | april 24 | new york dragons | home | w 60-58 | 0 |
| 12 | 13 | may 1 | colorado crush | away | l 58-40 | 0 |
| 13 | 14 | may 8 | las vegas gladiators | home | l 63-35 | 0 |
| 14 | 15 | may 15 | carolina cobras | home | l 46-43 | 0 |
| 15 | 16 | may 22 | san jose sabercats | away | l 48-36 | 0 |
| 16 | 17 | may 30 | new york dragons | away | l 69-54 | 0 | | | | date |
|---:|:------------|
| 0 | april 17 |
| 1 | february 15 |
| 2 | february 29 |
| 3 | march 13 |
| 4 | march 28 |
| 5 | may 1 |
| 6 | may 22 |
| 7 | may 30 | | [
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] |
select count ( title ) where producer(s) = 'none' and songwriters = 113 col : # | title | songwriters | producer(s) | performer (s) row 1 : 1 | "a dream" | l. lynn, w. adams, m.l. king jr | will.i.am | common, will.i.am row 2 : 2 | "listen!!!" | t.k. greene, k. holland, f. williams | kwame | talib kweli row 3 : 3 | "it's r time [lenky remix]" | j. ortega, v. santiago, l. vazquez, r. ramirez, k. ravenell, e. almonte | none | jeannie ortega row 4 : 4 | "when the ship goes down (diamond d remix)" | l. freese, l. muggerud, l. dickens | dj muggs | cypress hill row 5 : 5 | "hip hop hooray" | v. brown, a. criss, k. gist, e. isley, ru. isley, ro. isley, o. isley, m. isley | naughty by nature | naughty by nature row 6 : 6 | "keep ya head up" | t. shakur, d. anderson, s. vincent, r. troutman | dj daryl | 2pac row 7 : 7 | "code of the streets" | k. elam, c. martin, r. russell | dj premier | gang starr row 8 : 8 | "rebirth of slick (cool like dat)" | i. butler, c. irving, m. vieira, j. williams | butterfly | digable planets row 9 : 9 | "officer" | t. hardson, j. martinez, r. robinson, d. stewart, e. wilcox | j-swift | the pharcyde row 10 : 10 | "this is how we do it" | m. jordan, o. pierce, r. walters | montell jordan, oji pierce | montell jordan row 11 : 11 | "colors" | w. adams | will.i.am | will.i.am row 12 : 12 | "bus ride" | w. adams | will.i.am | will.i.am row 13 : 13 | "riots" | m. isham, w. adams | none | mark isham, miri ben-ari, will.i.am row 14 : 14 | "eva's theme" | m. isham | none | mark isham row 15 : 15 | "anne frank" | m. isham | none | mark isham, miri ben-ari | col : count ( "title" ) row 1 : 0 | select count ( title ) where producer(s) = 'none' and songwriters = 113 <table_name> : table \begin{tabular}{llllll}
\toprule
& # & title & songwriters & producer(s) & performer (s) \\
\midrule
0 & 1 & "a dream" & l. lynn, w. adams, m.l. king jr & will.i.am & common, will.i.am \\
1 & 2 & "listen!!!" & t.k. greene, k. holland, f. williams & kwame & talib kweli \\
2 & 3 & "it's r time [lenky remix]" & j. ortega, v. santiago, l. vazquez, r. ramirez, k. ravenell, e. almonte & none & jeannie ortega \\
3 & 4 & "when the ship goes down (diamond d remix)" & l. freese, l. muggerud, l. dickens & dj muggs & cypress hill \\
4 & 5 & "hip hop hooray" & v. brown, a. criss, k. gist, e. isley, ru. isley, ro. isley, o. isley, m. isley & naughty by nature & naughty by nature \\
5 & 6 & "keep ya head up" & t. shakur, d. anderson, s. vincent, r. troutman & dj daryl & 2pac \\
6 & 7 & "code of the streets" & k. elam, c. martin, r. russell & dj premier & gang starr \\
7 & 8 & "rebirth of slick (cool like dat)" & i. butler, c. irving, m. vieira, j. williams & butterfly & digable planets \\
8 & 9 & "officer" & t. hardson, j. martinez, r. robinson, d. stewart, e. wilcox & j-swift & the pharcyde \\
9 & 10 & "this is how we do it" & m. jordan, o. pierce, r. walters & montell jordan, oji pierce & montell jordan \\
10 & 11 & "colors" & w. adams & will.i.am & will.i.am \\
11 & 12 & "bus ride" & w. adams & will.i.am & will.i.am \\
12 & 13 & "riots" & m. isham, w. adams & none & mark isham, miri ben-ari, will.i.am \\
13 & 14 & "eva's theme" & m. isham & none & mark isham \\
14 & 15 & "anne frank" & m. isham & none & mark isham, miri ben-ari \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "title" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( title ) where producer(s) = 'none' and songwriters = 113 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>title</th>
<th>songwriters</th>
<th>producer(s)</th>
<th>performer (s)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>"a dream"</td>
<td>l. lynn, w. adams, m.l. king jr</td>
<td>will.i.am</td>
<td>common, will.i.am</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>"listen!!!"</td>
<td>t.k. greene, k. holland, f. williams</td>
<td>kwame</td>
<td>talib kweli</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>"it's r time [lenky remix]"</td>
<td>j. ortega, v. santiago, l. vazquez, r. ramirez, k. ravenell, e. almonte</td>
<td>none</td>
<td>jeannie ortega</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>"when the ship goes down (diamond d remix)"</td>
<td>l. freese, l. muggerud, l. dickens</td>
<td>dj muggs</td>
<td>cypress hill</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>"hip hop hooray"</td>
<td>v. brown, a. criss, k. gist, e. isley, ru. isley, ro. isley, o. isley, m. isley</td>
<td>naughty by nature</td>
<td>naughty by nature</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>"keep ya head up"</td>
<td>t. shakur, d. anderson, s. vincent, r. troutman</td>
<td>dj daryl</td>
<td>2pac</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>"code of the streets"</td>
<td>k. elam, c. martin, r. russell</td>
<td>dj premier</td>
<td>gang starr</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>"rebirth of slick (cool like dat)"</td>
<td>i. butler, c. irving, m. vieira, j. williams</td>
<td>butterfly</td>
<td>digable planets</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>"officer"</td>
<td>t. hardson, j. martinez, r. robinson, d. stewart, e. wilcox</td>
<td>j-swift</td>
<td>the pharcyde</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>"this is how we do it"</td>
<td>m. jordan, o. pierce, r. walters</td>
<td>montell jordan, oji pierce</td>
<td>montell jordan</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>"colors"</td>
<td>w. adams</td>
<td>will.i.am</td>
<td>will.i.am</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>"bus ride"</td>
<td>w. adams</td>
<td>will.i.am</td>
<td>will.i.am</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>"riots"</td>
<td>m. isham, w. adams</td>
<td>none</td>
<td>mark isham, miri ben-ari, will.i.am</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>"eva's theme"</td>
<td>m. isham</td>
<td>none</td>
<td>mark isham</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>"anne frank"</td>
<td>m. isham</td>
<td>none</td>
<td>mark isham, miri ben-ari</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "title" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( title ) where producer(s) = 'none' and songwriters = 113 <table_name> : table | | # | title | songwriters | producer(s) | performer (s) |
|---:|----:|:--------------------------------------------|:--------------------------------------------------------------------------------|:---------------------------|:------------------------------------|
| 0 | 1 | "a dream" | l. lynn, w. adams, m.l. king jr | will.i.am | common, will.i.am |
| 1 | 2 | "listen!!!" | t.k. greene, k. holland, f. williams | kwame | talib kweli |
| 2 | 3 | "it's r time [lenky remix]" | j. ortega, v. santiago, l. vazquez, r. ramirez, k. ravenell, e. almonte | none | jeannie ortega |
| 3 | 4 | "when the ship goes down (diamond d remix)" | l. freese, l. muggerud, l. dickens | dj muggs | cypress hill |
| 4 | 5 | "hip hop hooray" | v. brown, a. criss, k. gist, e. isley, ru. isley, ro. isley, o. isley, m. isley | naughty by nature | naughty by nature |
| 5 | 6 | "keep ya head up" | t. shakur, d. anderson, s. vincent, r. troutman | dj daryl | 2pac |
| 6 | 7 | "code of the streets" | k. elam, c. martin, r. russell | dj premier | gang starr |
| 7 | 8 | "rebirth of slick (cool like dat)" | i. butler, c. irving, m. vieira, j. williams | butterfly | digable planets |
| 8 | 9 | "officer" | t. hardson, j. martinez, r. robinson, d. stewart, e. wilcox | j-swift | the pharcyde |
| 9 | 10 | "this is how we do it" | m. jordan, o. pierce, r. walters | montell jordan, oji pierce | montell jordan |
| 10 | 11 | "colors" | w. adams | will.i.am | will.i.am |
| 11 | 12 | "bus ride" | w. adams | will.i.am | will.i.am |
| 12 | 13 | "riots" | m. isham, w. adams | none | mark isham, miri ben-ari, will.i.am |
| 13 | 14 | "eva's theme" | m. isham | none | mark isham |
| 14 | 15 | "anne frank" | m. isham | none | mark isham, miri ben-ari | | | | count ( "title" ) |
|---:|--------------------:|
| 0 | 0 | | [
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] |
select event where nation = 'ethiopia' col : event | performance | athlete | nation | place | date row 1 : 100 m | 9.72 | usain bolt | jamaica | new york city ny, usa | may 31 row 2 : 100 m | 9.69 | usain bolt | jamaica | beijing, china | august 16 row 3 : 200 m | 19.3 | usain bolt | jamaica | beijing, china | august 20 row 4 : 4 x 100 m relay | 37.1 | nesta carter michael frater usain bolt asafa powell | jamaica | beijing, china | august 22 row 5 : 110 m hurdles | 12.87 | dayron robles | cuba | ostrava, czech republic | june 12 row 6 : 50 km race walk | 3:34:14 | denis nizhegorodov | russia | cheboksary, russia | may 11 row 7 : marathon | 2:03:59 | haile gebrselassie | ethiopia | berlin, germany | september 28 | col : event row 1 : marathon | select event where nation = 'ethiopia' <table_name> : table \begin{tabular}{lllllll}
\toprule
& event & performance & athlete & nation & place & date \\
\midrule
0 & 100 m & 9.72 & usain bolt & jamaica & new york city ny, usa & may 31 \\
1 & 100 m & 9.69 & usain bolt & jamaica & beijing, china & august 16 \\
2 & 200 m & 19.3 & usain bolt & jamaica & beijing, china & august 20 \\
3 & 4 x 100 m relay & 37.1 & nesta carter michael frater usain bolt asafa powell & jamaica & beijing, china & august 22 \\
4 & 110 m hurdles & 12.87 & dayron robles & cuba & ostrava, czech republic & june 12 \\
5 & 50 km race walk & 3:34:14 & denis nizhegorodov & russia & cheboksary, russia & may 11 \\
6 & marathon & 2:03:59 & haile gebrselassie & ethiopia & berlin, germany & september 28 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& event \\
\midrule
0 & marathon \\
\bottomrule
\end{tabular}
| select event where nation = 'ethiopia' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>event</th>
<th>performance</th>
<th>athlete</th>
<th>nation</th>
<th>place</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>100 m</td>
<td>9.72</td>
<td>usain bolt</td>
<td>jamaica</td>
<td>new york city ny, usa</td>
<td>may 31</td>
</tr>
<tr>
<th>1</th>
<td>100 m</td>
<td>9.69</td>
<td>usain bolt</td>
<td>jamaica</td>
<td>beijing, china</td>
<td>august 16</td>
</tr>
<tr>
<th>2</th>
<td>200 m</td>
<td>19.3</td>
<td>usain bolt</td>
<td>jamaica</td>
<td>beijing, china</td>
<td>august 20</td>
</tr>
<tr>
<th>3</th>
<td>4 x 100 m relay</td>
<td>37.1</td>
<td>nesta carter michael frater usain bolt asafa powell</td>
<td>jamaica</td>
<td>beijing, china</td>
<td>august 22</td>
</tr>
<tr>
<th>4</th>
<td>110 m hurdles</td>
<td>12.87</td>
<td>dayron robles</td>
<td>cuba</td>
<td>ostrava, czech republic</td>
<td>june 12</td>
</tr>
<tr>
<th>5</th>
<td>50 km race walk</td>
<td>3:34:14</td>
<td>denis nizhegorodov</td>
<td>russia</td>
<td>cheboksary, russia</td>
<td>may 11</td>
</tr>
<tr>
<th>6</th>
<td>marathon</td>
<td>2:03:59</td>
<td>haile gebrselassie</td>
<td>ethiopia</td>
<td>berlin, germany</td>
<td>september 28</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>event</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>marathon</td>
</tr>
</tbody>
</table> | select event where nation = 'ethiopia' <table_name> : table | | event | performance | athlete | nation | place | date |
|---:|:----------------|:--------------|:----------------------------------------------------|:---------|:------------------------|:-------------|
| 0 | 100 m | 9.72 | usain bolt | jamaica | new york city ny, usa | may 31 |
| 1 | 100 m | 9.69 | usain bolt | jamaica | beijing, china | august 16 |
| 2 | 200 m | 19.3 | usain bolt | jamaica | beijing, china | august 20 |
| 3 | 4 x 100 m relay | 37.1 | nesta carter michael frater usain bolt asafa powell | jamaica | beijing, china | august 22 |
| 4 | 110 m hurdles | 12.87 | dayron robles | cuba | ostrava, czech republic | june 12 |
| 5 | 50 km race walk | 3:34:14 | denis nizhegorodov | russia | cheboksary, russia | may 11 |
| 6 | marathon | 2:03:59 | haile gebrselassie | ethiopia | berlin, germany | september 28 | | | | event |
|---:|:---------|
| 0 | marathon | | [
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select count ( constructor ) where time/retired < 626 col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 4 | robert kubica | bmw sauber | 70 | 1:36:24.227 | 2 | 10 row 2 : 2 | 3 | nick heidfeld | bmw sauber | 70 | 16.495 | 8 | 8 row 3 : 3 | 9 | david coulthard | red bull-renault | 70 | 23.352 | 13 | 6 row 4 : 4 | 12 | timo glock | toyota | 70 | 42.627 | 11 | 5 row 5 : 5 | 2 | felipe massa | ferrari | 70 | 43.934 | 6 | 4 row 6 : 6 | 11 | jarno trulli | toyota | 70 | 47.775 | 14 | 3 row 7 : 7 | 17 | rubens barrichello | honda | 70 | 53.597 | 9 | 2 row 8 : 8 | 15 | sebastian vettel | toro rosso-ferrari | 70 | 54.12 | 19 | 1 row 9 : 9 | 23 | heikki kovalainen | mclaren-mercedes | 70 | 54.433 | 7 | none row 10 : 10 | 7 | nico rosberg | williams-toyota | 70 | 54.749 | 5 | none row 11 : 11 | 16 | jenson button | honda | 70 | +1:07.540 | 20 | none row 12 : 12 | 10 | mark webber | red bull-renault | 70 | +1:11.299 | 10 | none row 13 : 13 | 14 | sebastien bourdais | toro rosso-ferrari | 69 | +1 lap | 18 | none row 14 : ret | 21 | giancarlo fisichella | force india-ferrari | 51 | spun off | 17 | none row 15 : ret | 8 | kazuki nakajima | williams-toyota | 46 | accident | 12 | none row 16 : ret | 5 | fernando alonso | renault | 44 | spun off | 4 | none row 17 : ret | 6 | nelson piquet jr | renault | 43 | brakes | 15 | none row 18 : ret | 1 | kimi raikkonen | ferrari | 19 | collision | 3 | none row 19 : ret | 22 | lewis hamilton | mclaren-mercedes | 19 | collision | 1 | none row 20 : ret | 20 | adrian sutil | force india-ferrari | 13 | gearbox | 16 | none | col : count ( "constructor" ) row 1 : 13 | select count ( constructor ) where time/retired < 626 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & constructor & laps & time/retired & grid & points \\
\midrule
0 & 1 & 4 & robert kubica & bmw sauber & 70 & 1:36:24.227 & 2 & 10 \\
1 & 2 & 3 & nick heidfeld & bmw sauber & 70 & 16.495 & 8 & 8 \\
2 & 3 & 9 & david coulthard & red bull-renault & 70 & 23.352 & 13 & 6 \\
3 & 4 & 12 & timo glock & toyota & 70 & 42.627 & 11 & 5 \\
4 & 5 & 2 & felipe massa & ferrari & 70 & 43.934 & 6 & 4 \\
5 & 6 & 11 & jarno trulli & toyota & 70 & 47.775 & 14 & 3 \\
6 & 7 & 17 & rubens barrichello & honda & 70 & 53.597 & 9 & 2 \\
7 & 8 & 15 & sebastian vettel & toro rosso-ferrari & 70 & 54.12 & 19 & 1 \\
8 & 9 & 23 & heikki kovalainen & mclaren-mercedes & 70 & 54.433 & 7 & none \\
9 & 10 & 7 & nico rosberg & williams-toyota & 70 & 54.749 & 5 & none \\
10 & 11 & 16 & jenson button & honda & 70 & +1:07.540 & 20 & none \\
11 & 12 & 10 & mark webber & red bull-renault & 70 & +1:11.299 & 10 & none \\
12 & 13 & 14 & sebastien bourdais & toro rosso-ferrari & 69 & +1 lap & 18 & none \\
13 & ret & 21 & giancarlo fisichella & force india-ferrari & 51 & spun off & 17 & none \\
14 & ret & 8 & kazuki nakajima & williams-toyota & 46 & accident & 12 & none \\
15 & ret & 5 & fernando alonso & renault & 44 & spun off & 4 & none \\
16 & ret & 6 & nelson piquet jr & renault & 43 & brakes & 15 & none \\
17 & ret & 1 & kimi raikkonen & ferrari & 19 & collision & 3 & none \\
18 & ret & 22 & lewis hamilton & mclaren-mercedes & 19 & collision & 1 & none \\
19 & ret & 20 & adrian sutil & force india-ferrari & 13 & gearbox & 16 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "constructor" ) \\
\midrule
0 & 13 \\
\bottomrule
\end{tabular}
| select count ( constructor ) where time/retired < 626 <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>4</td>
<td>robert kubica</td>
<td>bmw sauber</td>
<td>70</td>
<td>1:36:24.227</td>
<td>2</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>3</td>
<td>nick heidfeld</td>
<td>bmw sauber</td>
<td>70</td>
<td>16.495</td>
<td>8</td>
<td>8</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>9</td>
<td>david coulthard</td>
<td>red bull-renault</td>
<td>70</td>
<td>23.352</td>
<td>13</td>
<td>6</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>12</td>
<td>timo glock</td>
<td>toyota</td>
<td>70</td>
<td>42.627</td>
<td>11</td>
<td>5</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2</td>
<td>felipe massa</td>
<td>ferrari</td>
<td>70</td>
<td>43.934</td>
<td>6</td>
<td>4</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>11</td>
<td>jarno trulli</td>
<td>toyota</td>
<td>70</td>
<td>47.775</td>
<td>14</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>17</td>
<td>rubens barrichello</td>
<td>honda</td>
<td>70</td>
<td>53.597</td>
<td>9</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>15</td>
<td>sebastian vettel</td>
<td>toro rosso-ferrari</td>
<td>70</td>
<td>54.12</td>
<td>19</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>23</td>
<td>heikki kovalainen</td>
<td>mclaren-mercedes</td>
<td>70</td>
<td>54.433</td>
<td>7</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>7</td>
<td>nico rosberg</td>
<td>williams-toyota</td>
<td>70</td>
<td>54.749</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>16</td>
<td>jenson button</td>
<td>honda</td>
<td>70</td>
<td>+1:07.540</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>10</td>
<td>mark webber</td>
<td>red bull-renault</td>
<td>70</td>
<td>+1:11.299</td>
<td>10</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>14</td>
<td>sebastien bourdais</td>
<td>toro rosso-ferrari</td>
<td>69</td>
<td>+1 lap</td>
<td>18</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>ret</td>
<td>21</td>
<td>giancarlo fisichella</td>
<td>force india-ferrari</td>
<td>51</td>
<td>spun off</td>
<td>17</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>ret</td>
<td>8</td>
<td>kazuki nakajima</td>
<td>williams-toyota</td>
<td>46</td>
<td>accident</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>ret</td>
<td>5</td>
<td>fernando alonso</td>
<td>renault</td>
<td>44</td>
<td>spun off</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>ret</td>
<td>6</td>
<td>nelson piquet jr</td>
<td>renault</td>
<td>43</td>
<td>brakes</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>ret</td>
<td>1</td>
<td>kimi raikkonen</td>
<td>ferrari</td>
<td>19</td>
<td>collision</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>22</td>
<td>lewis hamilton</td>
<td>mclaren-mercedes</td>
<td>19</td>
<td>collision</td>
<td>1</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>20</td>
<td>adrian sutil</td>
<td>force india-ferrari</td>
<td>13</td>
<td>gearbox</td>
<td>16</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "constructor" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>13</td>
</tr>
</tbody>
</table> | select count ( constructor ) where time/retired < 626 <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points |
|---:|:------|-----:|:---------------------|:--------------------|-------:|:---------------|-------:|:---------|
| 0 | 1 | 4 | robert kubica | bmw sauber | 70 | 1:36:24.227 | 2 | 10 |
| 1 | 2 | 3 | nick heidfeld | bmw sauber | 70 | 16.495 | 8 | 8 |
| 2 | 3 | 9 | david coulthard | red bull-renault | 70 | 23.352 | 13 | 6 |
| 3 | 4 | 12 | timo glock | toyota | 70 | 42.627 | 11 | 5 |
| 4 | 5 | 2 | felipe massa | ferrari | 70 | 43.934 | 6 | 4 |
| 5 | 6 | 11 | jarno trulli | toyota | 70 | 47.775 | 14 | 3 |
| 6 | 7 | 17 | rubens barrichello | honda | 70 | 53.597 | 9 | 2 |
| 7 | 8 | 15 | sebastian vettel | toro rosso-ferrari | 70 | 54.12 | 19 | 1 |
| 8 | 9 | 23 | heikki kovalainen | mclaren-mercedes | 70 | 54.433 | 7 | none |
| 9 | 10 | 7 | nico rosberg | williams-toyota | 70 | 54.749 | 5 | none |
| 10 | 11 | 16 | jenson button | honda | 70 | +1:07.540 | 20 | none |
| 11 | 12 | 10 | mark webber | red bull-renault | 70 | +1:11.299 | 10 | none |
| 12 | 13 | 14 | sebastien bourdais | toro rosso-ferrari | 69 | +1 lap | 18 | none |
| 13 | ret | 21 | giancarlo fisichella | force india-ferrari | 51 | spun off | 17 | none |
| 14 | ret | 8 | kazuki nakajima | williams-toyota | 46 | accident | 12 | none |
| 15 | ret | 5 | fernando alonso | renault | 44 | spun off | 4 | none |
| 16 | ret | 6 | nelson piquet jr | renault | 43 | brakes | 15 | none |
| 17 | ret | 1 | kimi raikkonen | ferrari | 19 | collision | 3 | none |
| 18 | ret | 22 | lewis hamilton | mclaren-mercedes | 19 | collision | 1 | none |
| 19 | ret | 20 | adrian sutil | force india-ferrari | 13 | gearbox | 16 | none | | | | count ( "constructor" ) |
|---:|--------------------------:|
| 0 | 13 | | [
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select event where event = 'marathon' and year = 1982 col : year | competition | venue | position | event | notes row 1 : 1982 | african championships | cairo, egypt | 1st | marathon | 2:21:05 row 2 : 1982 | commonwealth games | brisbane, australia | 2nd | marathon | 2:09:30 row 3 : 1983 | world championships | helsinki, finland | 15th | marathon | 2:13:11 row 4 : 1983 | melbourne marathon | melbourne, australia | 1st | marathon | 2:13:50 row 5 : 1984 | tokyo marathon | tokyo, japan | 1st | marathon | 2:10:49 row 6 : 1984 | olympic games | los angeles, united states | 6th | marathon | 2:11:10 row 7 : 1984 | melbourne marathon | melbourne, australia | 1st | marathon | 2:15:31 row 8 : 1986 | tokyo marathon | tokyo, japan | 1st | marathon | 2:08:10 row 9 : 1986 | fukuoka marathon | fukuoka, japan | 1st | marathon | 2:10:06 row 10 : 1987 | world championships | rome, italy | 6th | marathon | 2:13:43 row 11 : 1987 | beijing marathon | beijing, pr china | 1st | marathon | 2:12:19 row 12 : 1988 | olympic games | seoul, south korea | 7th | marathon | 2:13:06 row 13 : 1988 | boston marathon | boston, united states | 2nd | marathon | none row 14 : 1989 | new york city marathon | new york, united states | 1st | marathon | 2:08:01 row 15 : 1989 | boston marathon | boston, united states | 2nd | marathon | none row 16 : 1990 | boston marathon | boston, united states | 2nd | marathon | none row 17 : 1992 | olympic games | barcelona, spain | 34th | marathon | 2:19:34 row 18 : 1993 | world championships | stuttgart, germany | 21st | marathon | 2:24:23 row 19 : 1995 | world championships | gothenburg, sweden | 43rd | marathon | 2:30:53 | col : event row 1 : marathon row 2 : marathon | select event where event = 'marathon' and year = 1982 <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & competition & venue & position & event & notes \\
\midrule
0 & 1982 & african championships & cairo, egypt & 1st & marathon & 2:21:05 \\
1 & 1982 & commonwealth games & brisbane, australia & 2nd & marathon & 2:09:30 \\
2 & 1983 & world championships & helsinki, finland & 15th & marathon & 2:13:11 \\
3 & 1983 & melbourne marathon & melbourne, australia & 1st & marathon & 2:13:50 \\
4 & 1984 & tokyo marathon & tokyo, japan & 1st & marathon & 2:10:49 \\
5 & 1984 & olympic games & los angeles, united states & 6th & marathon & 2:11:10 \\
6 & 1984 & melbourne marathon & melbourne, australia & 1st & marathon & 2:15:31 \\
7 & 1986 & tokyo marathon & tokyo, japan & 1st & marathon & 2:08:10 \\
8 & 1986 & fukuoka marathon & fukuoka, japan & 1st & marathon & 2:10:06 \\
9 & 1987 & world championships & rome, italy & 6th & marathon & 2:13:43 \\
10 & 1987 & beijing marathon & beijing, pr china & 1st & marathon & 2:12:19 \\
11 & 1988 & olympic games & seoul, south korea & 7th & marathon & 2:13:06 \\
12 & 1988 & boston marathon & boston, united states & 2nd & marathon & none \\
13 & 1989 & new york city marathon & new york, united states & 1st & marathon & 2:08:01 \\
14 & 1989 & boston marathon & boston, united states & 2nd & marathon & none \\
15 & 1990 & boston marathon & boston, united states & 2nd & marathon & none \\
16 & 1992 & olympic games & barcelona, spain & 34th & marathon & 2:19:34 \\
17 & 1993 & world championships & stuttgart, germany & 21st & marathon & 2:24:23 \\
18 & 1995 & world championships & gothenburg, sweden & 43rd & marathon & 2:30:53 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& event \\
\midrule
0 & marathon \\
1 & marathon \\
\bottomrule
\end{tabular}
| select event where event = 'marathon' and year = 1982 <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>1982</td>
<td>african championships</td>
<td>cairo, egypt</td>
<td>1st</td>
<td>marathon</td>
<td>2:21:05</td>
</tr>
<tr>
<th>1</th>
<td>1982</td>
<td>commonwealth games</td>
<td>brisbane, australia</td>
<td>2nd</td>
<td>marathon</td>
<td>2:09:30</td>
</tr>
<tr>
<th>2</th>
<td>1983</td>
<td>world championships</td>
<td>helsinki, finland</td>
<td>15th</td>
<td>marathon</td>
<td>2:13:11</td>
</tr>
<tr>
<th>3</th>
<td>1983</td>
<td>melbourne marathon</td>
<td>melbourne, australia</td>
<td>1st</td>
<td>marathon</td>
<td>2:13:50</td>
</tr>
<tr>
<th>4</th>
<td>1984</td>
<td>tokyo marathon</td>
<td>tokyo, japan</td>
<td>1st</td>
<td>marathon</td>
<td>2:10:49</td>
</tr>
<tr>
<th>5</th>
<td>1984</td>
<td>olympic games</td>
<td>los angeles, united states</td>
<td>6th</td>
<td>marathon</td>
<td>2:11:10</td>
</tr>
<tr>
<th>6</th>
<td>1984</td>
<td>melbourne marathon</td>
<td>melbourne, australia</td>
<td>1st</td>
<td>marathon</td>
<td>2:15:31</td>
</tr>
<tr>
<th>7</th>
<td>1986</td>
<td>tokyo marathon</td>
<td>tokyo, japan</td>
<td>1st</td>
<td>marathon</td>
<td>2:08:10</td>
</tr>
<tr>
<th>8</th>
<td>1986</td>
<td>fukuoka marathon</td>
<td>fukuoka, japan</td>
<td>1st</td>
<td>marathon</td>
<td>2:10:06</td>
</tr>
<tr>
<th>9</th>
<td>1987</td>
<td>world championships</td>
<td>rome, italy</td>
<td>6th</td>
<td>marathon</td>
<td>2:13:43</td>
</tr>
<tr>
<th>10</th>
<td>1987</td>
<td>beijing marathon</td>
<td>beijing, pr china</td>
<td>1st</td>
<td>marathon</td>
<td>2:12:19</td>
</tr>
<tr>
<th>11</th>
<td>1988</td>
<td>olympic games</td>
<td>seoul, south korea</td>
<td>7th</td>
<td>marathon</td>
<td>2:13:06</td>
</tr>
<tr>
<th>12</th>
<td>1988</td>
<td>boston marathon</td>
<td>boston, united states</td>
<td>2nd</td>
<td>marathon</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>1989</td>
<td>new york city marathon</td>
<td>new york, united states</td>
<td>1st</td>
<td>marathon</td>
<td>2:08:01</td>
</tr>
<tr>
<th>14</th>
<td>1989</td>
<td>boston marathon</td>
<td>boston, united states</td>
<td>2nd</td>
<td>marathon</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>1990</td>
<td>boston marathon</td>
<td>boston, united states</td>
<td>2nd</td>
<td>marathon</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>1992</td>
<td>olympic games</td>
<td>barcelona, spain</td>
<td>34th</td>
<td>marathon</td>
<td>2:19:34</td>
</tr>
<tr>
<th>17</th>
<td>1993</td>
<td>world championships</td>
<td>stuttgart, germany</td>
<td>21st</td>
<td>marathon</td>
<td>2:24:23</td>
</tr>
<tr>
<th>18</th>
<td>1995</td>
<td>world championships</td>
<td>gothenburg, sweden</td>
<td>43rd</td>
<td>marathon</td>
<td>2:30:53</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>event</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>marathon</td>
</tr>
<tr>
<th>1</th>
<td>marathon</td>
</tr>
</tbody>
</table> | select event where event = 'marathon' and year = 1982 <table_name> : table | | year | competition | venue | position | event | notes |
|---:|-------:|:-----------------------|:---------------------------|:-----------|:---------|:--------|
| 0 | 1982 | african championships | cairo, egypt | 1st | marathon | 2:21:05 |
| 1 | 1982 | commonwealth games | brisbane, australia | 2nd | marathon | 2:09:30 |
| 2 | 1983 | world championships | helsinki, finland | 15th | marathon | 2:13:11 |
| 3 | 1983 | melbourne marathon | melbourne, australia | 1st | marathon | 2:13:50 |
| 4 | 1984 | tokyo marathon | tokyo, japan | 1st | marathon | 2:10:49 |
| 5 | 1984 | olympic games | los angeles, united states | 6th | marathon | 2:11:10 |
| 6 | 1984 | melbourne marathon | melbourne, australia | 1st | marathon | 2:15:31 |
| 7 | 1986 | tokyo marathon | tokyo, japan | 1st | marathon | 2:08:10 |
| 8 | 1986 | fukuoka marathon | fukuoka, japan | 1st | marathon | 2:10:06 |
| 9 | 1987 | world championships | rome, italy | 6th | marathon | 2:13:43 |
| 10 | 1987 | beijing marathon | beijing, pr china | 1st | marathon | 2:12:19 |
| 11 | 1988 | olympic games | seoul, south korea | 7th | marathon | 2:13:06 |
| 12 | 1988 | boston marathon | boston, united states | 2nd | marathon | none |
| 13 | 1989 | new york city marathon | new york, united states | 1st | marathon | 2:08:01 |
| 14 | 1989 | boston marathon | boston, united states | 2nd | marathon | none |
| 15 | 1990 | boston marathon | boston, united states | 2nd | marathon | none |
| 16 | 1992 | olympic games | barcelona, spain | 34th | marathon | 2:19:34 |
| 17 | 1993 | world championships | stuttgart, germany | 21st | marathon | 2:24:23 |
| 18 | 1995 | world championships | gothenburg, sweden | 43rd | marathon | 2:30:53 | | | | event |
|---:|:---------|
| 0 | marathon |
| 1 | marathon | | [
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select score where points = 29 col : game | november | opponent | score | record | points row 1 : 13 | 2 | @ florida panthers | 4-3 | 10-3-0 | 20 row 2 : 14 | 4 | quebec nordiques | 4-1 | 11-3-0 | 22 row 3 : 15 | 6 | @ toronto maple leafs | 3-5 | 11-4-0 | 22 row 4 : 16 | 7 | vancouver canucks | 2-5 | 11-5-0 | 22 row 5 : 17 | 10 | @ buffalo sabres | 5-3 | 12-5-0 | 24 row 6 : 18 | 11 | new jersey devils | 3-5 | 12-6-0 | 24 row 7 : 19 | 13 | buffalo sabres | 2-7 | 12-7-0 | 24 row 8 : 20 | 16 | @ pittsburgh penguins | 5-11 | 12-8-0 | 24 row 9 : 21 | 18 | hartford whalers | 6-3 | 13-8-0 | 26 row 10 : 22 | 20 | @ boston bruins | 5-5 ot | 13-8-1 | 27 row 11 : 23 | 21 | new york islanders | 4-5 ot | 13-9-1 | 27 row 12 : 24 | 24 | montreal canadiens | 9-2 | 14-9-1 | 29 row 13 : 25 | 26 | tampa bay lightning | 3-0 | 15-9-1 | 31 row 14 : 26 | 27 | @ tampa bay lightning | 4-3 ot | 16-9-1 | 33 | col : score row 1 : 9-2 | select score where points = 29 <table_name> : table \begin{tabular}{lllllll}
\toprule
& game & november & opponent & score & record & points \\
\midrule
0 & 13 & 2 & @ florida panthers & 4-3 & 10-3-0 & 20 \\
1 & 14 & 4 & quebec nordiques & 4-1 & 11-3-0 & 22 \\
2 & 15 & 6 & @ toronto maple leafs & 3-5 & 11-4-0 & 22 \\
3 & 16 & 7 & vancouver canucks & 2-5 & 11-5-0 & 22 \\
4 & 17 & 10 & @ buffalo sabres & 5-3 & 12-5-0 & 24 \\
5 & 18 & 11 & new jersey devils & 3-5 & 12-6-0 & 24 \\
6 & 19 & 13 & buffalo sabres & 2-7 & 12-7-0 & 24 \\
7 & 20 & 16 & @ pittsburgh penguins & 5-11 & 12-8-0 & 24 \\
8 & 21 & 18 & hartford whalers & 6-3 & 13-8-0 & 26 \\
9 & 22 & 20 & @ boston bruins & 5-5 ot & 13-8-1 & 27 \\
10 & 23 & 21 & new york islanders & 4-5 ot & 13-9-1 & 27 \\
11 & 24 & 24 & montreal canadiens & 9-2 & 14-9-1 & 29 \\
12 & 25 & 26 & tampa bay lightning & 3-0 & 15-9-1 & 31 \\
13 & 26 & 27 & @ tampa bay lightning & 4-3 ot & 16-9-1 & 33 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& score \\
\midrule
0 & 9-2 \\
\bottomrule
\end{tabular}
| select score where points = 29 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>november</th>
<th>opponent</th>
<th>score</th>
<th>record</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>13</td>
<td>2</td>
<td>@ florida panthers</td>
<td>4-3</td>
<td>10-3-0</td>
<td>20</td>
</tr>
<tr>
<th>1</th>
<td>14</td>
<td>4</td>
<td>quebec nordiques</td>
<td>4-1</td>
<td>11-3-0</td>
<td>22</td>
</tr>
<tr>
<th>2</th>
<td>15</td>
<td>6</td>
<td>@ toronto maple leafs</td>
<td>3-5</td>
<td>11-4-0</td>
<td>22</td>
</tr>
<tr>
<th>3</th>
<td>16</td>
<td>7</td>
<td>vancouver canucks</td>
<td>2-5</td>
<td>11-5-0</td>
<td>22</td>
</tr>
<tr>
<th>4</th>
<td>17</td>
<td>10</td>
<td>@ buffalo sabres</td>
<td>5-3</td>
<td>12-5-0</td>
<td>24</td>
</tr>
<tr>
<th>5</th>
<td>18</td>
<td>11</td>
<td>new jersey devils</td>
<td>3-5</td>
<td>12-6-0</td>
<td>24</td>
</tr>
<tr>
<th>6</th>
<td>19</td>
<td>13</td>
<td>buffalo sabres</td>
<td>2-7</td>
<td>12-7-0</td>
<td>24</td>
</tr>
<tr>
<th>7</th>
<td>20</td>
<td>16</td>
<td>@ pittsburgh penguins</td>
<td>5-11</td>
<td>12-8-0</td>
<td>24</td>
</tr>
<tr>
<th>8</th>
<td>21</td>
<td>18</td>
<td>hartford whalers</td>
<td>6-3</td>
<td>13-8-0</td>
<td>26</td>
</tr>
<tr>
<th>9</th>
<td>22</td>
<td>20</td>
<td>@ boston bruins</td>
<td>5-5 ot</td>
<td>13-8-1</td>
<td>27</td>
</tr>
<tr>
<th>10</th>
<td>23</td>
<td>21</td>
<td>new york islanders</td>
<td>4-5 ot</td>
<td>13-9-1</td>
<td>27</td>
</tr>
<tr>
<th>11</th>
<td>24</td>
<td>24</td>
<td>montreal canadiens</td>
<td>9-2</td>
<td>14-9-1</td>
<td>29</td>
</tr>
<tr>
<th>12</th>
<td>25</td>
<td>26</td>
<td>tampa bay lightning</td>
<td>3-0</td>
<td>15-9-1</td>
<td>31</td>
</tr>
<tr>
<th>13</th>
<td>26</td>
<td>27</td>
<td>@ tampa bay lightning</td>
<td>4-3 ot</td>
<td>16-9-1</td>
<td>33</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>9-2</td>
</tr>
</tbody>
</table> | select score where points = 29 <table_name> : table | | game | november | opponent | score | record | points |
|---:|-------:|-----------:|:----------------------|:--------|:---------|---------:|
| 0 | 13 | 2 | @ florida panthers | 4-3 | 10-3-0 | 20 |
| 1 | 14 | 4 | quebec nordiques | 4-1 | 11-3-0 | 22 |
| 2 | 15 | 6 | @ toronto maple leafs | 3-5 | 11-4-0 | 22 |
| 3 | 16 | 7 | vancouver canucks | 2-5 | 11-5-0 | 22 |
| 4 | 17 | 10 | @ buffalo sabres | 5-3 | 12-5-0 | 24 |
| 5 | 18 | 11 | new jersey devils | 3-5 | 12-6-0 | 24 |
| 6 | 19 | 13 | buffalo sabres | 2-7 | 12-7-0 | 24 |
| 7 | 20 | 16 | @ pittsburgh penguins | 5-11 | 12-8-0 | 24 |
| 8 | 21 | 18 | hartford whalers | 6-3 | 13-8-0 | 26 |
| 9 | 22 | 20 | @ boston bruins | 5-5 ot | 13-8-1 | 27 |
| 10 | 23 | 21 | new york islanders | 4-5 ot | 13-9-1 | 27 |
| 11 | 24 | 24 | montreal canadiens | 9-2 | 14-9-1 | 29 |
| 12 | 25 | 26 | tampa bay lightning | 3-0 | 15-9-1 | 31 |
| 13 | 26 | 27 | @ tampa bay lightning | 4-3 ot | 16-9-1 | 33 | | | | score |
|---:|:--------|
| 0 | 9-2 | | [
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select count ( date ) where date = '11 nov 2007' col : no. | date | tournament | winning score | margin of victory | runner(s)-up row 1 : 1 | 2002-11-03 00:00:00 | philip morris k.k. championship | -19 (65-67-67-70=269) | 2 strokes | toshimitsu izawa row 2 : 2 | 2003-08-10 00:00:00 | sun chlorella classic | -8 (71-73-68-68=280) | 1 stroke | daisuke maruyama, taichi teshima row 3 : 3 | 2004-04-25 00:00:00 | tsuruya open | -9 (64-73-69-69=275) | 2 strokes | keiichiro fukabori, scott laycock, tatsuya mitsuhashi, taichi teshima, shinichi yokota row 4 : 4 | 2004-06-26 00:00:00 | gateway to the open mizuno open | -14 (67-68-70-69=274) | playoff | hiroaki iijima row 5 : 5 | 2006-04-23 00:00:00 | tsuruya open | -11 (70-68-66-69=273) | 2 strokes | mamo osanai row 6 : 6 | 2007-04-22 00:00:00 | tsuruya open | -16 (67-65-68-68=268) | 2 strokes | masahiro kuramoto, hirofumi miyase, takuya taniguchi row 7 : 7 | 2007-11-11 00:00:00 | mitsui sumitomo visa taiheiyo masters | -13 (67-68-69-70=274) | 5 strokes | toru taniguchi row 8 : 8 | 2007-12-02 00:00:00 | golf nippon series jt cup | -11 (70-70-68-61=261) | 1 stroke | toru taniguchi row 9 : 9 | 2010-09-26 00:00:00 | asia-pacific panasonic open (co-sanctioned by the asian tour) | -6 (71-70-66=207) | 1 stroke | ryuichi oda row 10 : 10 | 2011-05-01 00:00:00 | the crowns | -9 (67-66-68-70=271) | playoff | jang ik-jae row 11 : 11 | 2012-04-15 00:00:00 | token homemate cup | -15 (68-69-70-62=269) | 2 strokes | ryuichi oda row 12 : 12 | 2012-07-29 00:00:00 | sun chlorella classic | -15 (69-66-68-70=273) | 2 strokes | lee seong-ho, hideki matsuyama (am), yoshinobu tsukada row 13 : 13 | 2013-06-30 00:00:00 | gateway to the open mizuno open | -19 (67-66-68-68=269) | 3 strokes | kim kyung-tae | col : count ( "date" ) row 1 : 1 | select count ( date ) where date = '11 nov 2007' <table_name> : table \begin{tabular}{lllllll}
\toprule
& no. & date & tournament & winning score & margin of victory & runner(s)-up \\
\midrule
0 & 1 & 2002-11-03 00:00:00 & philip morris k.k. championship & -19 (65-67-67-70=269) & 2 strokes & toshimitsu izawa \\
1 & 2 & 2003-08-10 00:00:00 & sun chlorella classic & -8 (71-73-68-68=280) & 1 stroke & daisuke maruyama, taichi teshima \\
2 & 3 & 2004-04-25 00:00:00 & tsuruya open & -9 (64-73-69-69=275) & 2 strokes & keiichiro fukabori, scott laycock, tatsuya mitsuhashi, taichi teshima, shinichi yokota \\
3 & 4 & 2004-06-26 00:00:00 & gateway to the open mizuno open & -14 (67-68-70-69=274) & playoff & hiroaki iijima \\
4 & 5 & 2006-04-23 00:00:00 & tsuruya open & -11 (70-68-66-69=273) & 2 strokes & mamo osanai \\
5 & 6 & 2007-04-22 00:00:00 & tsuruya open & -16 (67-65-68-68=268) & 2 strokes & masahiro kuramoto, hirofumi miyase, takuya taniguchi \\
6 & 7 & 2007-11-11 00:00:00 & mitsui sumitomo visa taiheiyo masters & -13 (67-68-69-70=274) & 5 strokes & toru taniguchi \\
7 & 8 & 2007-12-02 00:00:00 & golf nippon series jt cup & -11 (70-70-68-61=261) & 1 stroke & toru taniguchi \\
8 & 9 & 2010-09-26 00:00:00 & asia-pacific panasonic open (co-sanctioned by the asian tour) & -6 (71-70-66=207) & 1 stroke & ryuichi oda \\
9 & 10 & 2011-05-01 00:00:00 & the crowns & -9 (67-66-68-70=271) & playoff & jang ik-jae \\
10 & 11 & 2012-04-15 00:00:00 & token homemate cup & -15 (68-69-70-62=269) & 2 strokes & ryuichi oda \\
11 & 12 & 2012-07-29 00:00:00 & sun chlorella classic & -15 (69-66-68-70=273) & 2 strokes & lee seong-ho, hideki matsuyama (am), yoshinobu tsukada \\
12 & 13 & 2013-06-30 00:00:00 & gateway to the open mizuno open & -19 (67-66-68-68=269) & 3 strokes & kim kyung-tae \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "date" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( date ) where date = '11 nov 2007' <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>winning score</th>
<th>margin of victory</th>
<th>runner(s)-up</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2002-11-03 00:00:00</td>
<td>philip morris k.k. championship</td>
<td>-19 (65-67-67-70=269)</td>
<td>2 strokes</td>
<td>toshimitsu izawa</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2003-08-10 00:00:00</td>
<td>sun chlorella classic</td>
<td>-8 (71-73-68-68=280)</td>
<td>1 stroke</td>
<td>daisuke maruyama, taichi teshima</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2004-04-25 00:00:00</td>
<td>tsuruya open</td>
<td>-9 (64-73-69-69=275)</td>
<td>2 strokes</td>
<td>keiichiro fukabori, scott laycock, tatsuya mitsuhashi, taichi teshima, shinichi yokota</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2004-06-26 00:00:00</td>
<td>gateway to the open mizuno open</td>
<td>-14 (67-68-70-69=274)</td>
<td>playoff</td>
<td>hiroaki iijima</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2006-04-23 00:00:00</td>
<td>tsuruya open</td>
<td>-11 (70-68-66-69=273)</td>
<td>2 strokes</td>
<td>mamo osanai</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2007-04-22 00:00:00</td>
<td>tsuruya open</td>
<td>-16 (67-65-68-68=268)</td>
<td>2 strokes</td>
<td>masahiro kuramoto, hirofumi miyase, takuya taniguchi</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2007-11-11 00:00:00</td>
<td>mitsui sumitomo visa taiheiyo masters</td>
<td>-13 (67-68-69-70=274)</td>
<td>5 strokes</td>
<td>toru taniguchi</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2007-12-02 00:00:00</td>
<td>golf nippon series jt cup</td>
<td>-11 (70-70-68-61=261)</td>
<td>1 stroke</td>
<td>toru taniguchi</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2010-09-26 00:00:00</td>
<td>asia-pacific panasonic open (co-sanctioned by the asian tour)</td>
<td>-6 (71-70-66=207)</td>
<td>1 stroke</td>
<td>ryuichi oda</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2011-05-01 00:00:00</td>
<td>the crowns</td>
<td>-9 (67-66-68-70=271)</td>
<td>playoff</td>
<td>jang ik-jae</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>2012-04-15 00:00:00</td>
<td>token homemate cup</td>
<td>-15 (68-69-70-62=269)</td>
<td>2 strokes</td>
<td>ryuichi oda</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>2012-07-29 00:00:00</td>
<td>sun chlorella classic</td>
<td>-15 (69-66-68-70=273)</td>
<td>2 strokes</td>
<td>lee seong-ho, hideki matsuyama (am), yoshinobu tsukada</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>2013-06-30 00:00:00</td>
<td>gateway to the open mizuno open</td>
<td>-19 (67-66-68-68=269)</td>
<td>3 strokes</td>
<td>kim kyung-tae</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>1</td>
</tr>
</tbody>
</table> | select count ( date ) where date = '11 nov 2007' <table_name> : table | | no. | date | tournament | winning score | margin of victory | runner(s)-up |
|---:|------:|:--------------------|:--------------------------------------------------------------|:----------------------|:--------------------|:---------------------------------------------------------------------------------------|
| 0 | 1 | 2002-11-03 00:00:00 | philip morris k.k. championship | -19 (65-67-67-70=269) | 2 strokes | toshimitsu izawa |
| 1 | 2 | 2003-08-10 00:00:00 | sun chlorella classic | -8 (71-73-68-68=280) | 1 stroke | daisuke maruyama, taichi teshima |
| 2 | 3 | 2004-04-25 00:00:00 | tsuruya open | -9 (64-73-69-69=275) | 2 strokes | keiichiro fukabori, scott laycock, tatsuya mitsuhashi, taichi teshima, shinichi yokota |
| 3 | 4 | 2004-06-26 00:00:00 | gateway to the open mizuno open | -14 (67-68-70-69=274) | playoff | hiroaki iijima |
| 4 | 5 | 2006-04-23 00:00:00 | tsuruya open | -11 (70-68-66-69=273) | 2 strokes | mamo osanai |
| 5 | 6 | 2007-04-22 00:00:00 | tsuruya open | -16 (67-65-68-68=268) | 2 strokes | masahiro kuramoto, hirofumi miyase, takuya taniguchi |
| 6 | 7 | 2007-11-11 00:00:00 | mitsui sumitomo visa taiheiyo masters | -13 (67-68-69-70=274) | 5 strokes | toru taniguchi |
| 7 | 8 | 2007-12-02 00:00:00 | golf nippon series jt cup | -11 (70-70-68-61=261) | 1 stroke | toru taniguchi |
| 8 | 9 | 2010-09-26 00:00:00 | asia-pacific panasonic open (co-sanctioned by the asian tour) | -6 (71-70-66=207) | 1 stroke | ryuichi oda |
| 9 | 10 | 2011-05-01 00:00:00 | the crowns | -9 (67-66-68-70=271) | playoff | jang ik-jae |
| 10 | 11 | 2012-04-15 00:00:00 | token homemate cup | -15 (68-69-70-62=269) | 2 strokes | ryuichi oda |
| 11 | 12 | 2012-07-29 00:00:00 | sun chlorella classic | -15 (69-66-68-70=273) | 2 strokes | lee seong-ho, hideki matsuyama (am), yoshinobu tsukada |
| 12 | 13 | 2013-06-30 00:00:00 | gateway to the open mizuno open | -19 (67-66-68-68=269) | 3 strokes | kim kyung-tae | | | | count ( "date" ) |
|---:|-------------------:|
| 0 | 1 | | [
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] |
select count ( ground ) where opponent = 'sg wattenscheid 09' col : match | date | ground | opponent | score1 | pos. | pts. | gd row 1 : 1 | 15 august | a | bayer uerdingen | 3 - 0 | 1 | 2 | 3 row 2 : 2 | 22 august | h | 1. fc kaiserslautern | 1 - 0 | 1 | 4 | 4 row 3 : 4 | 29 august | h | dynamo dresden | 3 - 1 | 1 | 6 | 6 row 4 : 5 | 2 september | a | 1. fc koln | 3 - 1 | 1 | 8 | 8 row 5 : 6 | 5 september | h | hamburger sv | 4 - 0 | 1 | 10 | 12 row 6 : 7 | 19 september | h | sg wattenscheid 09 | 1 - 1 | 1 | 11 | 12 row 7 : 8 | 25 september | a | borussia dortmund | 2 - 1 | 1 | 13 | 13 row 8 : 9 | 3 october | h | borussia monchengladbach | 2 - 2 | 1 | 14 | 13 row 9 : 10 | 17 october | a | 1. fc saarbrucken | 1 - 1 | 1 | 15 | 13 row 10 : 11 | 24 october | h | werder bremen | 1 - 3 | 1 | 15 | 11 row 11 : 3 | 27 october | a | eintracht frankfurt | 1 - 1 | 1 | 16 | 11 row 12 : 12 | 31 october | a | vfb stuttgart | 3 - 2 | 1 | 18 | 12 row 13 : 13 | 14 november | h | 1. fc nurnberg | 1 - 0 | 1 | 20 | 13 row 14 : 14 | 21 november | a | bayer leverkusen | 4 - 2 | 1 | 22 | 15 row 15 : 15 | 28 november | h | karlsruher sc | 3 - 3 | 1 | 23 | 15 row 16 : 16 | 5 december | a | vfl bochum | 2 - 2 | 1 | 24 | 15 row 17 : 17 | 12 december | h | schalke 04 | 1 - 1 | 1 | 25 | 15 row 18 : 18 | 20 february | h | bayer uerdingen | 2 - 0 | 1 | 27 | 17 row 19 : 19 | 27 february | a | 1. fc kaiserslautern | 3 - 1 | 1 | 29 | 19 row 20 : 20 | 6 march | h | eintracht frankfurt | 1 - 0 | 1 | 31 | 20 row 21 : 21 | 13 march | a | dynamo dresden | 0 - 0 | 1 | 32 | 20 row 22 : 22 | 20 march | h | 1. fc koln | 3 - 0 | 1 | 34 | 23 row 23 : 23 | 28 march | a | hamburger sv | 1 - 3 | 1 | 34 | 21 row 24 : 24 | 2 april | a | sg wattenscheid 09 | 0 - 2 | 1 | 34 | 19 row 25 : 25 | 10 april | h | borussia dortmund | 2 - 0 | 1 | 36 | 21 row 26 : 26 | 17 april | a | borussia monchengladbach | 2 - 2 | 1 | 37 | 21 row 27 : 27 | 23 april | h | 1. fc saarbrucken | 6 - 0 | 1 | 39 | 27 row 28 : 28 | 26 april | a | werder bremen | 1 - 4 | 1 | 39 | 24 row 29 : 29 | 30 april | h | vfb stuttgart | 5 - 3 | 1 | 41 | 26 row 30 : 30 | 8 may | a | 1. fc nurnberg | 0 - 0 | 1 | 42 | 26 row 31 : 31 | 15 may | h | bayer leverkusen | 4 - 1 | 1 | 44 | 29 row 32 : 32 | 23 may | a | karlsruher sc | 2 - 4 | 1 | 44 | 27 row 33 : 33 | 29 may | h | vfl bochum | 3 - 1 | 2 | 46 | 29 row 34 : 34 | 5 june | a | schalke 04 | 3 - 3 | 2 | 47 | 29 | col : count ( "ground" ) row 1 : 2 | select count ( ground ) where opponent = 'sg wattenscheid 09' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& match & date & ground & opponent & score1 & pos. & pts. & gd \\
\midrule
0 & 1 & 15 august & a & bayer uerdingen & 3 - 0 & 1 & 2 & 3 \\
1 & 2 & 22 august & h & 1. fc kaiserslautern & 1 - 0 & 1 & 4 & 4 \\
2 & 4 & 29 august & h & dynamo dresden & 3 - 1 & 1 & 6 & 6 \\
3 & 5 & 2 september & a & 1. fc koln & 3 - 1 & 1 & 8 & 8 \\
4 & 6 & 5 september & h & hamburger sv & 4 - 0 & 1 & 10 & 12 \\
5 & 7 & 19 september & h & sg wattenscheid 09 & 1 - 1 & 1 & 11 & 12 \\
6 & 8 & 25 september & a & borussia dortmund & 2 - 1 & 1 & 13 & 13 \\
7 & 9 & 3 october & h & borussia monchengladbach & 2 - 2 & 1 & 14 & 13 \\
8 & 10 & 17 october & a & 1. fc saarbrucken & 1 - 1 & 1 & 15 & 13 \\
9 & 11 & 24 october & h & werder bremen & 1 - 3 & 1 & 15 & 11 \\
10 & 3 & 27 october & a & eintracht frankfurt & 1 - 1 & 1 & 16 & 11 \\
11 & 12 & 31 october & a & vfb stuttgart & 3 - 2 & 1 & 18 & 12 \\
12 & 13 & 14 november & h & 1. fc nurnberg & 1 - 0 & 1 & 20 & 13 \\
13 & 14 & 21 november & a & bayer leverkusen & 4 - 2 & 1 & 22 & 15 \\
14 & 15 & 28 november & h & karlsruher sc & 3 - 3 & 1 & 23 & 15 \\
15 & 16 & 5 december & a & vfl bochum & 2 - 2 & 1 & 24 & 15 \\
16 & 17 & 12 december & h & schalke 04 & 1 - 1 & 1 & 25 & 15 \\
17 & 18 & 20 february & h & bayer uerdingen & 2 - 0 & 1 & 27 & 17 \\
18 & 19 & 27 february & a & 1. fc kaiserslautern & 3 - 1 & 1 & 29 & 19 \\
19 & 20 & 6 march & h & eintracht frankfurt & 1 - 0 & 1 & 31 & 20 \\
20 & 21 & 13 march & a & dynamo dresden & 0 - 0 & 1 & 32 & 20 \\
21 & 22 & 20 march & h & 1. fc koln & 3 - 0 & 1 & 34 & 23 \\
22 & 23 & 28 march & a & hamburger sv & 1 - 3 & 1 & 34 & 21 \\
23 & 24 & 2 april & a & sg wattenscheid 09 & 0 - 2 & 1 & 34 & 19 \\
24 & 25 & 10 april & h & borussia dortmund & 2 - 0 & 1 & 36 & 21 \\
25 & 26 & 17 april & a & borussia monchengladbach & 2 - 2 & 1 & 37 & 21 \\
26 & 27 & 23 april & h & 1. fc saarbrucken & 6 - 0 & 1 & 39 & 27 \\
27 & 28 & 26 april & a & werder bremen & 1 - 4 & 1 & 39 & 24 \\
28 & 29 & 30 april & h & vfb stuttgart & 5 - 3 & 1 & 41 & 26 \\
29 & 30 & 8 may & a & 1. fc nurnberg & 0 - 0 & 1 & 42 & 26 \\
30 & 31 & 15 may & h & bayer leverkusen & 4 - 1 & 1 & 44 & 29 \\
31 & 32 & 23 may & a & karlsruher sc & 2 - 4 & 1 & 44 & 27 \\
32 & 33 & 29 may & h & vfl bochum & 3 - 1 & 2 & 46 & 29 \\
33 & 34 & 5 june & a & schalke 04 & 3 - 3 & 2 & 47 & 29 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "ground" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( ground ) where opponent = 'sg wattenscheid 09' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>match</th>
<th>date</th>
<th>ground</th>
<th>opponent</th>
<th>score1</th>
<th>pos.</th>
<th>pts.</th>
<th>gd</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>15 august</td>
<td>a</td>
<td>bayer uerdingen</td>
<td>3 - 0</td>
<td>1</td>
<td>2</td>
<td>3</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>22 august</td>
<td>h</td>
<td>1. fc kaiserslautern</td>
<td>1 - 0</td>
<td>1</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>2</th>
<td>4</td>
<td>29 august</td>
<td>h</td>
<td>dynamo dresden</td>
<td>3 - 1</td>
<td>1</td>
<td>6</td>
<td>6</td>
</tr>
<tr>
<th>3</th>
<td>5</td>
<td>2 september</td>
<td>a</td>
<td>1. fc koln</td>
<td>3 - 1</td>
<td>1</td>
<td>8</td>
<td>8</td>
</tr>
<tr>
<th>4</th>
<td>6</td>
<td>5 september</td>
<td>h</td>
<td>hamburger sv</td>
<td>4 - 0</td>
<td>1</td>
<td>10</td>
<td>12</td>
</tr>
<tr>
<th>5</th>
<td>7</td>
<td>19 september</td>
<td>h</td>
<td>sg wattenscheid 09</td>
<td>1 - 1</td>
<td>1</td>
<td>11</td>
<td>12</td>
</tr>
<tr>
<th>6</th>
<td>8</td>
<td>25 september</td>
<td>a</td>
<td>borussia dortmund</td>
<td>2 - 1</td>
<td>1</td>
<td>13</td>
<td>13</td>
</tr>
<tr>
<th>7</th>
<td>9</td>
<td>3 october</td>
<td>h</td>
<td>borussia monchengladbach</td>
<td>2 - 2</td>
<td>1</td>
<td>14</td>
<td>13</td>
</tr>
<tr>
<th>8</th>
<td>10</td>
<td>17 october</td>
<td>a</td>
<td>1. fc saarbrucken</td>
<td>1 - 1</td>
<td>1</td>
<td>15</td>
<td>13</td>
</tr>
<tr>
<th>9</th>
<td>11</td>
<td>24 october</td>
<td>h</td>
<td>werder bremen</td>
<td>1 - 3</td>
<td>1</td>
<td>15</td>
<td>11</td>
</tr>
<tr>
<th>10</th>
<td>3</td>
<td>27 october</td>
<td>a</td>
<td>eintracht frankfurt</td>
<td>1 - 1</td>
<td>1</td>
<td>16</td>
<td>11</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>31 october</td>
<td>a</td>
<td>vfb stuttgart</td>
<td>3 - 2</td>
<td>1</td>
<td>18</td>
<td>12</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>14 november</td>
<td>h</td>
<td>1. fc nurnberg</td>
<td>1 - 0</td>
<td>1</td>
<td>20</td>
<td>13</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>21 november</td>
<td>a</td>
<td>bayer leverkusen</td>
<td>4 - 2</td>
<td>1</td>
<td>22</td>
<td>15</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>28 november</td>
<td>h</td>
<td>karlsruher sc</td>
<td>3 - 3</td>
<td>1</td>
<td>23</td>
<td>15</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>5 december</td>
<td>a</td>
<td>vfl bochum</td>
<td>2 - 2</td>
<td>1</td>
<td>24</td>
<td>15</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>12 december</td>
<td>h</td>
<td>schalke 04</td>
<td>1 - 1</td>
<td>1</td>
<td>25</td>
<td>15</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>20 february</td>
<td>h</td>
<td>bayer uerdingen</td>
<td>2 - 0</td>
<td>1</td>
<td>27</td>
<td>17</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>27 february</td>
<td>a</td>
<td>1. fc kaiserslautern</td>
<td>3 - 1</td>
<td>1</td>
<td>29</td>
<td>19</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>6 march</td>
<td>h</td>
<td>eintracht frankfurt</td>
<td>1 - 0</td>
<td>1</td>
<td>31</td>
<td>20</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>13 march</td>
<td>a</td>
<td>dynamo dresden</td>
<td>0 - 0</td>
<td>1</td>
<td>32</td>
<td>20</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>20 march</td>
<td>h</td>
<td>1. fc koln</td>
<td>3 - 0</td>
<td>1</td>
<td>34</td>
<td>23</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>28 march</td>
<td>a</td>
<td>hamburger sv</td>
<td>1 - 3</td>
<td>1</td>
<td>34</td>
<td>21</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>2 april</td>
<td>a</td>
<td>sg wattenscheid 09</td>
<td>0 - 2</td>
<td>1</td>
<td>34</td>
<td>19</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>10 april</td>
<td>h</td>
<td>borussia dortmund</td>
<td>2 - 0</td>
<td>1</td>
<td>36</td>
<td>21</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>17 april</td>
<td>a</td>
<td>borussia monchengladbach</td>
<td>2 - 2</td>
<td>1</td>
<td>37</td>
<td>21</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>23 april</td>
<td>h</td>
<td>1. fc saarbrucken</td>
<td>6 - 0</td>
<td>1</td>
<td>39</td>
<td>27</td>
</tr>
<tr>
<th>27</th>
<td>28</td>
<td>26 april</td>
<td>a</td>
<td>werder bremen</td>
<td>1 - 4</td>
<td>1</td>
<td>39</td>
<td>24</td>
</tr>
<tr>
<th>28</th>
<td>29</td>
<td>30 april</td>
<td>h</td>
<td>vfb stuttgart</td>
<td>5 - 3</td>
<td>1</td>
<td>41</td>
<td>26</td>
</tr>
<tr>
<th>29</th>
<td>30</td>
<td>8 may</td>
<td>a</td>
<td>1. fc nurnberg</td>
<td>0 - 0</td>
<td>1</td>
<td>42</td>
<td>26</td>
</tr>
<tr>
<th>30</th>
<td>31</td>
<td>15 may</td>
<td>h</td>
<td>bayer leverkusen</td>
<td>4 - 1</td>
<td>1</td>
<td>44</td>
<td>29</td>
</tr>
<tr>
<th>31</th>
<td>32</td>
<td>23 may</td>
<td>a</td>
<td>karlsruher sc</td>
<td>2 - 4</td>
<td>1</td>
<td>44</td>
<td>27</td>
</tr>
<tr>
<th>32</th>
<td>33</td>
<td>29 may</td>
<td>h</td>
<td>vfl bochum</td>
<td>3 - 1</td>
<td>2</td>
<td>46</td>
<td>29</td>
</tr>
<tr>
<th>33</th>
<td>34</td>
<td>5 june</td>
<td>a</td>
<td>schalke 04</td>
<td>3 - 3</td>
<td>2</td>
<td>47</td>
<td>29</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "ground" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( ground ) where opponent = 'sg wattenscheid 09' <table_name> : table | | match | date | ground | opponent | score1 | pos. | pts. | gd |
|---:|--------:|:-------------|:---------|:-------------------------|:---------|-------:|-------:|-----:|
| 0 | 1 | 15 august | a | bayer uerdingen | 3 - 0 | 1 | 2 | 3 |
| 1 | 2 | 22 august | h | 1. fc kaiserslautern | 1 - 0 | 1 | 4 | 4 |
| 2 | 4 | 29 august | h | dynamo dresden | 3 - 1 | 1 | 6 | 6 |
| 3 | 5 | 2 september | a | 1. fc koln | 3 - 1 | 1 | 8 | 8 |
| 4 | 6 | 5 september | h | hamburger sv | 4 - 0 | 1 | 10 | 12 |
| 5 | 7 | 19 september | h | sg wattenscheid 09 | 1 - 1 | 1 | 11 | 12 |
| 6 | 8 | 25 september | a | borussia dortmund | 2 - 1 | 1 | 13 | 13 |
| 7 | 9 | 3 october | h | borussia monchengladbach | 2 - 2 | 1 | 14 | 13 |
| 8 | 10 | 17 october | a | 1. fc saarbrucken | 1 - 1 | 1 | 15 | 13 |
| 9 | 11 | 24 october | h | werder bremen | 1 - 3 | 1 | 15 | 11 |
| 10 | 3 | 27 october | a | eintracht frankfurt | 1 - 1 | 1 | 16 | 11 |
| 11 | 12 | 31 october | a | vfb stuttgart | 3 - 2 | 1 | 18 | 12 |
| 12 | 13 | 14 november | h | 1. fc nurnberg | 1 - 0 | 1 | 20 | 13 |
| 13 | 14 | 21 november | a | bayer leverkusen | 4 - 2 | 1 | 22 | 15 |
| 14 | 15 | 28 november | h | karlsruher sc | 3 - 3 | 1 | 23 | 15 |
| 15 | 16 | 5 december | a | vfl bochum | 2 - 2 | 1 | 24 | 15 |
| 16 | 17 | 12 december | h | schalke 04 | 1 - 1 | 1 | 25 | 15 |
| 17 | 18 | 20 february | h | bayer uerdingen | 2 - 0 | 1 | 27 | 17 |
| 18 | 19 | 27 february | a | 1. fc kaiserslautern | 3 - 1 | 1 | 29 | 19 |
| 19 | 20 | 6 march | h | eintracht frankfurt | 1 - 0 | 1 | 31 | 20 |
| 20 | 21 | 13 march | a | dynamo dresden | 0 - 0 | 1 | 32 | 20 |
| 21 | 22 | 20 march | h | 1. fc koln | 3 - 0 | 1 | 34 | 23 |
| 22 | 23 | 28 march | a | hamburger sv | 1 - 3 | 1 | 34 | 21 |
| 23 | 24 | 2 april | a | sg wattenscheid 09 | 0 - 2 | 1 | 34 | 19 |
| 24 | 25 | 10 april | h | borussia dortmund | 2 - 0 | 1 | 36 | 21 |
| 25 | 26 | 17 april | a | borussia monchengladbach | 2 - 2 | 1 | 37 | 21 |
| 26 | 27 | 23 april | h | 1. fc saarbrucken | 6 - 0 | 1 | 39 | 27 |
| 27 | 28 | 26 april | a | werder bremen | 1 - 4 | 1 | 39 | 24 |
| 28 | 29 | 30 april | h | vfb stuttgart | 5 - 3 | 1 | 41 | 26 |
| 29 | 30 | 8 may | a | 1. fc nurnberg | 0 - 0 | 1 | 42 | 26 |
| 30 | 31 | 15 may | h | bayer leverkusen | 4 - 1 | 1 | 44 | 29 |
| 31 | 32 | 23 may | a | karlsruher sc | 2 - 4 | 1 | 44 | 27 |
| 32 | 33 | 29 may | h | vfl bochum | 3 - 1 | 2 | 46 | 29 |
| 33 | 34 | 5 june | a | schalke 04 | 3 - 3 | 2 | 47 | 29 | | | | count ( "ground" ) |
|---:|---------------------:|
| 0 | 2 | | [
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select agg where score = '1-4' col : home team | score | away team | date | agg row 1 : aberdeen | 7-1 | hamilton academical | 1978-11-10 00:00:00 | 8-1 row 2 : airdrieonians | 1-2 | arbroath | 1978-10-10 00:00:00 | 2-3 row 3 : ayr united | 1-1 | falkirk | 1978-11-10 00:00:00 | 3-1 row 4 : clydebank | 1-1 | hibernian | 1978-11-10 00:00:00 | 1-2 row 5 : morton | 5-2 | kilmarnock | 1978-11-10 00:00:00 | 5-4 row 6 : montrose | 5-1 | raith rovers | 1978-11-10 00:00:00 | 5-4 row 7 : motherwell | 1-4 | celtic | 1978-11-10 00:00:00 | 2-4 row 8 : st. mirren | 0-0 | rangers | 1978-11-10 00:00:00 | 2-3 | col : agg row 1 : 2-4 | select agg where score = '1-4' <table_name> : table \begin{tabular}{llllll}
\toprule
& home team & score & away team & date & agg \\
\midrule
0 & aberdeen & 7-1 & hamilton academical & 1978-11-10 00:00:00 & 8-1 \\
1 & airdrieonians & 1-2 & arbroath & 1978-10-10 00:00:00 & 2-3 \\
2 & ayr united & 1-1 & falkirk & 1978-11-10 00:00:00 & 3-1 \\
3 & clydebank & 1-1 & hibernian & 1978-11-10 00:00:00 & 1-2 \\
4 & morton & 5-2 & kilmarnock & 1978-11-10 00:00:00 & 5-4 \\
5 & montrose & 5-1 & raith rovers & 1978-11-10 00:00:00 & 5-4 \\
6 & motherwell & 1-4 & celtic & 1978-11-10 00:00:00 & 2-4 \\
7 & st. mirren & 0-0 & rangers & 1978-11-10 00:00:00 & 2-3 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& agg \\
\midrule
0 & 2-4 \\
\bottomrule
\end{tabular}
| select agg where score = '1-4' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>home team</th>
<th>score</th>
<th>away team</th>
<th>date</th>
<th>agg</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>aberdeen</td>
<td>7-1</td>
<td>hamilton academical</td>
<td>1978-11-10 00:00:00</td>
<td>8-1</td>
</tr>
<tr>
<th>1</th>
<td>airdrieonians</td>
<td>1-2</td>
<td>arbroath</td>
<td>1978-10-10 00:00:00</td>
<td>2-3</td>
</tr>
<tr>
<th>2</th>
<td>ayr united</td>
<td>1-1</td>
<td>falkirk</td>
<td>1978-11-10 00:00:00</td>
<td>3-1</td>
</tr>
<tr>
<th>3</th>
<td>clydebank</td>
<td>1-1</td>
<td>hibernian</td>
<td>1978-11-10 00:00:00</td>
<td>1-2</td>
</tr>
<tr>
<th>4</th>
<td>morton</td>
<td>5-2</td>
<td>kilmarnock</td>
<td>1978-11-10 00:00:00</td>
<td>5-4</td>
</tr>
<tr>
<th>5</th>
<td>montrose</td>
<td>5-1</td>
<td>raith rovers</td>
<td>1978-11-10 00:00:00</td>
<td>5-4</td>
</tr>
<tr>
<th>6</th>
<td>motherwell</td>
<td>1-4</td>
<td>celtic</td>
<td>1978-11-10 00:00:00</td>
<td>2-4</td>
</tr>
<tr>
<th>7</th>
<td>st. mirren</td>
<td>0-0</td>
<td>rangers</td>
<td>1978-11-10 00:00:00</td>
<td>2-3</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>2-4</td>
</tr>
</tbody>
</table> | select agg where score = '1-4' <table_name> : table | | home team | score | away team | date | agg |
|---:|:--------------|:--------|:--------------------|:--------------------|:------|
| 0 | aberdeen | 7-1 | hamilton academical | 1978-11-10 00:00:00 | 8-1 |
| 1 | airdrieonians | 1-2 | arbroath | 1978-10-10 00:00:00 | 2-3 |
| 2 | ayr united | 1-1 | falkirk | 1978-11-10 00:00:00 | 3-1 |
| 3 | clydebank | 1-1 | hibernian | 1978-11-10 00:00:00 | 1-2 |
| 4 | morton | 5-2 | kilmarnock | 1978-11-10 00:00:00 | 5-4 |
| 5 | montrose | 5-1 | raith rovers | 1978-11-10 00:00:00 | 5-4 |
| 6 | motherwell | 1-4 | celtic | 1978-11-10 00:00:00 | 2-4 |
| 7 | st. mirren | 0-0 | rangers | 1978-11-10 00:00:00 | 2-3 | | | | agg |
|---:|:------|
| 0 | 2-4 | | [
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] |
select candidate where ∆% = '-0.07' col : party | candidate | votes | % | ∆% row 1 : conservative | joe daniel | 14422 | 36.78 | 5.78 row 2 : liberal | yasmin ratansi | 13552 | 34.56 | -13.51 row 3 : new democratic | mary trapani hynes | 9878 | 25.19 | 11.87 row 4 : green | akil sadikali | 1114 | 2.84 | -4.05 row 5 : christian heritage | ryan kidd | 246 | 0.63 | -0.07 row 6 : total valid votes | total valid votes | 39212 | 100 | none row 7 : total rejected ballots | total rejected ballots | 218 | 0.55 | none row 8 : turnout | turnout | 39430 | 57.24 | none row 9 : eligible voters | eligible voters | 68890 | none | none | col : candidate row 1 : ryan kidd | select candidate where ∆% = '-0.07' <table_name> : table \begin{tabular}{llllll}
\toprule
& party & candidate & votes & % & ∆% \\
\midrule
0 & conservative & joe daniel & 14422 & 36.78 & 5.78 \\
1 & liberal & yasmin ratansi & 13552 & 34.56 & -13.51 \\
2 & new democratic & mary trapani hynes & 9878 & 25.19 & 11.87 \\
3 & green & akil sadikali & 1114 & 2.84 & -4.05 \\
4 & christian heritage & ryan kidd & 246 & 0.63 & -0.07 \\
5 & total valid votes & total valid votes & 39212 & 100 & none \\
6 & total rejected ballots & total rejected ballots & 218 & 0.55 & none \\
7 & turnout & turnout & 39430 & 57.24 & none \\
8 & eligible voters & eligible voters & 68890 & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& candidate \\
\midrule
0 & ryan kidd \\
\bottomrule
\end{tabular}
| select candidate where ∆% = '-0.07' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
<th>candidate</th>
<th>votes</th>
<th>%</th>
<th>∆%</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>conservative</td>
<td>joe daniel</td>
<td>14422</td>
<td>36.78</td>
<td>5.78</td>
</tr>
<tr>
<th>1</th>
<td>liberal</td>
<td>yasmin ratansi</td>
<td>13552</td>
<td>34.56</td>
<td>-13.51</td>
</tr>
<tr>
<th>2</th>
<td>new democratic</td>
<td>mary trapani hynes</td>
<td>9878</td>
<td>25.19</td>
<td>11.87</td>
</tr>
<tr>
<th>3</th>
<td>green</td>
<td>akil sadikali</td>
<td>1114</td>
<td>2.84</td>
<td>-4.05</td>
</tr>
<tr>
<th>4</th>
<td>christian heritage</td>
<td>ryan kidd</td>
<td>246</td>
<td>0.63</td>
<td>-0.07</td>
</tr>
<tr>
<th>5</th>
<td>total valid votes</td>
<td>total valid votes</td>
<td>39212</td>
<td>100</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>total rejected ballots</td>
<td>total rejected ballots</td>
<td>218</td>
<td>0.55</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>turnout</td>
<td>turnout</td>
<td>39430</td>
<td>57.24</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>eligible voters</td>
<td>eligible voters</td>
<td>68890</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>candidate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>ryan kidd</td>
</tr>
</tbody>
</table> | select candidate where ∆% = '-0.07' <table_name> : table | | party | candidate | votes | % | ∆% |
|---:|:-----------------------|:-----------------------|--------:|:------|:-------|
| 0 | conservative | joe daniel | 14422 | 36.78 | 5.78 |
| 1 | liberal | yasmin ratansi | 13552 | 34.56 | -13.51 |
| 2 | new democratic | mary trapani hynes | 9878 | 25.19 | 11.87 |
| 3 | green | akil sadikali | 1114 | 2.84 | -4.05 |
| 4 | christian heritage | ryan kidd | 246 | 0.63 | -0.07 |
| 5 | total valid votes | total valid votes | 39212 | 100 | none |
| 6 | total rejected ballots | total rejected ballots | 218 | 0.55 | none |
| 7 | turnout | turnout | 39430 | 57.24 | none |
| 8 | eligible voters | eligible voters | 68890 | none | none | | | | candidate |
|---:|:------------|
| 0 | ryan kidd | | [
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select count ( round ) where attendance = attendance col : date | round | opponents | h / a | result f-a | scorers | attendance row 1 : 1984-09-19 00:00:00 | round 1 first leg | raba eto gyor | h | 3-0 | robson, muhren, hughes | 33119 row 2 : 1984-10-03 00:00:00 | round 1 second leg | raba eto gyor | a | 2-2 | brazil, muhren (pen) | 26000 row 3 : 1984-10-24 00:00:00 | round 2 first leg | psv eindhoven | a | 0-0 | none | 27500 row 4 : 1984-11-07 00:00:00 | round 2 second leg | psv eindhoven | h | 1-0 | strachan (pen) | 39281 row 5 : 1984-11-28 00:00:00 | round 3 first leg | dundee united | h | 2-2 | strachan (pen), robson | 48278 row 6 : 1984-12-12 00:00:00 | round 3 second leg | dundee united | a | 3-2 | hughes, mcginnis (og), muhren | 21821 row 7 : 1985-03-06 00:00:00 | quarter-final first leg | videoton | h | 1-0 | stapleton | 35432 row 8 : 1985-03-20 00:00:00 | quarter-final second leg | videoton | a | 0-1 (4-5 p) | none | 25000 | col : count ( "round" ) row 1 : 8 | select count ( round ) where attendance = attendance <table_name> : table \begin{tabular}{llllllll}
\toprule
& date & round & opponents & h / a & result f-a & scorers & attendance \\
\midrule
0 & 1984-09-19 00:00:00 & round 1 first leg & raba eto gyor & h & 3-0 & robson, muhren, hughes & 33119 \\
1 & 1984-10-03 00:00:00 & round 1 second leg & raba eto gyor & a & 2-2 & brazil, muhren (pen) & 26000 \\
2 & 1984-10-24 00:00:00 & round 2 first leg & psv eindhoven & a & 0-0 & none & 27500 \\
3 & 1984-11-07 00:00:00 & round 2 second leg & psv eindhoven & h & 1-0 & strachan (pen) & 39281 \\
4 & 1984-11-28 00:00:00 & round 3 first leg & dundee united & h & 2-2 & strachan (pen), robson & 48278 \\
5 & 1984-12-12 00:00:00 & round 3 second leg & dundee united & a & 3-2 & hughes, mcginnis (og), muhren & 21821 \\
6 & 1985-03-06 00:00:00 & quarter-final first leg & videoton & h & 1-0 & stapleton & 35432 \\
7 & 1985-03-20 00:00:00 & quarter-final second leg & videoton & a & 0-1 (4-5 p) & none & 25000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "round" ) \\
\midrule
0 & 8 \\
\bottomrule
\end{tabular}
| select count ( round ) where attendance = attendance <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>round</th>
<th>opponents</th>
<th>h / a</th>
<th>result f-a</th>
<th>scorers</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1984-09-19 00:00:00</td>
<td>round 1 first leg</td>
<td>raba eto gyor</td>
<td>h</td>
<td>3-0</td>
<td>robson, muhren, hughes</td>
<td>33119</td>
</tr>
<tr>
<th>1</th>
<td>1984-10-03 00:00:00</td>
<td>round 1 second leg</td>
<td>raba eto gyor</td>
<td>a</td>
<td>2-2</td>
<td>brazil, muhren (pen)</td>
<td>26000</td>
</tr>
<tr>
<th>2</th>
<td>1984-10-24 00:00:00</td>
<td>round 2 first leg</td>
<td>psv eindhoven</td>
<td>a</td>
<td>0-0</td>
<td>none</td>
<td>27500</td>
</tr>
<tr>
<th>3</th>
<td>1984-11-07 00:00:00</td>
<td>round 2 second leg</td>
<td>psv eindhoven</td>
<td>h</td>
<td>1-0</td>
<td>strachan (pen)</td>
<td>39281</td>
</tr>
<tr>
<th>4</th>
<td>1984-11-28 00:00:00</td>
<td>round 3 first leg</td>
<td>dundee united</td>
<td>h</td>
<td>2-2</td>
<td>strachan (pen), robson</td>
<td>48278</td>
</tr>
<tr>
<th>5</th>
<td>1984-12-12 00:00:00</td>
<td>round 3 second leg</td>
<td>dundee united</td>
<td>a</td>
<td>3-2</td>
<td>hughes, mcginnis (og), muhren</td>
<td>21821</td>
</tr>
<tr>
<th>6</th>
<td>1985-03-06 00:00:00</td>
<td>quarter-final first leg</td>
<td>videoton</td>
<td>h</td>
<td>1-0</td>
<td>stapleton</td>
<td>35432</td>
</tr>
<tr>
<th>7</th>
<td>1985-03-20 00:00:00</td>
<td>quarter-final second leg</td>
<td>videoton</td>
<td>a</td>
<td>0-1 (4-5 p)</td>
<td>none</td>
<td>25000</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "round" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>8</td>
</tr>
</tbody>
</table> | select count ( round ) where attendance = attendance <table_name> : table | | date | round | opponents | h / a | result f-a | scorers | attendance |
|---:|:--------------------|:-------------------------|:--------------|:--------|:-------------|:------------------------------|-------------:|
| 0 | 1984-09-19 00:00:00 | round 1 first leg | raba eto gyor | h | 3-0 | robson, muhren, hughes | 33119 |
| 1 | 1984-10-03 00:00:00 | round 1 second leg | raba eto gyor | a | 2-2 | brazil, muhren (pen) | 26000 |
| 2 | 1984-10-24 00:00:00 | round 2 first leg | psv eindhoven | a | 0-0 | none | 27500 |
| 3 | 1984-11-07 00:00:00 | round 2 second leg | psv eindhoven | h | 1-0 | strachan (pen) | 39281 |
| 4 | 1984-11-28 00:00:00 | round 3 first leg | dundee united | h | 2-2 | strachan (pen), robson | 48278 |
| 5 | 1984-12-12 00:00:00 | round 3 second leg | dundee united | a | 3-2 | hughes, mcginnis (og), muhren | 21821 |
| 6 | 1985-03-06 00:00:00 | quarter-final first leg | videoton | h | 1-0 | stapleton | 35432 |
| 7 | 1985-03-20 00:00:00 | quarter-final second leg | videoton | a | 0-1 (4-5 p) | none | 25000 | | | | count ( "round" ) |
|---:|--------------------:|
| 0 | 8 | | [
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select count ( * ) where club = 'grasshoppers' col : name | position | birth date/age at start of campaign | games in campaign | club row 1 : erich burgener | gk | february 15, 1951 (age 31) | 3 | servette row 2 : roger berbig | gk | november 6, 1954 (age 27) | 3 | grasshoppers row 3 : charly in-albon | df | june 23, 1957 (age 25) | 4 | grasshoppers row 4 : heinz ludi | df | october 8, 1958 (age 23) | 4 | fc zurich row 5 : beat rietmann | df | october 24, 1961 (age 20) | 2 | fc st. gallen row 6 : andy egli | df | may 8, 1958 (age 24) | 6 | grasshoppers row 7 : alain geiger | df | november 5, 1960 (age 21) | 4 | servette row 8 : marco schallibaum | df | april 6, 1962 (age 20) | 1 | grasshoppers row 9 : marcel koller | df | november 11, 1960 (age 21) | 2 (both as sub) | grasshoppers row 10 : rene botteron | mf | october 17, 1954 (age 27) | 1 | 1. fc nuremberg fc basel row 11 : heinz hermann | mf | march 28, 1958 (age 24) | 6 | grasshoppers row 12 : roger wehrli | mf | march 18, 1956 (age 26) | 6 | grasshoppers row 13 : lucien favre | mf | november 2, 1957 (age 24) | 5 (1 as sub) | toulouse servette row 14 : alfred scheiwiler | mf | february 4, 1956 (age 26) | 1 | lausanne row 15 : erni maissen | mf | january 1, 1958 (age 24) | 1 (as sub) | fc zurich fc basel row 16 : michel decastel | mf | october 22, 1955 (age 26) | 3 | servette row 17 : ruedi elsener | mf | february 18, 1953 (age 29) | 4 | none row 18 : umberto barberis | mf | june 5, 1952 (age 30) | 3 (1 as sub) | as monaco servette row 19 : andre ladner | mf | may 20, 1962 (age 20) | 1 | grasshoppers row 20 : jean-paul brigger | st | december 14, 1957 (age 24) | 2 (1 as sub) | servette row 21 : hans-peter zwicker | st | april 7, 1960 (age 22) | 2 (both as sub) | fc zurich lausanne row 22 : claudio sulser | st | october 8, 1955 (age 26) | 5 | grasshoppers row 23 : beat sutter | st | december 12, 1962 (age 19) | 2 (1 as sub) | fc basel row 24 : raimondo ponte | st | april 4, 1955 (age 27) | 4 | grasshoppers row 25 : manfred braschler | st | october 8, 1958 (age 23) | 2 | fc st. gallen | col : count ( "*" ) row 1 : 10 | select count ( * ) where club = 'grasshoppers' <table_name> : table \begin{tabular}{llllll}
\toprule
& name & position & birth date/age at start of campaign & games in campaign & club \\
\midrule
0 & erich burgener & gk & february 15, 1951 (age 31) & 3 & servette \\
1 & roger berbig & gk & november 6, 1954 (age 27) & 3 & grasshoppers \\
2 & charly in-albon & df & june 23, 1957 (age 25) & 4 & grasshoppers \\
3 & heinz ludi & df & october 8, 1958 (age 23) & 4 & fc zurich \\
4 & beat rietmann & df & october 24, 1961 (age 20) & 2 & fc st. gallen \\
5 & andy egli & df & may 8, 1958 (age 24) & 6 & grasshoppers \\
6 & alain geiger & df & november 5, 1960 (age 21) & 4 & servette \\
7 & marco schallibaum & df & april 6, 1962 (age 20) & 1 & grasshoppers \\
8 & marcel koller & df & november 11, 1960 (age 21) & 2 (both as sub) & grasshoppers \\
9 & rene botteron & mf & october 17, 1954 (age 27) & 1 & 1. fc nuremberg fc basel \\
10 & heinz hermann & mf & march 28, 1958 (age 24) & 6 & grasshoppers \\
11 & roger wehrli & mf & march 18, 1956 (age 26) & 6 & grasshoppers \\
12 & lucien favre & mf & november 2, 1957 (age 24) & 5 (1 as sub) & toulouse servette \\
13 & alfred scheiwiler & mf & february 4, 1956 (age 26) & 1 & lausanne \\
14 & erni maissen & mf & january 1, 1958 (age 24) & 1 (as sub) & fc zurich fc basel \\
15 & michel decastel & mf & october 22, 1955 (age 26) & 3 & servette \\
16 & ruedi elsener & mf & february 18, 1953 (age 29) & 4 & none \\
17 & umberto barberis & mf & june 5, 1952 (age 30) & 3 (1 as sub) & as monaco servette \\
18 & andre ladner & mf & may 20, 1962 (age 20) & 1 & grasshoppers \\
19 & jean-paul brigger & st & december 14, 1957 (age 24) & 2 (1 as sub) & servette \\
20 & hans-peter zwicker & st & april 7, 1960 (age 22) & 2 (both as sub) & fc zurich lausanne \\
21 & claudio sulser & st & october 8, 1955 (age 26) & 5 & grasshoppers \\
22 & beat sutter & st & december 12, 1962 (age 19) & 2 (1 as sub) & fc basel \\
23 & raimondo ponte & st & april 4, 1955 (age 27) & 4 & grasshoppers \\
24 & manfred braschler & st & october 8, 1958 (age 23) & 2 & fc st. gallen \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 10 \\
\bottomrule
\end{tabular}
| select count ( * ) where club = 'grasshoppers' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>position</th>
<th>birth date/age at start of campaign</th>
<th>games in campaign</th>
<th>club</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>erich burgener</td>
<td>gk</td>
<td>february 15, 1951 (age 31)</td>
<td>3</td>
<td>servette</td>
</tr>
<tr>
<th>1</th>
<td>roger berbig</td>
<td>gk</td>
<td>november 6, 1954 (age 27)</td>
<td>3</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>2</th>
<td>charly in-albon</td>
<td>df</td>
<td>june 23, 1957 (age 25)</td>
<td>4</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>3</th>
<td>heinz ludi</td>
<td>df</td>
<td>october 8, 1958 (age 23)</td>
<td>4</td>
<td>fc zurich</td>
</tr>
<tr>
<th>4</th>
<td>beat rietmann</td>
<td>df</td>
<td>october 24, 1961 (age 20)</td>
<td>2</td>
<td>fc st. gallen</td>
</tr>
<tr>
<th>5</th>
<td>andy egli</td>
<td>df</td>
<td>may 8, 1958 (age 24)</td>
<td>6</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>6</th>
<td>alain geiger</td>
<td>df</td>
<td>november 5, 1960 (age 21)</td>
<td>4</td>
<td>servette</td>
</tr>
<tr>
<th>7</th>
<td>marco schallibaum</td>
<td>df</td>
<td>april 6, 1962 (age 20)</td>
<td>1</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>8</th>
<td>marcel koller</td>
<td>df</td>
<td>november 11, 1960 (age 21)</td>
<td>2 (both as sub)</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>9</th>
<td>rene botteron</td>
<td>mf</td>
<td>october 17, 1954 (age 27)</td>
<td>1</td>
<td>1. fc nuremberg fc basel</td>
</tr>
<tr>
<th>10</th>
<td>heinz hermann</td>
<td>mf</td>
<td>march 28, 1958 (age 24)</td>
<td>6</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>11</th>
<td>roger wehrli</td>
<td>mf</td>
<td>march 18, 1956 (age 26)</td>
<td>6</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>12</th>
<td>lucien favre</td>
<td>mf</td>
<td>november 2, 1957 (age 24)</td>
<td>5 (1 as sub)</td>
<td>toulouse servette</td>
</tr>
<tr>
<th>13</th>
<td>alfred scheiwiler</td>
<td>mf</td>
<td>february 4, 1956 (age 26)</td>
<td>1</td>
<td>lausanne</td>
</tr>
<tr>
<th>14</th>
<td>erni maissen</td>
<td>mf</td>
<td>january 1, 1958 (age 24)</td>
<td>1 (as sub)</td>
<td>fc zurich fc basel</td>
</tr>
<tr>
<th>15</th>
<td>michel decastel</td>
<td>mf</td>
<td>october 22, 1955 (age 26)</td>
<td>3</td>
<td>servette</td>
</tr>
<tr>
<th>16</th>
<td>ruedi elsener</td>
<td>mf</td>
<td>february 18, 1953 (age 29)</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>umberto barberis</td>
<td>mf</td>
<td>june 5, 1952 (age 30)</td>
<td>3 (1 as sub)</td>
<td>as monaco servette</td>
</tr>
<tr>
<th>18</th>
<td>andre ladner</td>
<td>mf</td>
<td>may 20, 1962 (age 20)</td>
<td>1</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>19</th>
<td>jean-paul brigger</td>
<td>st</td>
<td>december 14, 1957 (age 24)</td>
<td>2 (1 as sub)</td>
<td>servette</td>
</tr>
<tr>
<th>20</th>
<td>hans-peter zwicker</td>
<td>st</td>
<td>april 7, 1960 (age 22)</td>
<td>2 (both as sub)</td>
<td>fc zurich lausanne</td>
</tr>
<tr>
<th>21</th>
<td>claudio sulser</td>
<td>st</td>
<td>october 8, 1955 (age 26)</td>
<td>5</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>22</th>
<td>beat sutter</td>
<td>st</td>
<td>december 12, 1962 (age 19)</td>
<td>2 (1 as sub)</td>
<td>fc basel</td>
</tr>
<tr>
<th>23</th>
<td>raimondo ponte</td>
<td>st</td>
<td>april 4, 1955 (age 27)</td>
<td>4</td>
<td>grasshoppers</td>
</tr>
<tr>
<th>24</th>
<td>manfred braschler</td>
<td>st</td>
<td>october 8, 1958 (age 23)</td>
<td>2</td>
<td>fc st. gallen</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>10</td>
</tr>
</tbody>
</table> | select count ( * ) where club = 'grasshoppers' <table_name> : table | | name | position | birth date/age at start of campaign | games in campaign | club |
|---:|:-------------------|:-----------|:--------------------------------------|:--------------------|:-------------------------|
| 0 | erich burgener | gk | february 15, 1951 (age 31) | 3 | servette |
| 1 | roger berbig | gk | november 6, 1954 (age 27) | 3 | grasshoppers |
| 2 | charly in-albon | df | june 23, 1957 (age 25) | 4 | grasshoppers |
| 3 | heinz ludi | df | october 8, 1958 (age 23) | 4 | fc zurich |
| 4 | beat rietmann | df | october 24, 1961 (age 20) | 2 | fc st. gallen |
| 5 | andy egli | df | may 8, 1958 (age 24) | 6 | grasshoppers |
| 6 | alain geiger | df | november 5, 1960 (age 21) | 4 | servette |
| 7 | marco schallibaum | df | april 6, 1962 (age 20) | 1 | grasshoppers |
| 8 | marcel koller | df | november 11, 1960 (age 21) | 2 (both as sub) | grasshoppers |
| 9 | rene botteron | mf | october 17, 1954 (age 27) | 1 | 1. fc nuremberg fc basel |
| 10 | heinz hermann | mf | march 28, 1958 (age 24) | 6 | grasshoppers |
| 11 | roger wehrli | mf | march 18, 1956 (age 26) | 6 | grasshoppers |
| 12 | lucien favre | mf | november 2, 1957 (age 24) | 5 (1 as sub) | toulouse servette |
| 13 | alfred scheiwiler | mf | february 4, 1956 (age 26) | 1 | lausanne |
| 14 | erni maissen | mf | january 1, 1958 (age 24) | 1 (as sub) | fc zurich fc basel |
| 15 | michel decastel | mf | october 22, 1955 (age 26) | 3 | servette |
| 16 | ruedi elsener | mf | february 18, 1953 (age 29) | 4 | none |
| 17 | umberto barberis | mf | june 5, 1952 (age 30) | 3 (1 as sub) | as monaco servette |
| 18 | andre ladner | mf | may 20, 1962 (age 20) | 1 | grasshoppers |
| 19 | jean-paul brigger | st | december 14, 1957 (age 24) | 2 (1 as sub) | servette |
| 20 | hans-peter zwicker | st | april 7, 1960 (age 22) | 2 (both as sub) | fc zurich lausanne |
| 21 | claudio sulser | st | october 8, 1955 (age 26) | 5 | grasshoppers |
| 22 | beat sutter | st | december 12, 1962 (age 19) | 2 (1 as sub) | fc basel |
| 23 | raimondo ponte | st | april 4, 1955 (age 27) | 4 | grasshoppers |
| 24 | manfred braschler | st | october 8, 1958 (age 23) | 2 | fc st. gallen | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 10 | | [
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select first worn where first worn > 2002 col : national team | title(s) represented | first worn | number of stars | notes row 1 : brazil | world cup | 1971 | 5 | third win was in 1970; fourth and fifth stars added after 1994 and 2002 wins. briefly wore 2 stars on a tour of europe in 1968 row 2 : italy | world cup | 1982 | 4 | added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006 row 3 : germany | world cup | 1996 | 3 | 1954, 1974, third win was in 1990 row 4 : uruguay | world cup and olympics | 1930 | 4 | represent 2 world cups (1930 & 1950) and 2 olympic football titles (1924 & 1928) recognized as fifa world championships row 5 : argentina | world cup | 2003 | 2 | 1978, second win was in 1986 row 6 : england | world cup | 2003 | 1 | title won in 1966. star added after a campaign on sky sports' soccer am programme, first worn on the sleeve row 7 : france | world cup | 1998 | 1 | title won in 1998. star added above their badge which was unveiled at their opening qualifying game for euro 2000 row 8 : spain | world cup | 2010 | 1 | title won in 2010. spain played in their away kit for the final, but upon winning the world cup they changed into their home kit, complete with a star above the badge, for the presentation ceremony | col : first worn row 1 : 2003 row 2 : 2003 row 3 : 2010 | select first worn where first worn > 2002 <table_name> : table \begin{tabular}{llllll}
\toprule
& national team & title(s) represented & first worn & number of stars & notes \\
\midrule
0 & brazil & world cup & 1971 & 5 & third win was in 1970; fourth and fifth stars added after 1994 and 2002 wins. briefly wore 2 stars on a tour of europe in 1968 \\
1 & italy & world cup & 1982 & 4 & added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006 \\
2 & germany & world cup & 1996 & 3 & 1954, 1974, third win was in 1990 \\
3 & uruguay & world cup and olympics & 1930 & 4 & represent 2 world cups (1930 & 1950) and 2 olympic football titles (1924 & 1928) recognized as fifa world championships \\
4 & argentina & world cup & 2003 & 2 & 1978, second win was in 1986 \\
5 & england & world cup & 2003 & 1 & title won in 1966. star added after a campaign on sky sports' soccer am programme, first worn on the sleeve \\
6 & france & world cup & 1998 & 1 & title won in 1998. star added above their badge which was unveiled at their opening qualifying game for euro 2000 \\
7 & spain & world cup & 2010 & 1 & title won in 2010. spain played in their away kit for the final, but upon winning the world cup they changed into their home kit, complete with a star above the badge, for the presentation ceremony \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& first worn \\
\midrule
0 & 2003 \\
1 & 2003 \\
2 & 2010 \\
\bottomrule
\end{tabular}
| select first worn where first worn > 2002 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>national team</th>
<th>title(s) represented</th>
<th>first worn</th>
<th>number of stars</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>brazil</td>
<td>world cup</td>
<td>1971</td>
<td>5</td>
<td>third win was in 1970; fourth and fifth stars added after 1994 and 2002 wins. briefly wore 2 stars on a tour of europe in 1968</td>
</tr>
<tr>
<th>1</th>
<td>italy</td>
<td>world cup</td>
<td>1982</td>
<td>4</td>
<td>added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006</td>
</tr>
<tr>
<th>2</th>
<td>germany</td>
<td>world cup</td>
<td>1996</td>
<td>3</td>
<td>1954, 1974, third win was in 1990</td>
</tr>
<tr>
<th>3</th>
<td>uruguay</td>
<td>world cup and olympics</td>
<td>1930</td>
<td>4</td>
<td>represent 2 world cups (1930 & 1950) and 2 olympic football titles (1924 & 1928) recognized as fifa world championships</td>
</tr>
<tr>
<th>4</th>
<td>argentina</td>
<td>world cup</td>
<td>2003</td>
<td>2</td>
<td>1978, second win was in 1986</td>
</tr>
<tr>
<th>5</th>
<td>england</td>
<td>world cup</td>
<td>2003</td>
<td>1</td>
<td>title won in 1966. star added after a campaign on sky sports' soccer am programme, first worn on the sleeve</td>
</tr>
<tr>
<th>6</th>
<td>france</td>
<td>world cup</td>
<td>1998</td>
<td>1</td>
<td>title won in 1998. star added above their badge which was unveiled at their opening qualifying game for euro 2000</td>
</tr>
<tr>
<th>7</th>
<td>spain</td>
<td>world cup</td>
<td>2010</td>
<td>1</td>
<td>title won in 2010. spain played in their away kit for the final, but upon winning the world cup they changed into their home kit, complete with a star above the badge, for the presentation ceremony</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>first worn</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2003</td>
</tr>
<tr>
<th>1</th>
<td>2003</td>
</tr>
<tr>
<th>2</th>
<td>2010</td>
</tr>
</tbody>
</table> | select first worn where first worn > 2002 <table_name> : table | | national team | title(s) represented | first worn | number of stars | notes |
|---:|:----------------|:-----------------------|-------------:|------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | brazil | world cup | 1971 | 5 | third win was in 1970; fourth and fifth stars added after 1994 and 2002 wins. briefly wore 2 stars on a tour of europe in 1968 |
| 1 | italy | world cup | 1982 | 4 | added after third win; fourth star added after the 2006 win. incorporated into the badge since 2006 |
| 2 | germany | world cup | 1996 | 3 | 1954, 1974, third win was in 1990 |
| 3 | uruguay | world cup and olympics | 1930 | 4 | represent 2 world cups (1930 & 1950) and 2 olympic football titles (1924 & 1928) recognized as fifa world championships |
| 4 | argentina | world cup | 2003 | 2 | 1978, second win was in 1986 |
| 5 | england | world cup | 2003 | 1 | title won in 1966. star added after a campaign on sky sports' soccer am programme, first worn on the sleeve |
| 6 | france | world cup | 1998 | 1 | title won in 1998. star added above their badge which was unveiled at their opening qualifying game for euro 2000 |
| 7 | spain | world cup | 2010 | 1 | title won in 2010. spain played in their away kit for the final, but upon winning the world cup they changed into their home kit, complete with a star above the badge, for the presentation ceremony | | | | first worn |
|---:|-------------:|
| 0 | 2003 |
| 1 | 2003 |
| 2 | 2010 | | [
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select count ( * ) where function = 'plenipotentiary in hungary' col : name | function | sentence row 1 : ernst von weizsacker | permanent secretary of state in the auswartiges amt (foreign ministry) under ribbentrop until 1943, then ambassador to the holy see; ss-brigadefuhrer | 7 years' imprisonment; reduced to 5 years on december 12, 1949, released in october 1950 row 2 : gustav adolf steengracht von moyland | successor of von weizsacker as secretary of state in the foreign ministry (until 1945) | 7 years' imprisonment; reduced to 5 years on december 12, 1949, released 1950 row 3 : wilhelm keppler | secretary of state; hitler's advisor for economy | 10 years' imprisonment; released 1951 row 4 : ernst wilhelm bohle | ns-gauleiter, secretary of state in the foreign ministry; head of the auslandorganisation (foreign organization) of the nsdap | 5 years' imprisonment row 5 : ernst woermann (de) | secretary in the foreign ministry; head of the political division | 7 years' imprisonment; reduced to 5 years on december 12, 1949; released 1951 row 6 : karl ritter | liaison between foreign office and the high command of the german armed forces | 4 years' imprisonment incl. time already served; released after the judgment row 7 : otto von erdmannsdorff | secretary in the foreign ministry; deputy to wormann | acquitted row 8 : edmund veesenmayer | plenipotentiary in hungary | 20 years' imprisonment; reduced to 10 years in 1951 and released the same year row 9 : hans heinrich lammers | head of the reich chancellery | 20 years' imprisonment; reduced to 10 years in january 1951 and released december 16, 1951 row 10 : wilhelm stuckart | secretary of state in the interior ministry | time already served (3 years and 10 months) row 11 : richard walther darre | minister for food and agriculture | 7 years' imprisonment; released 1950 row 12 : otto meissner | head of the presidential chancellery | acquitted row 13 : otto dietrich | reichspressechef of the nsdap and secretary of state in the propagandaministerium | 7 years' imprisonment incl. time already served; released in 1950 row 14 : gottlob berger | head of the ss-hauptamt, ss-obergruppenfuhrer | 25 years' imprisonment; reduced to 10 years in 1951; released the same year row 15 : walter schellenberg | second-in-command of the gestapo, head of the sd and the abwehr, and successor of wilhelm canaris as the head of the combined secret services; ss-brigadefuhrer | 6 years' imprisonment incl. time already served row 16 : lutz graf schwerin von krosigk | minister of finance | 10 years' imprisonment; released in 1951 row 17 : emil puhl | vice-president of the reichsbank | 5 years' imprisonment incl. time already served row 18 : karl rasche | director of the dresdner bank | 7 years' imprisonment incl. time already served row 19 : paul korner (de) | secretary of state, deputy of goring | 15 years' imprisonment; reduced to 10 years in 1951; released the same year row 20 : paul pleiger | head of the reichswerke hermann goring (confiscated steel plants employing slave laborers) | 15 years' imprisonment; reduced to 10 years in 1951; released the same year row 21 : hans kehrl (de) | secretary in the ministry of armament; head of the planning office | 15 years' imprisonment; released in 1951 | col : count ( "*" ) row 1 : 1 | select count ( * ) where function = 'plenipotentiary in hungary' <table_name> : table \begin{tabular}{llll}
\toprule
& name & function & sentence \\
\midrule
0 & ernst von weizsacker & permanent secretary of state in the auswartiges amt (foreign ministry) under ribbentrop until 1943, then ambassador to the holy see; ss-brigadefuhrer & 7 years' imprisonment; reduced to 5 years on december 12, 1949, released in october 1950 \\
1 & gustav adolf steengracht von moyland & successor of von weizsacker as secretary of state in the foreign ministry (until 1945) & 7 years' imprisonment; reduced to 5 years on december 12, 1949, released 1950 \\
2 & wilhelm keppler & secretary of state; hitler's advisor for economy & 10 years' imprisonment; released 1951 \\
3 & ernst wilhelm bohle & ns-gauleiter, secretary of state in the foreign ministry; head of the auslandorganisation (foreign organization) of the nsdap & 5 years' imprisonment \\
4 & ernst woermann (de) & secretary in the foreign ministry; head of the political division & 7 years' imprisonment; reduced to 5 years on december 12, 1949; released 1951 \\
5 & karl ritter & liaison between foreign office and the high command of the german armed forces & 4 years' imprisonment incl. time already served; released after the judgment \\
6 & otto von erdmannsdorff & secretary in the foreign ministry; deputy to wormann & acquitted \\
7 & edmund veesenmayer & plenipotentiary in hungary & 20 years' imprisonment; reduced to 10 years in 1951 and released the same year \\
8 & hans heinrich lammers & head of the reich chancellery & 20 years' imprisonment; reduced to 10 years in january 1951 and released december 16, 1951 \\
9 & wilhelm stuckart & secretary of state in the interior ministry & time already served (3 years and 10 months) \\
10 & richard walther darre & minister for food and agriculture & 7 years' imprisonment; released 1950 \\
11 & otto meissner & head of the presidential chancellery & acquitted \\
12 & otto dietrich & reichspressechef of the nsdap and secretary of state in the propagandaministerium & 7 years' imprisonment incl. time already served; released in 1950 \\
13 & gottlob berger & head of the ss-hauptamt, ss-obergruppenfuhrer & 25 years' imprisonment; reduced to 10 years in 1951; released the same year \\
14 & walter schellenberg & second-in-command of the gestapo, head of the sd and the abwehr, and successor of wilhelm canaris as the head of the combined secret services; ss-brigadefuhrer & 6 years' imprisonment incl. time already served \\
15 & lutz graf schwerin von krosigk & minister of finance & 10 years' imprisonment; released in 1951 \\
16 & emil puhl & vice-president of the reichsbank & 5 years' imprisonment incl. time already served \\
17 & karl rasche & director of the dresdner bank & 7 years' imprisonment incl. time already served \\
18 & paul korner (de) & secretary of state, deputy of goring & 15 years' imprisonment; reduced to 10 years in 1951; released the same year \\
19 & paul pleiger & head of the reichswerke hermann goring (confiscated steel plants employing slave laborers) & 15 years' imprisonment; reduced to 10 years in 1951; released the same year \\
20 & hans kehrl (de) & secretary in the ministry of armament; head of the planning office & 15 years' imprisonment; released in 1951 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where function = 'plenipotentiary in hungary' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>function</th>
<th>sentence</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>ernst von weizsacker</td>
<td>permanent secretary of state in the auswartiges amt (foreign ministry) under ribbentrop until 1943, then ambassador to the holy see; ss-brigadefuhrer</td>
<td>7 years' imprisonment; reduced to 5 years on december 12, 1949, released in october 1950</td>
</tr>
<tr>
<th>1</th>
<td>gustav adolf steengracht von moyland</td>
<td>successor of von weizsacker as secretary of state in the foreign ministry (until 1945)</td>
<td>7 years' imprisonment; reduced to 5 years on december 12, 1949, released 1950</td>
</tr>
<tr>
<th>2</th>
<td>wilhelm keppler</td>
<td>secretary of state; hitler's advisor for economy</td>
<td>10 years' imprisonment; released 1951</td>
</tr>
<tr>
<th>3</th>
<td>ernst wilhelm bohle</td>
<td>ns-gauleiter, secretary of state in the foreign ministry; head of the auslandorganisation (foreign organization) of the nsdap</td>
<td>5 years' imprisonment</td>
</tr>
<tr>
<th>4</th>
<td>ernst woermann (de)</td>
<td>secretary in the foreign ministry; head of the political division</td>
<td>7 years' imprisonment; reduced to 5 years on december 12, 1949; released 1951</td>
</tr>
<tr>
<th>5</th>
<td>karl ritter</td>
<td>liaison between foreign office and the high command of the german armed forces</td>
<td>4 years' imprisonment incl. time already served; released after the judgment</td>
</tr>
<tr>
<th>6</th>
<td>otto von erdmannsdorff</td>
<td>secretary in the foreign ministry; deputy to wormann</td>
<td>acquitted</td>
</tr>
<tr>
<th>7</th>
<td>edmund veesenmayer</td>
<td>plenipotentiary in hungary</td>
<td>20 years' imprisonment; reduced to 10 years in 1951 and released the same year</td>
</tr>
<tr>
<th>8</th>
<td>hans heinrich lammers</td>
<td>head of the reich chancellery</td>
<td>20 years' imprisonment; reduced to 10 years in january 1951 and released december 16, 1951</td>
</tr>
<tr>
<th>9</th>
<td>wilhelm stuckart</td>
<td>secretary of state in the interior ministry</td>
<td>time already served (3 years and 10 months)</td>
</tr>
<tr>
<th>10</th>
<td>richard walther darre</td>
<td>minister for food and agriculture</td>
<td>7 years' imprisonment; released 1950</td>
</tr>
<tr>
<th>11</th>
<td>otto meissner</td>
<td>head of the presidential chancellery</td>
<td>acquitted</td>
</tr>
<tr>
<th>12</th>
<td>otto dietrich</td>
<td>reichspressechef of the nsdap and secretary of state in the propagandaministerium</td>
<td>7 years' imprisonment incl. time already served; released in 1950</td>
</tr>
<tr>
<th>13</th>
<td>gottlob berger</td>
<td>head of the ss-hauptamt, ss-obergruppenfuhrer</td>
<td>25 years' imprisonment; reduced to 10 years in 1951; released the same year</td>
</tr>
<tr>
<th>14</th>
<td>walter schellenberg</td>
<td>second-in-command of the gestapo, head of the sd and the abwehr, and successor of wilhelm canaris as the head of the combined secret services; ss-brigadefuhrer</td>
<td>6 years' imprisonment incl. time already served</td>
</tr>
<tr>
<th>15</th>
<td>lutz graf schwerin von krosigk</td>
<td>minister of finance</td>
<td>10 years' imprisonment; released in 1951</td>
</tr>
<tr>
<th>16</th>
<td>emil puhl</td>
<td>vice-president of the reichsbank</td>
<td>5 years' imprisonment incl. time already served</td>
</tr>
<tr>
<th>17</th>
<td>karl rasche</td>
<td>director of the dresdner bank</td>
<td>7 years' imprisonment incl. time already served</td>
</tr>
<tr>
<th>18</th>
<td>paul korner (de)</td>
<td>secretary of state, deputy of goring</td>
<td>15 years' imprisonment; reduced to 10 years in 1951; released the same year</td>
</tr>
<tr>
<th>19</th>
<td>paul pleiger</td>
<td>head of the reichswerke hermann goring (confiscated steel plants employing slave laborers)</td>
<td>15 years' imprisonment; reduced to 10 years in 1951; released the same year</td>
</tr>
<tr>
<th>20</th>
<td>hans kehrl (de)</td>
<td>secretary in the ministry of armament; head of the planning office</td>
<td>15 years' imprisonment; released in 1951</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 function = 'plenipotentiary in hungary' <table_name> : table | | name | function | sentence |
|---:|:-------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------|
| 0 | ernst von weizsacker | permanent secretary of state in the auswartiges amt (foreign ministry) under ribbentrop until 1943, then ambassador to the holy see; ss-brigadefuhrer | 7 years' imprisonment; reduced to 5 years on december 12, 1949, released in october 1950 |
| 1 | gustav adolf steengracht von moyland | successor of von weizsacker as secretary of state in the foreign ministry (until 1945) | 7 years' imprisonment; reduced to 5 years on december 12, 1949, released 1950 |
| 2 | wilhelm keppler | secretary of state; hitler's advisor for economy | 10 years' imprisonment; released 1951 |
| 3 | ernst wilhelm bohle | ns-gauleiter, secretary of state in the foreign ministry; head of the auslandorganisation (foreign organization) of the nsdap | 5 years' imprisonment |
| 4 | ernst woermann (de) | secretary in the foreign ministry; head of the political division | 7 years' imprisonment; reduced to 5 years on december 12, 1949; released 1951 |
| 5 | karl ritter | liaison between foreign office and the high command of the german armed forces | 4 years' imprisonment incl. time already served; released after the judgment |
| 6 | otto von erdmannsdorff | secretary in the foreign ministry; deputy to wormann | acquitted |
| 7 | edmund veesenmayer | plenipotentiary in hungary | 20 years' imprisonment; reduced to 10 years in 1951 and released the same year |
| 8 | hans heinrich lammers | head of the reich chancellery | 20 years' imprisonment; reduced to 10 years in january 1951 and released december 16, 1951 |
| 9 | wilhelm stuckart | secretary of state in the interior ministry | time already served (3 years and 10 months) |
| 10 | richard walther darre | minister for food and agriculture | 7 years' imprisonment; released 1950 |
| 11 | otto meissner | head of the presidential chancellery | acquitted |
| 12 | otto dietrich | reichspressechef of the nsdap and secretary of state in the propagandaministerium | 7 years' imprisonment incl. time already served; released in 1950 |
| 13 | gottlob berger | head of the ss-hauptamt, ss-obergruppenfuhrer | 25 years' imprisonment; reduced to 10 years in 1951; released the same year |
| 14 | walter schellenberg | second-in-command of the gestapo, head of the sd and the abwehr, and successor of wilhelm canaris as the head of the combined secret services; ss-brigadefuhrer | 6 years' imprisonment incl. time already served |
| 15 | lutz graf schwerin von krosigk | minister of finance | 10 years' imprisonment; released in 1951 |
| 16 | emil puhl | vice-president of the reichsbank | 5 years' imprisonment incl. time already served |
| 17 | karl rasche | director of the dresdner bank | 7 years' imprisonment incl. time already served |
| 18 | paul korner (de) | secretary of state, deputy of goring | 15 years' imprisonment; reduced to 10 years in 1951; released the same year |
| 19 | paul pleiger | head of the reichswerke hermann goring (confiscated steel plants employing slave laborers) | 15 years' imprisonment; reduced to 10 years in 1951; released the same year |
| 20 | hans kehrl (de) | secretary in the ministry of armament; head of the planning office | 15 years' imprisonment; released in 1951 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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2
]
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select maps where names = 'ռստամ-սսհմ' col : volume | year | names | articles | pages | images | maps | number of copies row 1 : 1 | 1974 | ա-արգինա | 3442 | 720 | 1294 | 75 | 100000 row 2 : 2 | 1976 | արգիշտի-գեղերվան | 3503 | 720 | 1798 | 75 | 100000 row 3 : 3 | 1977 | գեղեցիկը-զուրաբյան | 3509 | 720 | 1726 | 53 | 100000 row 4 : 4 | 1978 | է-խաղխաղ | 3451 | 720 | 1228 | 53 | 100000 row 5 : 5 | 1979 | խաղող-կուլիսներ | 3694 | 720 | 1326 | 68 | 100000 row 6 : 6 | 1980 | կուլզոր-ձուլուկ | 3108 | 720 | 1097 | 64 | 100000 row 7 : 7 | 1981 | ձուլում-մոնոպխոնք | 3250 | 720 | 1436 | 46 | 100000 row 8 : 8 | 1982 | մոնոպոլիա-չեչերեկ | 3145 | 720 | 1274 | 70 | 100000 row 9 : 9 | 1983 | չեչքար-ռստակես | 3185 | 720 | 1046 | 60 | 100000 row 10 : 10 | 1984 | ռստամ-սսհմ | 2009 | 736 | 1065 | 61 | 100000 row 11 : 11 | 1985 | սովետական-տիեզերք | 2970 | 720 | 958 | 67 | 100000 row 12 : 12 | 1986 | տիեպոլո-ֆուքսին | 3501 | 752 | 1015 | 96 | 100000 row 13 : total | 1974-1986 | ա-ֆուքսին | 36767 | 8688 | 15263 | 858 | 1200000 row 14 : 13 | 1987 | սովետական հայաստան | none | none | none | none | none | col : maps row 1 : 61 | select maps where names = 'ռստամ-սսհմ' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& volume & year & names & articles & pages & images & maps & number of copies \\
\midrule
0 & 1 & 1974 & ա-արգինա & 3442 & 720 & 1294 & 75 & 100000 \\
1 & 2 & 1976 & արգիշտի-գեղերվան & 3503 & 720 & 1798 & 75 & 100000 \\
2 & 3 & 1977 & գեղեցիկը-զուրաբյան & 3509 & 720 & 1726 & 53 & 100000 \\
3 & 4 & 1978 & է-խաղխաղ & 3451 & 720 & 1228 & 53 & 100000 \\
4 & 5 & 1979 & խաղող-կուլիսներ & 3694 & 720 & 1326 & 68 & 100000 \\
5 & 6 & 1980 & կուլզոր-ձուլուկ & 3108 & 720 & 1097 & 64 & 100000 \\
6 & 7 & 1981 & ձուլում-մոնոպխոնք & 3250 & 720 & 1436 & 46 & 100000 \\
7 & 8 & 1982 & մոնոպոլիա-չեչերեկ & 3145 & 720 & 1274 & 70 & 100000 \\
8 & 9 & 1983 & չեչքար-ռստակես & 3185 & 720 & 1046 & 60 & 100000 \\
9 & 10 & 1984 & ռստամ-սսհմ & 2009 & 736 & 1065 & 61 & 100000 \\
10 & 11 & 1985 & սովետական-տիեզերք & 2970 & 720 & 958 & 67 & 100000 \\
11 & 12 & 1986 & տիեպոլո-ֆուքսին & 3501 & 752 & 1015 & 96 & 100000 \\
12 & total & 1974-1986 & ա-ֆուքսին & 36767 & 8688 & 15263 & 858 & 1200000 \\
13 & 13 & 1987 & սովետական հայաստան & none & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& maps \\
\midrule
0 & 61 \\
\bottomrule
\end{tabular}
| select maps where names = 'ռստամ-սսհմ' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>volume</th>
<th>year</th>
<th>names</th>
<th>articles</th>
<th>pages</th>
<th>images</th>
<th>maps</th>
<th>number of copies</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1974</td>
<td>ա-արգինա</td>
<td>3442</td>
<td>720</td>
<td>1294</td>
<td>75</td>
<td>100000</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1976</td>
<td>արգիշտի-գեղերվան</td>
<td>3503</td>
<td>720</td>
<td>1798</td>
<td>75</td>
<td>100000</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1977</td>
<td>գեղեցիկը-զուրաբյան</td>
<td>3509</td>
<td>720</td>
<td>1726</td>
<td>53</td>
<td>100000</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1978</td>
<td>է-խաղխաղ</td>
<td>3451</td>
<td>720</td>
<td>1228</td>
<td>53</td>
<td>100000</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1979</td>
<td>խաղող-կուլիսներ</td>
<td>3694</td>
<td>720</td>
<td>1326</td>
<td>68</td>
<td>100000</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>1980</td>
<td>կուլզոր-ձուլուկ</td>
<td>3108</td>
<td>720</td>
<td>1097</td>
<td>64</td>
<td>100000</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>1981</td>
<td>ձուլում-մոնոպխոնք</td>
<td>3250</td>
<td>720</td>
<td>1436</td>
<td>46</td>
<td>100000</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>1982</td>
<td>մոնոպոլիա-չեչերեկ</td>
<td>3145</td>
<td>720</td>
<td>1274</td>
<td>70</td>
<td>100000</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>1983</td>
<td>չեչքար-ռստակես</td>
<td>3185</td>
<td>720</td>
<td>1046</td>
<td>60</td>
<td>100000</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>1984</td>
<td>ռստամ-սսհմ</td>
<td>2009</td>
<td>736</td>
<td>1065</td>
<td>61</td>
<td>100000</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>1985</td>
<td>սովետական-տիեզերք</td>
<td>2970</td>
<td>720</td>
<td>958</td>
<td>67</td>
<td>100000</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>1986</td>
<td>տիեպոլո-ֆուքսին</td>
<td>3501</td>
<td>752</td>
<td>1015</td>
<td>96</td>
<td>100000</td>
</tr>
<tr>
<th>12</th>
<td>total</td>
<td>1974-1986</td>
<td>ա-ֆուքսին</td>
<td>36767</td>
<td>8688</td>
<td>15263</td>
<td>858</td>
<td>1200000</td>
</tr>
<tr>
<th>13</th>
<td>13</td>
<td>1987</td>
<td>սովետական հայաստան</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>maps</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>61</td>
</tr>
</tbody>
</table> | select maps where names = 'ռստամ-սսհմ' <table_name> : table | | volume | year | names | articles | pages | images | maps | number of copies |
|---:|:---------|:----------|:-------------------|:-----------|:--------|:---------|:-------|:-------------------|
| 0 | 1 | 1974 | ա-արգինա | 3442 | 720 | 1294 | 75 | 100000 |
| 1 | 2 | 1976 | արգիշտի-գեղերվան | 3503 | 720 | 1798 | 75 | 100000 |
| 2 | 3 | 1977 | գեղեցիկը-զուրաբյան | 3509 | 720 | 1726 | 53 | 100000 |
| 3 | 4 | 1978 | է-խաղխաղ | 3451 | 720 | 1228 | 53 | 100000 |
| 4 | 5 | 1979 | խաղող-կուլիսներ | 3694 | 720 | 1326 | 68 | 100000 |
| 5 | 6 | 1980 | կուլզոր-ձուլուկ | 3108 | 720 | 1097 | 64 | 100000 |
| 6 | 7 | 1981 | ձուլում-մոնոպխոնք | 3250 | 720 | 1436 | 46 | 100000 |
| 7 | 8 | 1982 | մոնոպոլիա-չեչերեկ | 3145 | 720 | 1274 | 70 | 100000 |
| 8 | 9 | 1983 | չեչքար-ռստակես | 3185 | 720 | 1046 | 60 | 100000 |
| 9 | 10 | 1984 | ռստամ-սսհմ | 2009 | 736 | 1065 | 61 | 100000 |
| 10 | 11 | 1985 | սովետական-տիեզերք | 2970 | 720 | 958 | 67 | 100000 |
| 11 | 12 | 1986 | տիեպոլո-ֆուքսին | 3501 | 752 | 1015 | 96 | 100000 |
| 12 | total | 1974-1986 | ա-ֆուքսին | 36767 | 8688 | 15263 | 858 | 1200000 |
| 13 | 13 | 1987 | սովետական հայաստան | none | none | none | none | none | | | | maps |
|---:|-------:|
| 0 | 61 | | [
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select home or away where home or away = 'home' col : record | date and time | competition | home or away | opponent | score row 1 : biggest win | 19.10.1912 at 15:00 | spartan league | home | aylesbury united | 14-0 row 2 : biggest defeat | 09.11.1946 at 15:00 | isthmian league | home | wimbledon | 0-11 row 3 : most goals in one match | 22.11.1922 at 15:00 | fa cup / 4th qf (replay) | away | dulwich hamlet | 7-8 row 4 : biggest home win | 19.10.1912 at 15:00 | spartan league | home | aylesbury united | 14-0 row 5 : biggest home defeat | 09.11.1946 at 15:00 | isthmian league | home | wimbledon | 0-11 row 6 : biggest away win | 24.11.1970 at 15:00 | mithras cup 2nd rd (2nd leg) | away | ruislip manor | 10-0 row 7 : biggest away win | 17.04.1920 at 15:00 | spartan league | away | tufnell spartans | 11-1 row 8 : biggest away defeat | 04.11.2008 at 19:45 | herts charity cup | away | hemel hempstead town | 0-10 | col : home or away row 1 : home row 2 : home row 3 : home row 4 : home | select home or away where home or away = 'home' <table_name> : table \begin{tabular}{lllllll}
\toprule
& record & date and time & competition & home or away & opponent & score \\
\midrule
0 & biggest win & 19.10.1912 at 15:00 & spartan league & home & aylesbury united & 14-0 \\
1 & biggest defeat & 09.11.1946 at 15:00 & isthmian league & home & wimbledon & 0-11 \\
2 & most goals in one match & 22.11.1922 at 15:00 & fa cup / 4th qf (replay) & away & dulwich hamlet & 7-8 \\
3 & biggest home win & 19.10.1912 at 15:00 & spartan league & home & aylesbury united & 14-0 \\
4 & biggest home defeat & 09.11.1946 at 15:00 & isthmian league & home & wimbledon & 0-11 \\
5 & biggest away win & 24.11.1970 at 15:00 & mithras cup 2nd rd (2nd leg) & away & ruislip manor & 10-0 \\
6 & biggest away win & 17.04.1920 at 15:00 & spartan league & away & tufnell spartans & 11-1 \\
7 & biggest away defeat & 04.11.2008 at 19:45 & herts charity cup & away & hemel hempstead town & 0-10 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& home or away \\
\midrule
0 & home \\
1 & home \\
2 & home \\
3 & home \\
\bottomrule
\end{tabular}
| select home or away where home or away = 'home' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>record</th>
<th>date and time</th>
<th>competition</th>
<th>home or away</th>
<th>opponent</th>
<th>score</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>biggest win</td>
<td>19.10.1912 at 15:00</td>
<td>spartan league</td>
<td>home</td>
<td>aylesbury united</td>
<td>14-0</td>
</tr>
<tr>
<th>1</th>
<td>biggest defeat</td>
<td>09.11.1946 at 15:00</td>
<td>isthmian league</td>
<td>home</td>
<td>wimbledon</td>
<td>0-11</td>
</tr>
<tr>
<th>2</th>
<td>most goals in one match</td>
<td>22.11.1922 at 15:00</td>
<td>fa cup / 4th qf (replay)</td>
<td>away</td>
<td>dulwich hamlet</td>
<td>7-8</td>
</tr>
<tr>
<th>3</th>
<td>biggest home win</td>
<td>19.10.1912 at 15:00</td>
<td>spartan league</td>
<td>home</td>
<td>aylesbury united</td>
<td>14-0</td>
</tr>
<tr>
<th>4</th>
<td>biggest home defeat</td>
<td>09.11.1946 at 15:00</td>
<td>isthmian league</td>
<td>home</td>
<td>wimbledon</td>
<td>0-11</td>
</tr>
<tr>
<th>5</th>
<td>biggest away win</td>
<td>24.11.1970 at 15:00</td>
<td>mithras cup 2nd rd (2nd leg)</td>
<td>away</td>
<td>ruislip manor</td>
<td>10-0</td>
</tr>
<tr>
<th>6</th>
<td>biggest away win</td>
<td>17.04.1920 at 15:00</td>
<td>spartan league</td>
<td>away</td>
<td>tufnell spartans</td>
<td>11-1</td>
</tr>
<tr>
<th>7</th>
<td>biggest away defeat</td>
<td>04.11.2008 at 19:45</td>
<td>herts charity cup</td>
<td>away</td>
<td>hemel hempstead town</td>
<td>0-10</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>home or away</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>home</td>
</tr>
<tr>
<th>1</th>
<td>home</td>
</tr>
<tr>
<th>2</th>
<td>home</td>
</tr>
<tr>
<th>3</th>
<td>home</td>
</tr>
</tbody>
</table> | select home or away where home or away = 'home' <table_name> : table | | record | date and time | competition | home or away | opponent | score |
|---:|:------------------------|:--------------------|:-----------------------------|:---------------|:---------------------|:--------|
| 0 | biggest win | 19.10.1912 at 15:00 | spartan league | home | aylesbury united | 14-0 |
| 1 | biggest defeat | 09.11.1946 at 15:00 | isthmian league | home | wimbledon | 0-11 |
| 2 | most goals in one match | 22.11.1922 at 15:00 | fa cup / 4th qf (replay) | away | dulwich hamlet | 7-8 |
| 3 | biggest home win | 19.10.1912 at 15:00 | spartan league | home | aylesbury united | 14-0 |
| 4 | biggest home defeat | 09.11.1946 at 15:00 | isthmian league | home | wimbledon | 0-11 |
| 5 | biggest away win | 24.11.1970 at 15:00 | mithras cup 2nd rd (2nd leg) | away | ruislip manor | 10-0 |
| 6 | biggest away win | 17.04.1920 at 15:00 | spartan league | away | tufnell spartans | 11-1 |
| 7 | biggest away defeat | 04.11.2008 at 19:45 | herts charity cup | away | hemel hempstead town | 0-10 | | | | home or away |
|---:|:---------------|
| 0 | home |
| 1 | home |
| 2 | home |
| 3 | home | | [
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select grid where no = 27 col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 5 | nigel mansell | williams-renault | 65 | 1:56:10.674 | 1 | 10 row 2 : 2 | 19 | michael schumacher | benetton-ford | 65 | + 23.914 | 2 | 6 row 3 : 3 | 27 | jean alesi | ferrari | 65 | + 26.462 | 8 | 4 row 4 : 4 | 2 | gerhard berger | mclaren-honda | 65 | + 1:20.647 | 7 | 3 row 5 : 5 | 9 | michele alboreto | footwork-mugen-honda | 64 | + 1 lap | 16 | 2 row 6 : 6 | 22 | pierluigi martini | dallara-ferrari | 63 | + 2 laps | 13 | 1 row 7 : 7 | 10 | aguri suzuki | footwork-mugen-honda | 63 | + 2 laps | 19 | none row 8 : 8 | 16 | karl wendlinger | march-ilmor | 63 | + 2 laps | 9 | none row 9 : 9 | 1 | ayrton senna | mclaren-honda | 62 | spun off | 3 | none row 10 : 10 | 28 | ivan capelli | ferrari | 62 | spun off | 5 | none row 11 : 11 | 23 | christian fittipaldi | minardi-lamborghini | 61 | + 4 laps | 22 | none row 12 : 12 | 17 | paul belmondo | march-ilmor | 61 | + 4 laps | 23 | none row 13 : ret | 21 | jj lehto | dallara-ferrari | 56 | spun off | 12 | none row 14 : ret | 15 | gabriele tarquini | fondmetal-ford | 56 | spun off | 18 | none row 15 : ret | 11 | mika hakkinen | lotus-ford | 56 | spun off | 21 | none row 16 : ret | 26 | erik comas | ligier-renault | 55 | spun off | 10 | none row 17 : ret | 29 | bertrand gachot | larrousse-lamborghini | 35 | engine | 24 | none row 18 : ret | 3 | olivier grouillard | tyrrell-ilmor | 30 | spun off | 15 | none row 19 : ret | 24 | gianni morbidelli | minardi-lamborghini | 26 | handling | 25 | none row 20 : ret | 33 | mauricio gugelmin | jordan-yamaha | 24 | spun off | 17 | none row 21 : ret | 14 | andrea chiesa | fondmetal-ford | 22 | spun off | 20 | none row 22 : ret | 6 | riccardo patrese | williams-renault | 19 | spun off | 4 | none row 23 : ret | 12 | johnny herbert | lotus-ford | 13 | spun off | 26 | none row 24 : ret | 25 | thierry boutsen | ligier-renault | 11 | engine | 14 | none row 25 : ret | 20 | martin brundle | benetton-ford | 4 | spun off | 6 | none row 26 : ret | 4 | andrea de cesaris | tyrrell-ilmor | 2 | engine | 11 | none row 27 : dnq | 30 | ukyo katayama | larrousse-lamborghini | none | none | none | none row 28 : dnq | 7 | eric van de poele | brabham-judd | none | none | none | none row 29 : dnq | 32 | stefano modena | jordan-yamaha | none | none | none | none row 30 : dnq | 8 | damon hill | brabham-judd | none | none | none | none row 31 : dnpq | 34 | roberto moreno | moda-judd | none | none | none | none row 32 : dnpq | 35 | perry mccarthy | moda-judd | none | none | none | none | col : grid row 1 : 8 | select grid where no = 27 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & constructor & laps & time/retired & grid & points \\
\midrule
0 & 1 & 5 & nigel mansell & williams-renault & 65 & 1:56:10.674 & 1 & 10 \\
1 & 2 & 19 & michael schumacher & benetton-ford & 65 & + 23.914 & 2 & 6 \\
2 & 3 & 27 & jean alesi & ferrari & 65 & + 26.462 & 8 & 4 \\
3 & 4 & 2 & gerhard berger & mclaren-honda & 65 & + 1:20.647 & 7 & 3 \\
4 & 5 & 9 & michele alboreto & footwork-mugen-honda & 64 & + 1 lap & 16 & 2 \\
5 & 6 & 22 & pierluigi martini & dallara-ferrari & 63 & + 2 laps & 13 & 1 \\
6 & 7 & 10 & aguri suzuki & footwork-mugen-honda & 63 & + 2 laps & 19 & none \\
7 & 8 & 16 & karl wendlinger & march-ilmor & 63 & + 2 laps & 9 & none \\
8 & 9 & 1 & ayrton senna & mclaren-honda & 62 & spun off & 3 & none \\
9 & 10 & 28 & ivan capelli & ferrari & 62 & spun off & 5 & none \\
10 & 11 & 23 & christian fittipaldi & minardi-lamborghini & 61 & + 4 laps & 22 & none \\
11 & 12 & 17 & paul belmondo & march-ilmor & 61 & + 4 laps & 23 & none \\
12 & ret & 21 & jj lehto & dallara-ferrari & 56 & spun off & 12 & none \\
13 & ret & 15 & gabriele tarquini & fondmetal-ford & 56 & spun off & 18 & none \\
14 & ret & 11 & mika hakkinen & lotus-ford & 56 & spun off & 21 & none \\
15 & ret & 26 & erik comas & ligier-renault & 55 & spun off & 10 & none \\
16 & ret & 29 & bertrand gachot & larrousse-lamborghini & 35 & engine & 24 & none \\
17 & ret & 3 & olivier grouillard & tyrrell-ilmor & 30 & spun off & 15 & none \\
18 & ret & 24 & gianni morbidelli & minardi-lamborghini & 26 & handling & 25 & none \\
19 & ret & 33 & mauricio gugelmin & jordan-yamaha & 24 & spun off & 17 & none \\
20 & ret & 14 & andrea chiesa & fondmetal-ford & 22 & spun off & 20 & none \\
21 & ret & 6 & riccardo patrese & williams-renault & 19 & spun off & 4 & none \\
22 & ret & 12 & johnny herbert & lotus-ford & 13 & spun off & 26 & none \\
23 & ret & 25 & thierry boutsen & ligier-renault & 11 & engine & 14 & none \\
24 & ret & 20 & martin brundle & benetton-ford & 4 & spun off & 6 & none \\
25 & ret & 4 & andrea de cesaris & tyrrell-ilmor & 2 & engine & 11 & none \\
26 & dnq & 30 & ukyo katayama & larrousse-lamborghini & none & none & none & none \\
27 & dnq & 7 & eric van de poele & brabham-judd & none & none & none & none \\
28 & dnq & 32 & stefano modena & jordan-yamaha & none & none & none & none \\
29 & dnq & 8 & damon hill & brabham-judd & none & none & none & none \\
30 & dnpq & 34 & roberto moreno & moda-judd & none & none & none & none \\
31 & dnpq & 35 & perry mccarthy & moda-judd & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& grid \\
\midrule
0 & 8 \\
\bottomrule
\end{tabular}
| select grid where no = 27 <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>5</td>
<td>nigel mansell</td>
<td>williams-renault</td>
<td>65</td>
<td>1:56:10.674</td>
<td>1</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>19</td>
<td>michael schumacher</td>
<td>benetton-ford</td>
<td>65</td>
<td>+ 23.914</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>27</td>
<td>jean alesi</td>
<td>ferrari</td>
<td>65</td>
<td>+ 26.462</td>
<td>8</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2</td>
<td>gerhard berger</td>
<td>mclaren-honda</td>
<td>65</td>
<td>+ 1:20.647</td>
<td>7</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>9</td>
<td>michele alboreto</td>
<td>footwork-mugen-honda</td>
<td>64</td>
<td>+ 1 lap</td>
<td>16</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>22</td>
<td>pierluigi martini</td>
<td>dallara-ferrari</td>
<td>63</td>
<td>+ 2 laps</td>
<td>13</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>10</td>
<td>aguri suzuki</td>
<td>footwork-mugen-honda</td>
<td>63</td>
<td>+ 2 laps</td>
<td>19</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>16</td>
<td>karl wendlinger</td>
<td>march-ilmor</td>
<td>63</td>
<td>+ 2 laps</td>
<td>9</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>1</td>
<td>ayrton senna</td>
<td>mclaren-honda</td>
<td>62</td>
<td>spun off</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>28</td>
<td>ivan capelli</td>
<td>ferrari</td>
<td>62</td>
<td>spun off</td>
<td>5</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>23</td>
<td>christian fittipaldi</td>
<td>minardi-lamborghini</td>
<td>61</td>
<td>+ 4 laps</td>
<td>22</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>17</td>
<td>paul belmondo</td>
<td>march-ilmor</td>
<td>61</td>
<td>+ 4 laps</td>
<td>23</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>ret</td>
<td>21</td>
<td>jj lehto</td>
<td>dallara-ferrari</td>
<td>56</td>
<td>spun off</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>ret</td>
<td>15</td>
<td>gabriele tarquini</td>
<td>fondmetal-ford</td>
<td>56</td>
<td>spun off</td>
<td>18</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>ret</td>
<td>11</td>
<td>mika hakkinen</td>
<td>lotus-ford</td>
<td>56</td>
<td>spun off</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>ret</td>
<td>26</td>
<td>erik comas</td>
<td>ligier-renault</td>
<td>55</td>
<td>spun off</td>
<td>10</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>ret</td>
<td>29</td>
<td>bertrand gachot</td>
<td>larrousse-lamborghini</td>
<td>35</td>
<td>engine</td>
<td>24</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>ret</td>
<td>3</td>
<td>olivier grouillard</td>
<td>tyrrell-ilmor</td>
<td>30</td>
<td>spun off</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>24</td>
<td>gianni morbidelli</td>
<td>minardi-lamborghini</td>
<td>26</td>
<td>handling</td>
<td>25</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>33</td>
<td>mauricio gugelmin</td>
<td>jordan-yamaha</td>
<td>24</td>
<td>spun off</td>
<td>17</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>ret</td>
<td>14</td>
<td>andrea chiesa</td>
<td>fondmetal-ford</td>
<td>22</td>
<td>spun off</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>ret</td>
<td>6</td>
<td>riccardo patrese</td>
<td>williams-renault</td>
<td>19</td>
<td>spun off</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>ret</td>
<td>12</td>
<td>johnny herbert</td>
<td>lotus-ford</td>
<td>13</td>
<td>spun off</td>
<td>26</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>ret</td>
<td>25</td>
<td>thierry boutsen</td>
<td>ligier-renault</td>
<td>11</td>
<td>engine</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>20</td>
<td>martin brundle</td>
<td>benetton-ford</td>
<td>4</td>
<td>spun off</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>4</td>
<td>andrea de cesaris</td>
<td>tyrrell-ilmor</td>
<td>2</td>
<td>engine</td>
<td>11</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>dnq</td>
<td>30</td>
<td>ukyo katayama</td>
<td>larrousse-lamborghini</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>dnq</td>
<td>7</td>
<td>eric van de poele</td>
<td>brabham-judd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>dnq</td>
<td>32</td>
<td>stefano modena</td>
<td>jordan-yamaha</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>dnq</td>
<td>8</td>
<td>damon hill</td>
<td>brabham-judd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>dnpq</td>
<td>34</td>
<td>roberto moreno</td>
<td>moda-judd</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>dnpq</td>
<td>35</td>
<td>perry mccarthy</td>
<td>moda-judd</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>grid</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>8</td>
</tr>
</tbody>
</table> | select grid where no = 27 <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points |
|---:|:------|-----:|:---------------------|:----------------------|:-------|:---------------|:-------|:---------|
| 0 | 1 | 5 | nigel mansell | williams-renault | 65 | 1:56:10.674 | 1 | 10 |
| 1 | 2 | 19 | michael schumacher | benetton-ford | 65 | + 23.914 | 2 | 6 |
| 2 | 3 | 27 | jean alesi | ferrari | 65 | + 26.462 | 8 | 4 |
| 3 | 4 | 2 | gerhard berger | mclaren-honda | 65 | + 1:20.647 | 7 | 3 |
| 4 | 5 | 9 | michele alboreto | footwork-mugen-honda | 64 | + 1 lap | 16 | 2 |
| 5 | 6 | 22 | pierluigi martini | dallara-ferrari | 63 | + 2 laps | 13 | 1 |
| 6 | 7 | 10 | aguri suzuki | footwork-mugen-honda | 63 | + 2 laps | 19 | none |
| 7 | 8 | 16 | karl wendlinger | march-ilmor | 63 | + 2 laps | 9 | none |
| 8 | 9 | 1 | ayrton senna | mclaren-honda | 62 | spun off | 3 | none |
| 9 | 10 | 28 | ivan capelli | ferrari | 62 | spun off | 5 | none |
| 10 | 11 | 23 | christian fittipaldi | minardi-lamborghini | 61 | + 4 laps | 22 | none |
| 11 | 12 | 17 | paul belmondo | march-ilmor | 61 | + 4 laps | 23 | none |
| 12 | ret | 21 | jj lehto | dallara-ferrari | 56 | spun off | 12 | none |
| 13 | ret | 15 | gabriele tarquini | fondmetal-ford | 56 | spun off | 18 | none |
| 14 | ret | 11 | mika hakkinen | lotus-ford | 56 | spun off | 21 | none |
| 15 | ret | 26 | erik comas | ligier-renault | 55 | spun off | 10 | none |
| 16 | ret | 29 | bertrand gachot | larrousse-lamborghini | 35 | engine | 24 | none |
| 17 | ret | 3 | olivier grouillard | tyrrell-ilmor | 30 | spun off | 15 | none |
| 18 | ret | 24 | gianni morbidelli | minardi-lamborghini | 26 | handling | 25 | none |
| 19 | ret | 33 | mauricio gugelmin | jordan-yamaha | 24 | spun off | 17 | none |
| 20 | ret | 14 | andrea chiesa | fondmetal-ford | 22 | spun off | 20 | none |
| 21 | ret | 6 | riccardo patrese | williams-renault | 19 | spun off | 4 | none |
| 22 | ret | 12 | johnny herbert | lotus-ford | 13 | spun off | 26 | none |
| 23 | ret | 25 | thierry boutsen | ligier-renault | 11 | engine | 14 | none |
| 24 | ret | 20 | martin brundle | benetton-ford | 4 | spun off | 6 | none |
| 25 | ret | 4 | andrea de cesaris | tyrrell-ilmor | 2 | engine | 11 | none |
| 26 | dnq | 30 | ukyo katayama | larrousse-lamborghini | none | none | none | none |
| 27 | dnq | 7 | eric van de poele | brabham-judd | none | none | none | none |
| 28 | dnq | 32 | stefano modena | jordan-yamaha | none | none | none | none |
| 29 | dnq | 8 | damon hill | brabham-judd | none | none | none | none |
| 30 | dnpq | 34 | roberto moreno | moda-judd | none | none | none | none |
| 31 | dnpq | 35 | perry mccarthy | moda-judd | none | none | none | none | | | | grid |
|---:|-------:|
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select year where place = 'zagreb' col : year | place | gold | silver | bronze row 1 : 1970 | phoenix | united states of america sally carroll lucile chambliss barbara hile | soviet union nadezda ibragimova nina rasskazova nina stoliarova | federal republic of germany ortrud feickert karin fitzner ruth kasten row 2 : 1974 | thun | soviet union galina zarikova zinaida simonian nina stoliarova | czechoslovakia tereza bohinska bedriska hykova katarina pastorova | australia judith harrison enid newton gloria vause row 3 : 1978 | seoul | denmark kirsten broge bonnie bruun aase havsteen | australia julie aitken patricia dench lynne uden | united states of america sally carroll kimberly dyer ruby fox row 4 : 1982 | caracas | soviet union marina dobrantcheva inna rose auksne treinite | hungary palma balogh marta kotroczo gabriella kanyai | people's republic of china jianmin gao zhifang wen cui qing yang row 5 : 1986 | suhl | soviet union marina dobrantcheva irina kotcherova nino salukvadze | france martine guepin evelyne manchon corine serra-tosio | albania diana mata emanuela delilaj edlira shyti row 6 : 1990 | moscow | soviet union yauheniya haluza marina logvinenko nino salukvadze | sweden kerstin bodin britt marie ellis chris kajd | people's republic of china haiying liu duihong li meifang qian row 7 : 1994 | milan | people's republic of china xiaoping fan duihong li lina wang | korea soon hee boo sun bok lee jung hee park | belarus zhanna shitik yauheniya haluza yuliya siniak row 8 : 1998 | barcelona | people's republic of china yeqing cai luna tao yi sun | korea eun kyung shin soon hee boo joo hyung seo | mongolia munkhbayar dorjsuren oyun davaajantsan gundegmaa otryad row 9 : 2002 | lahti | people's republic of china luna tao ying chen duihong li | russia irina dolgatcheva galina beliaeva svetlana smirnova | united states of america elizabeth callahan rebecca snyder sandra uptagrafft row 10 : 2006 | zagreb | people's republic of china ying chen fengji fei duihong li | belarus liudmila chabatar zhanna shapialevich yauheniya haluza | germany munkhbayar dorjsuren stefanie thurmann claudia verdicchio row 11 : 2010 | munich | russia yulia alipova kira klimova galina beliaeva | serbia zorana arunovic jasna sekaric jelena arunovic | czech republic lenka maruskova michaela musilova petra hykova row 12 : 2014 | granada | none | none | none row 13 : 2018 | changwon | none | none | none | col : year row 1 : 2006 | select year where place = 'zagreb' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & place & gold & silver & bronze \\
\midrule
0 & 1970 & phoenix & united states of america sally carroll lucile chambliss barbara hile & soviet union nadezda ibragimova nina rasskazova nina stoliarova & federal republic of germany ortrud feickert karin fitzner ruth kasten \\
1 & 1974 & thun & soviet union galina zarikova zinaida simonian nina stoliarova & czechoslovakia tereza bohinska bedriska hykova katarina pastorova & australia judith harrison enid newton gloria vause \\
2 & 1978 & seoul & denmark kirsten broge bonnie bruun aase havsteen & australia julie aitken patricia dench lynne uden & united states of america sally carroll kimberly dyer ruby fox \\
3 & 1982 & caracas & soviet union marina dobrantcheva inna rose auksne treinite & hungary palma balogh marta kotroczo gabriella kanyai & people's republic of china jianmin gao zhifang wen cui qing yang \\
4 & 1986 & suhl & soviet union marina dobrantcheva irina kotcherova nino salukvadze & france martine guepin evelyne manchon corine serra-tosio & albania diana mata emanuela delilaj edlira shyti \\
5 & 1990 & moscow & soviet union yauheniya haluza marina logvinenko nino salukvadze & sweden kerstin bodin britt marie ellis chris kajd & people's republic of china haiying liu duihong li meifang qian \\
6 & 1994 & milan & people's republic of china xiaoping fan duihong li lina wang & korea soon hee boo sun bok lee jung hee park & belarus zhanna shitik yauheniya haluza yuliya siniak \\
7 & 1998 & barcelona & people's republic of china yeqing cai luna tao yi sun & korea eun kyung shin soon hee boo joo hyung seo & mongolia munkhbayar dorjsuren oyun davaajantsan gundegmaa otryad \\
8 & 2002 & lahti & people's republic of china luna tao ying chen duihong li & russia irina dolgatcheva galina beliaeva svetlana smirnova & united states of america elizabeth callahan rebecca snyder sandra uptagrafft \\
9 & 2006 & zagreb & people's republic of china ying chen fengji fei duihong li & belarus liudmila chabatar zhanna shapialevich yauheniya haluza & germany munkhbayar dorjsuren stefanie thurmann claudia verdicchio \\
10 & 2010 & munich & russia yulia alipova kira klimova galina beliaeva & serbia zorana arunovic jasna sekaric jelena arunovic & czech republic lenka maruskova michaela musilova petra hykova \\
11 & 2014 & granada & none & none & none \\
12 & 2018 & changwon & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 2006 \\
\bottomrule
\end{tabular}
| select year where place = 'zagreb' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>place</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1970</td>
<td>phoenix</td>
<td>united states of america sally carroll lucile chambliss barbara hile</td>
<td>soviet union nadezda ibragimova nina rasskazova nina stoliarova</td>
<td>federal republic of germany ortrud feickert karin fitzner ruth kasten</td>
</tr>
<tr>
<th>1</th>
<td>1974</td>
<td>thun</td>
<td>soviet union galina zarikova zinaida simonian nina stoliarova</td>
<td>czechoslovakia tereza bohinska bedriska hykova katarina pastorova</td>
<td>australia judith harrison enid newton gloria vause</td>
</tr>
<tr>
<th>2</th>
<td>1978</td>
<td>seoul</td>
<td>denmark kirsten broge bonnie bruun aase havsteen</td>
<td>australia julie aitken patricia dench lynne uden</td>
<td>united states of america sally carroll kimberly dyer ruby fox</td>
</tr>
<tr>
<th>3</th>
<td>1982</td>
<td>caracas</td>
<td>soviet union marina dobrantcheva inna rose auksne treinite</td>
<td>hungary palma balogh marta kotroczo gabriella kanyai</td>
<td>people's republic of china jianmin gao zhifang wen cui qing yang</td>
</tr>
<tr>
<th>4</th>
<td>1986</td>
<td>suhl</td>
<td>soviet union marina dobrantcheva irina kotcherova nino salukvadze</td>
<td>france martine guepin evelyne manchon corine serra-tosio</td>
<td>albania diana mata emanuela delilaj edlira shyti</td>
</tr>
<tr>
<th>5</th>
<td>1990</td>
<td>moscow</td>
<td>soviet union yauheniya haluza marina logvinenko nino salukvadze</td>
<td>sweden kerstin bodin britt marie ellis chris kajd</td>
<td>people's republic of china haiying liu duihong li meifang qian</td>
</tr>
<tr>
<th>6</th>
<td>1994</td>
<td>milan</td>
<td>people's republic of china xiaoping fan duihong li lina wang</td>
<td>korea soon hee boo sun bok lee jung hee park</td>
<td>belarus zhanna shitik yauheniya haluza yuliya siniak</td>
</tr>
<tr>
<th>7</th>
<td>1998</td>
<td>barcelona</td>
<td>people's republic of china yeqing cai luna tao yi sun</td>
<td>korea eun kyung shin soon hee boo joo hyung seo</td>
<td>mongolia munkhbayar dorjsuren oyun davaajantsan gundegmaa otryad</td>
</tr>
<tr>
<th>8</th>
<td>2002</td>
<td>lahti</td>
<td>people's republic of china luna tao ying chen duihong li</td>
<td>russia irina dolgatcheva galina beliaeva svetlana smirnova</td>
<td>united states of america elizabeth callahan rebecca snyder sandra uptagrafft</td>
</tr>
<tr>
<th>9</th>
<td>2006</td>
<td>zagreb</td>
<td>people's republic of china ying chen fengji fei duihong li</td>
<td>belarus liudmila chabatar zhanna shapialevich yauheniya haluza</td>
<td>germany munkhbayar dorjsuren stefanie thurmann claudia verdicchio</td>
</tr>
<tr>
<th>10</th>
<td>2010</td>
<td>munich</td>
<td>russia yulia alipova kira klimova galina beliaeva</td>
<td>serbia zorana arunovic jasna sekaric jelena arunovic</td>
<td>czech republic lenka maruskova michaela musilova petra hykova</td>
</tr>
<tr>
<th>11</th>
<td>2014</td>
<td>granada</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>2018</td>
<td>changwon</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>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2006</td>
</tr>
</tbody>
</table> | select year where place = 'zagreb' <table_name> : table | | year | place | gold | silver | bronze |
|---:|-------:|:----------|:---------------------------------------------------------------------|:------------------------------------------------------------------|:-----------------------------------------------------------------------------|
| 0 | 1970 | phoenix | united states of america sally carroll lucile chambliss barbara hile | soviet union nadezda ibragimova nina rasskazova nina stoliarova | federal republic of germany ortrud feickert karin fitzner ruth kasten |
| 1 | 1974 | thun | soviet union galina zarikova zinaida simonian nina stoliarova | czechoslovakia tereza bohinska bedriska hykova katarina pastorova | australia judith harrison enid newton gloria vause |
| 2 | 1978 | seoul | denmark kirsten broge bonnie bruun aase havsteen | australia julie aitken patricia dench lynne uden | united states of america sally carroll kimberly dyer ruby fox |
| 3 | 1982 | caracas | soviet union marina dobrantcheva inna rose auksne treinite | hungary palma balogh marta kotroczo gabriella kanyai | people's republic of china jianmin gao zhifang wen cui qing yang |
| 4 | 1986 | suhl | soviet union marina dobrantcheva irina kotcherova nino salukvadze | france martine guepin evelyne manchon corine serra-tosio | albania diana mata emanuela delilaj edlira shyti |
| 5 | 1990 | moscow | soviet union yauheniya haluza marina logvinenko nino salukvadze | sweden kerstin bodin britt marie ellis chris kajd | people's republic of china haiying liu duihong li meifang qian |
| 6 | 1994 | milan | people's republic of china xiaoping fan duihong li lina wang | korea soon hee boo sun bok lee jung hee park | belarus zhanna shitik yauheniya haluza yuliya siniak |
| 7 | 1998 | barcelona | people's republic of china yeqing cai luna tao yi sun | korea eun kyung shin soon hee boo joo hyung seo | mongolia munkhbayar dorjsuren oyun davaajantsan gundegmaa otryad |
| 8 | 2002 | lahti | people's republic of china luna tao ying chen duihong li | russia irina dolgatcheva galina beliaeva svetlana smirnova | united states of america elizabeth callahan rebecca snyder sandra uptagrafft |
| 9 | 2006 | zagreb | people's republic of china ying chen fengji fei duihong li | belarus liudmila chabatar zhanna shapialevich yauheniya haluza | germany munkhbayar dorjsuren stefanie thurmann claudia verdicchio |
| 10 | 2010 | munich | russia yulia alipova kira klimova galina beliaeva | serbia zorana arunovic jasna sekaric jelena arunovic | czech republic lenka maruskova michaela musilova petra hykova |
| 11 | 2014 | granada | none | none | none |
| 12 | 2018 | changwon | none | none | none | | | | year |
|---:|-------:|
| 0 | 2006 | | [
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select original airing season finale where original airing season finale = 'may 17, 2007' 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 : original airing season finale row 1 : may 17, 2007 | select original airing season finale where original airing season finale = 'may 17, 2007' <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
& original airing season finale \\
\midrule
0 & may 17, 2007 \\
\bottomrule
\end{tabular}
| select original airing season finale where original airing season finale = 'may 17, 2007' <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>original airing season finale</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>may 17, 2007</td>
</tr>
</tbody>
</table> | select original airing season finale where original airing season finale = 'may 17, 2007' <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 | | | | original airing season finale |
|---:|:--------------------------------|
| 0 | may 17, 2007 | | [
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select count ( school name ) where establishment < 2012 col : school name | city | grades | establishment | charter row 1 : aliamanu intermediate school | honolulu | 7-8 | 1958 | none row 2 : anuenue school | honolulu | k-12 | 1958 | charter row 3 : central middle school | honolulu | 6-8 | 1926 | none row 4 : dole middle school | honolulu | 6-8 | 1955 | none row 5 : halau ku mana ncpcs | honolulu | 6-12 | 2000 | charter row 6 : jarrett middle school | honolulu | 6-8 | 1955 | none row 7 : kaimuki middle school | honolulu | 6-8 | 1939 | none row 8 : kalakaua middle school | honolulu | 6-8 | 1928 | none row 9 : kawananakoa middle school | honolulu | 6-8 | 1927 | none row 10 : moanalua middle school | honolulu | 7-8 | 1967 | none row 11 : niu valley middle school | honolulu | 6-8 | 1955 | none row 12 : stevenson middle school | honolulu | 6-8 | 1937 | none row 13 : washington middle school | honolulu | 6-8 | 1854 | none | col : count ( "school name" ) row 1 : 13 | select count ( school name ) where establishment < 2012 <table_name> : table \begin{tabular}{llllll}
\toprule
& school name & city & grades & establishment & charter \\
\midrule
0 & aliamanu intermediate school & honolulu & 7-8 & 1958 & none \\
1 & anuenue school & honolulu & k-12 & 1958 & charter \\
2 & central middle school & honolulu & 6-8 & 1926 & none \\
3 & dole middle school & honolulu & 6-8 & 1955 & none \\
4 & halau ku mana ncpcs & honolulu & 6-12 & 2000 & charter \\
5 & jarrett middle school & honolulu & 6-8 & 1955 & none \\
6 & kaimuki middle school & honolulu & 6-8 & 1939 & none \\
7 & kalakaua middle school & honolulu & 6-8 & 1928 & none \\
8 & kawananakoa middle school & honolulu & 6-8 & 1927 & none \\
9 & moanalua middle school & honolulu & 7-8 & 1967 & none \\
10 & niu valley middle school & honolulu & 6-8 & 1955 & none \\
11 & stevenson middle school & honolulu & 6-8 & 1937 & none \\
12 & washington middle school & honolulu & 6-8 & 1854 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "school name" ) \\
\midrule
0 & 13 \\
\bottomrule
\end{tabular}
| select count ( school name ) where establishment < 2012 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>school name</th>
<th>city</th>
<th>grades</th>
<th>establishment</th>
<th>charter</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>aliamanu intermediate school</td>
<td>honolulu</td>
<td>7-8</td>
<td>1958</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>anuenue school</td>
<td>honolulu</td>
<td>k-12</td>
<td>1958</td>
<td>charter</td>
</tr>
<tr>
<th>2</th>
<td>central middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1926</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>dole middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1955</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>halau ku mana ncpcs</td>
<td>honolulu</td>
<td>6-12</td>
<td>2000</td>
<td>charter</td>
</tr>
<tr>
<th>5</th>
<td>jarrett middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1955</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>kaimuki middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1939</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>kalakaua middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1928</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>kawananakoa middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1927</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>moanalua middle school</td>
<td>honolulu</td>
<td>7-8</td>
<td>1967</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>niu valley middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1955</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>stevenson middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1937</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>washington middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1854</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "school name" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>13</td>
</tr>
</tbody>
</table> | select count ( school name ) where establishment < 2012 <table_name> : table | | school name | city | grades | establishment | charter |
|---:|:-----------------------------|:---------|:---------|----------------:|:----------|
| 0 | aliamanu intermediate school | honolulu | 7-8 | 1958 | none |
| 1 | anuenue school | honolulu | k-12 | 1958 | charter |
| 2 | central middle school | honolulu | 6-8 | 1926 | none |
| 3 | dole middle school | honolulu | 6-8 | 1955 | none |
| 4 | halau ku mana ncpcs | honolulu | 6-12 | 2000 | charter |
| 5 | jarrett middle school | honolulu | 6-8 | 1955 | none |
| 6 | kaimuki middle school | honolulu | 6-8 | 1939 | none |
| 7 | kalakaua middle school | honolulu | 6-8 | 1928 | none |
| 8 | kawananakoa middle school | honolulu | 6-8 | 1927 | none |
| 9 | moanalua middle school | honolulu | 7-8 | 1967 | none |
| 10 | niu valley middle school | honolulu | 6-8 | 1955 | none |
| 11 | stevenson middle school | honolulu | 6-8 | 1937 | none |
| 12 | washington middle school | honolulu | 6-8 | 1854 | none | | | | count ( "school name" ) |
|---:|--------------------------:|
| 0 | 13 | | [
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select count ( artist ) where month = 'october' col : month | song | artist | aggregate points | total downloads | year-end chart row 1 : january | "lovey-dovey" | t-ara | 142,691,767 | 1,903,727 | 7 row 2 : february | "blue" | big bang | 102,380,663 | 1,351,429 | 10 row 3 : march | "fantastic baby" | big bang | 105,296,671 | 1,229,518 | 5 row 4 : april | "cherry blossom ending" | busker busker | 169,546,447 | 1,570,146 | 2 row 5 : may | "twinkle" | girls' generation-tts | 119,415,981 | 997,122 | 11 row 6 : june | "like this" | wonder girls | 138,592,996 | 1,444,339 | 18 row 7 : july | "i love you" | 2ne1 | 151,627,608 | 1,522,263 | 6 row 8 : august | "gangnam style" | psy | 150,855,485 | 1,280,050 | 1 row 9 : september | "all for you" | jung eunji & seo in guk | 113,858,049 | 1,037,911 | 8 row 10 : october | "bloom" | gain | 115,479,048 | 1,182,829 | 42 row 11 : november | "1, 2, 3, 4" | lee hi | 132,391,547 | 1,210,297 | 23 row 12 : december | "return" | lee seung gi | 110,364,099 | 896,196 | 37 | col : count ( "artist" ) row 1 : 1 | select count ( artist ) where month = 'october' <table_name> : table \begin{tabular}{lllllll}
\toprule
& month & song & artist & aggregate points & total downloads & year-end chart \\
\midrule
0 & january & "lovey-dovey" & t-ara & 142,691,767 & 1,903,727 & 7 \\
1 & february & "blue" & big bang & 102,380,663 & 1,351,429 & 10 \\
2 & march & "fantastic baby" & big bang & 105,296,671 & 1,229,518 & 5 \\
3 & april & "cherry blossom ending" & busker busker & 169,546,447 & 1,570,146 & 2 \\
4 & may & "twinkle" & girls' generation-tts & 119,415,981 & 997,122 & 11 \\
5 & june & "like this" & wonder girls & 138,592,996 & 1,444,339 & 18 \\
6 & july & "i love you" & 2ne1 & 151,627,608 & 1,522,263 & 6 \\
7 & august & "gangnam style" & psy & 150,855,485 & 1,280,050 & 1 \\
8 & september & "all for you" & jung eunji & seo in guk & 113,858,049 & 1,037,911 & 8 \\
9 & october & "bloom" & gain & 115,479,048 & 1,182,829 & 42 \\
10 & november & "1, 2, 3, 4" & lee hi & 132,391,547 & 1,210,297 & 23 \\
11 & december & "return" & lee seung gi & 110,364,099 & 896,196 & 37 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "artist" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( artist ) where month = 'october' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>month</th>
<th>song</th>
<th>artist</th>
<th>aggregate points</th>
<th>total downloads</th>
<th>year-end chart</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>january</td>
<td>"lovey-dovey"</td>
<td>t-ara</td>
<td>142,691,767</td>
<td>1,903,727</td>
<td>7</td>
</tr>
<tr>
<th>1</th>
<td>february</td>
<td>"blue"</td>
<td>big bang</td>
<td>102,380,663</td>
<td>1,351,429</td>
<td>10</td>
</tr>
<tr>
<th>2</th>
<td>march</td>
<td>"fantastic baby"</td>
<td>big bang</td>
<td>105,296,671</td>
<td>1,229,518</td>
<td>5</td>
</tr>
<tr>
<th>3</th>
<td>april</td>
<td>"cherry blossom ending"</td>
<td>busker busker</td>
<td>169,546,447</td>
<td>1,570,146</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>may</td>
<td>"twinkle"</td>
<td>girls' generation-tts</td>
<td>119,415,981</td>
<td>997,122</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>june</td>
<td>"like this"</td>
<td>wonder girls</td>
<td>138,592,996</td>
<td>1,444,339</td>
<td>18</td>
</tr>
<tr>
<th>6</th>
<td>july</td>
<td>"i love you"</td>
<td>2ne1</td>
<td>151,627,608</td>
<td>1,522,263</td>
<td>6</td>
</tr>
<tr>
<th>7</th>
<td>august</td>
<td>"gangnam style"</td>
<td>psy</td>
<td>150,855,485</td>
<td>1,280,050</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>september</td>
<td>"all for you"</td>
<td>jung eunji & seo in guk</td>
<td>113,858,049</td>
<td>1,037,911</td>
<td>8</td>
</tr>
<tr>
<th>9</th>
<td>october</td>
<td>"bloom"</td>
<td>gain</td>
<td>115,479,048</td>
<td>1,182,829</td>
<td>42</td>
</tr>
<tr>
<th>10</th>
<td>november</td>
<td>"1, 2, 3, 4"</td>
<td>lee hi</td>
<td>132,391,547</td>
<td>1,210,297</td>
<td>23</td>
</tr>
<tr>
<th>11</th>
<td>december</td>
<td>"return"</td>
<td>lee seung gi</td>
<td>110,364,099</td>
<td>896,196</td>
<td>37</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "artist" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( artist ) where month = 'october' <table_name> : table | | month | song | artist | aggregate points | total downloads | year-end chart |
|---:|:----------|:------------------------|:------------------------|:-------------------|:------------------|-----------------:|
| 0 | january | "lovey-dovey" | t-ara | 142,691,767 | 1,903,727 | 7 |
| 1 | february | "blue" | big bang | 102,380,663 | 1,351,429 | 10 |
| 2 | march | "fantastic baby" | big bang | 105,296,671 | 1,229,518 | 5 |
| 3 | april | "cherry blossom ending" | busker busker | 169,546,447 | 1,570,146 | 2 |
| 4 | may | "twinkle" | girls' generation-tts | 119,415,981 | 997,122 | 11 |
| 5 | june | "like this" | wonder girls | 138,592,996 | 1,444,339 | 18 |
| 6 | july | "i love you" | 2ne1 | 151,627,608 | 1,522,263 | 6 |
| 7 | august | "gangnam style" | psy | 150,855,485 | 1,280,050 | 1 |
| 8 | september | "all for you" | jung eunji & seo in guk | 113,858,049 | 1,037,911 | 8 |
| 9 | october | "bloom" | gain | 115,479,048 | 1,182,829 | 42 |
| 10 | november | "1, 2, 3, 4" | lee hi | 132,391,547 | 1,210,297 | 23 |
| 11 | december | "return" | lee seung gi | 110,364,099 | 896,196 | 37 | | | | count ( "artist" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select count ( country ) where team = 'shandong luneng' col : season | team | country | division | apps | goals row 1 : 2003 | shandong luneng | china | 1 | 4 | 0 row 2 : 2004 | shandong luneng | china | 1 | 0 | 0 row 3 : 2005 | shandong luneng | china | 1 | 0 | 0 row 4 : 2006 | chengdu wuniu | china | 2 | 1 | 0 row 5 : 2007 | shandong luneng | china | 1 | 0 | 0 row 6 : 2008 | jiangsu sainty | china | 2 | 24 | 0 row 7 : 2009 | jiangsu sainty | china | 1 | 15 | 0 row 8 : 2010 | jiangsu sainty | china | 1 | 17 | 0 row 9 : 2011 | jiangsu sainty | china | 1 | 9 | 0 row 10 : 2012 | jiangsu sainty | china | 1 | 0 | 0 row 11 : 2013 | jiangsu sainty | china | 1 | 11 | 0 | col : count ( "country" ) row 1 : 4 | select count ( country ) where team = 'shandong luneng' <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & team & country & division & apps & goals \\
\midrule
0 & 2003 & shandong luneng & china & 1 & 4 & 0 \\
1 & 2004 & shandong luneng & china & 1 & 0 & 0 \\
2 & 2005 & shandong luneng & china & 1 & 0 & 0 \\
3 & 2006 & chengdu wuniu & china & 2 & 1 & 0 \\
4 & 2007 & shandong luneng & china & 1 & 0 & 0 \\
5 & 2008 & jiangsu sainty & china & 2 & 24 & 0 \\
6 & 2009 & jiangsu sainty & china & 1 & 15 & 0 \\
7 & 2010 & jiangsu sainty & china & 1 & 17 & 0 \\
8 & 2011 & jiangsu sainty & china & 1 & 9 & 0 \\
9 & 2012 & jiangsu sainty & china & 1 & 0 & 0 \\
10 & 2013 & jiangsu sainty & china & 1 & 11 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "country" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( country ) where team = 'shandong luneng' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>team</th>
<th>country</th>
<th>division</th>
<th>apps</th>
<th>goals</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2003</td>
<td>shandong luneng</td>
<td>china</td>
<td>1</td>
<td>4</td>
<td>0</td>
</tr>
<tr>
<th>1</th>
<td>2004</td>
<td>shandong luneng</td>
<td>china</td>
<td>1</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>shandong luneng</td>
<td>china</td>
<td>1</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>2006</td>
<td>chengdu wuniu</td>
<td>china</td>
<td>2</td>
<td>1</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>2007</td>
<td>shandong luneng</td>
<td>china</td>
<td>1</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>jiangsu sainty</td>
<td>china</td>
<td>2</td>
<td>24</td>
<td>0</td>
</tr>
<tr>
<th>6</th>
<td>2009</td>
<td>jiangsu sainty</td>
<td>china</td>
<td>1</td>
<td>15</td>
<td>0</td>
</tr>
<tr>
<th>7</th>
<td>2010</td>
<td>jiangsu sainty</td>
<td>china</td>
<td>1</td>
<td>17</td>
<td>0</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>jiangsu sainty</td>
<td>china</td>
<td>1</td>
<td>9</td>
<td>0</td>
</tr>
<tr>
<th>9</th>
<td>2012</td>
<td>jiangsu sainty</td>
<td>china</td>
<td>1</td>
<td>0</td>
<td>0</td>
</tr>
<tr>
<th>10</th>
<td>2013</td>
<td>jiangsu sainty</td>
<td>china</td>
<td>1</td>
<td>11</td>
<td>0</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 count ( country ) where team = 'shandong luneng' <table_name> : table | | season | team | country | division | apps | goals |
|---:|---------:|:----------------|:----------|-----------:|-------:|--------:|
| 0 | 2003 | shandong luneng | china | 1 | 4 | 0 |
| 1 | 2004 | shandong luneng | china | 1 | 0 | 0 |
| 2 | 2005 | shandong luneng | china | 1 | 0 | 0 |
| 3 | 2006 | chengdu wuniu | china | 2 | 1 | 0 |
| 4 | 2007 | shandong luneng | china | 1 | 0 | 0 |
| 5 | 2008 | jiangsu sainty | china | 2 | 24 | 0 |
| 6 | 2009 | jiangsu sainty | china | 1 | 15 | 0 |
| 7 | 2010 | jiangsu sainty | china | 1 | 17 | 0 |
| 8 | 2011 | jiangsu sainty | china | 1 | 9 | 0 |
| 9 | 2012 | jiangsu sainty | china | 1 | 0 | 0 |
| 10 | 2013 | jiangsu sainty | china | 1 | 11 | 0 | | | | count ( "country" ) |
|---:|----------------------:|
| 0 | 4 | | [
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select joining year where women's team = 'korea dpr' col : association | joining year | men's team | women's team | league row 1 : china pr | 2002 | china | china | chinese super league row 2 : guam | 2002 | guam | guam | guam league row 3 : hong kong | 2002 | hong kong | hong kong | hong kong first division league row 4 : japan | 2002 | japan | japan | j. league row 5 : korea dpr | 2002 | korea dpr | korea dpr | dpr korea league row 6 : korea republic | 2002 | korea republic | korea republic | k-league row 7 : macau | 2002 | macau | macau | campeonato da 1a divisao do futebol row 8 : mongolia | 2002 | mongolia | mongolia | mongolia premier league row 9 : northern mariana islands | 2008 | northern mariana islands | northern mariana islands | northern mariana championship row 10 : chinese taipei | 2002 | chinese taipei | chinese taipei | intercity football league | col : joining year row 1 : 2002 | select joining year where women's team = 'korea dpr' <table_name> : table \begin{tabular}{llllll}
\toprule
& association & joining year & men's team & women's team & league \\
\midrule
0 & china pr & 2002 & china & china & chinese super league \\
1 & guam & 2002 & guam & guam & guam league \\
2 & hong kong & 2002 & hong kong & hong kong & hong kong first division league \\
3 & japan & 2002 & japan & japan & j. league \\
4 & korea dpr & 2002 & korea dpr & korea dpr & dpr korea league \\
5 & korea republic & 2002 & korea republic & korea republic & k-league \\
6 & macau & 2002 & macau & macau & campeonato da 1a divisao do futebol \\
7 & mongolia & 2002 & mongolia & mongolia & mongolia premier league \\
8 & northern mariana islands & 2008 & northern mariana islands & northern mariana islands & northern mariana championship \\
9 & chinese taipei & 2002 & chinese taipei & chinese taipei & intercity football league \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& joining year \\
\midrule
0 & 2002 \\
\bottomrule
\end{tabular}
| select joining year where women's team = 'korea dpr' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>association</th>
<th>joining year</th>
<th>men's team</th>
<th>women's team</th>
<th>league</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>china pr</td>
<td>2002</td>
<td>china</td>
<td>china</td>
<td>chinese super league</td>
</tr>
<tr>
<th>1</th>
<td>guam</td>
<td>2002</td>
<td>guam</td>
<td>guam</td>
<td>guam league</td>
</tr>
<tr>
<th>2</th>
<td>hong kong</td>
<td>2002</td>
<td>hong kong</td>
<td>hong kong</td>
<td>hong kong first division league</td>
</tr>
<tr>
<th>3</th>
<td>japan</td>
<td>2002</td>
<td>japan</td>
<td>japan</td>
<td>j. league</td>
</tr>
<tr>
<th>4</th>
<td>korea dpr</td>
<td>2002</td>
<td>korea dpr</td>
<td>korea dpr</td>
<td>dpr korea league</td>
</tr>
<tr>
<th>5</th>
<td>korea republic</td>
<td>2002</td>
<td>korea republic</td>
<td>korea republic</td>
<td>k-league</td>
</tr>
<tr>
<th>6</th>
<td>macau</td>
<td>2002</td>
<td>macau</td>
<td>macau</td>
<td>campeonato da 1a divisao do futebol</td>
</tr>
<tr>
<th>7</th>
<td>mongolia</td>
<td>2002</td>
<td>mongolia</td>
<td>mongolia</td>
<td>mongolia premier league</td>
</tr>
<tr>
<th>8</th>
<td>northern mariana islands</td>
<td>2008</td>
<td>northern mariana islands</td>
<td>northern mariana islands</td>
<td>northern mariana championship</td>
</tr>
<tr>
<th>9</th>
<td>chinese taipei</td>
<td>2002</td>
<td>chinese taipei</td>
<td>chinese taipei</td>
<td>intercity football league</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>joining year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2002</td>
</tr>
</tbody>
</table> | select joining year where women's team = 'korea dpr' <table_name> : table | | association | joining year | men's team | women's team | league |
|---:|:-------------------------|---------------:|:-------------------------|:-------------------------|:------------------------------------|
| 0 | china pr | 2002 | china | china | chinese super league |
| 1 | guam | 2002 | guam | guam | guam league |
| 2 | hong kong | 2002 | hong kong | hong kong | hong kong first division league |
| 3 | japan | 2002 | japan | japan | j. league |
| 4 | korea dpr | 2002 | korea dpr | korea dpr | dpr korea league |
| 5 | korea republic | 2002 | korea republic | korea republic | k-league |
| 6 | macau | 2002 | macau | macau | campeonato da 1a divisao do futebol |
| 7 | mongolia | 2002 | mongolia | mongolia | mongolia premier league |
| 8 | northern mariana islands | 2008 | northern mariana islands | northern mariana islands | northern mariana championship |
| 9 | chinese taipei | 2002 | chinese taipei | chinese taipei | intercity football league | | | | joining year |
|---:|---------------:|
| 0 | 2002 | | [
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select count ( * ) where stadium = 248 col : team | stadium | capacity | city/area row 1 : bradford bulls (2014 season) | provident stadium | 27000 | bradford, west yorkshire row 2 : castleford tigers (2014 season) | the wish communications stadium | 11750 | castleford, west yorkshire row 3 : catalans dragons (2014 season) | stade gilbert brutus | 14000 | perpignan, pyrenees-orientales, france row 4 : huddersfield giants (2014 season) | john smith's stadium | 24544 | huddersfield, west yorkshire row 5 : hull (2014 season) | kingston communications stadium | 25404 | kingston upon hull, east riding of yorkshire row 6 : hull kingston rovers (2014 season) | ms3 craven park | 9471 | kingston upon hull, east riding of yorkshire row 7 : leeds rhinos (2014 season) | headingley carnegie stadium | 22250 | leeds, west yorkshire row 8 : london broncos (2014 season) | twickenham stoop | 12700 | twickenham, london row 9 : salford city reds (2014 season) | salford city stadium | 12000 | salford, greater manchester row 10 : st helens rlfc (2014 season) | langtree park | 18000 | st helens, merseyside row 11 : wakefield trinity wildcats (2014 season) | rapid solicitors stadium | 11000 | wakefield, west yorkshire row 12 : warrington wolves (2014 season) | halliwell jones stadium | 15500 | warrington, cheshire row 13 : widnes vikings (2014 season) | the select security stadium | 13500 | widnes, cheshire, england row 14 : wigan warriors (2014 season) | dw stadium | 25138 | wigan, greater manchester | col : count ( "*" ) row 1 : 0 | select count ( * ) where stadium = 248 <table_name> : table \begin{tabular}{lllll}
\toprule
& team & stadium & capacity & city/area \\
\midrule
0 & bradford bulls (2014 season) & provident stadium & 27000 & bradford, west yorkshire \\
1 & castleford tigers (2014 season) & the wish communications stadium & 11750 & castleford, west yorkshire \\
2 & catalans dragons (2014 season) & stade gilbert brutus & 14000 & perpignan, pyrenees-orientales, france \\
3 & huddersfield giants (2014 season) & john smith's stadium & 24544 & huddersfield, west yorkshire \\
4 & hull (2014 season) & kingston communications stadium & 25404 & kingston upon hull, east riding of yorkshire \\
5 & hull kingston rovers (2014 season) & ms3 craven park & 9471 & kingston upon hull, east riding of yorkshire \\
6 & leeds rhinos (2014 season) & headingley carnegie stadium & 22250 & leeds, west yorkshire \\
7 & london broncos (2014 season) & twickenham stoop & 12700 & twickenham, london \\
8 & salford city reds (2014 season) & salford city stadium & 12000 & salford, greater manchester \\
9 & st helens rlfc (2014 season) & langtree park & 18000 & st helens, merseyside \\
10 & wakefield trinity wildcats (2014 season) & rapid solicitors stadium & 11000 & wakefield, west yorkshire \\
11 & warrington wolves (2014 season) & halliwell jones stadium & 15500 & warrington, cheshire \\
12 & widnes vikings (2014 season) & the select security stadium & 13500 & widnes, cheshire, england \\
13 & wigan warriors (2014 season) & dw stadium & 25138 & wigan, greater manchester \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where stadium = 248 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>team</th>
<th>stadium</th>
<th>capacity</th>
<th>city/area</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>bradford bulls (2014 season)</td>
<td>provident stadium</td>
<td>27000</td>
<td>bradford, west yorkshire</td>
</tr>
<tr>
<th>1</th>
<td>castleford tigers (2014 season)</td>
<td>the wish communications stadium</td>
<td>11750</td>
<td>castleford, west yorkshire</td>
</tr>
<tr>
<th>2</th>
<td>catalans dragons (2014 season)</td>
<td>stade gilbert brutus</td>
<td>14000</td>
<td>perpignan, pyrenees-orientales, france</td>
</tr>
<tr>
<th>3</th>
<td>huddersfield giants (2014 season)</td>
<td>john smith's stadium</td>
<td>24544</td>
<td>huddersfield, west yorkshire</td>
</tr>
<tr>
<th>4</th>
<td>hull (2014 season)</td>
<td>kingston communications stadium</td>
<td>25404</td>
<td>kingston upon hull, east riding of yorkshire</td>
</tr>
<tr>
<th>5</th>
<td>hull kingston rovers (2014 season)</td>
<td>ms3 craven park</td>
<td>9471</td>
<td>kingston upon hull, east riding of yorkshire</td>
</tr>
<tr>
<th>6</th>
<td>leeds rhinos (2014 season)</td>
<td>headingley carnegie stadium</td>
<td>22250</td>
<td>leeds, west yorkshire</td>
</tr>
<tr>
<th>7</th>
<td>london broncos (2014 season)</td>
<td>twickenham stoop</td>
<td>12700</td>
<td>twickenham, london</td>
</tr>
<tr>
<th>8</th>
<td>salford city reds (2014 season)</td>
<td>salford city stadium</td>
<td>12000</td>
<td>salford, greater manchester</td>
</tr>
<tr>
<th>9</th>
<td>st helens rlfc (2014 season)</td>
<td>langtree park</td>
<td>18000</td>
<td>st helens, merseyside</td>
</tr>
<tr>
<th>10</th>
<td>wakefield trinity wildcats (2014 season)</td>
<td>rapid solicitors stadium</td>
<td>11000</td>
<td>wakefield, west yorkshire</td>
</tr>
<tr>
<th>11</th>
<td>warrington wolves (2014 season)</td>
<td>halliwell jones stadium</td>
<td>15500</td>
<td>warrington, cheshire</td>
</tr>
<tr>
<th>12</th>
<td>widnes vikings (2014 season)</td>
<td>the select security stadium</td>
<td>13500</td>
<td>widnes, cheshire, england</td>
</tr>
<tr>
<th>13</th>
<td>wigan warriors (2014 season)</td>
<td>dw stadium</td>
<td>25138</td>
<td>wigan, greater manchester</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 stadium = 248 <table_name> : table | | team | stadium | capacity | city/area |
|---:|:-----------------------------------------|:--------------------------------|-----------:|:---------------------------------------------|
| 0 | bradford bulls (2014 season) | provident stadium | 27000 | bradford, west yorkshire |
| 1 | castleford tigers (2014 season) | the wish communications stadium | 11750 | castleford, west yorkshire |
| 2 | catalans dragons (2014 season) | stade gilbert brutus | 14000 | perpignan, pyrenees-orientales, france |
| 3 | huddersfield giants (2014 season) | john smith's stadium | 24544 | huddersfield, west yorkshire |
| 4 | hull (2014 season) | kingston communications stadium | 25404 | kingston upon hull, east riding of yorkshire |
| 5 | hull kingston rovers (2014 season) | ms3 craven park | 9471 | kingston upon hull, east riding of yorkshire |
| 6 | leeds rhinos (2014 season) | headingley carnegie stadium | 22250 | leeds, west yorkshire |
| 7 | london broncos (2014 season) | twickenham stoop | 12700 | twickenham, london |
| 8 | salford city reds (2014 season) | salford city stadium | 12000 | salford, greater manchester |
| 9 | st helens rlfc (2014 season) | langtree park | 18000 | st helens, merseyside |
| 10 | wakefield trinity wildcats (2014 season) | rapid solicitors stadium | 11000 | wakefield, west yorkshire |
| 11 | warrington wolves (2014 season) | halliwell jones stadium | 15500 | warrington, cheshire |
| 12 | widnes vikings (2014 season) | the select security stadium | 13500 | widnes, cheshire, england |
| 13 | wigan warriors (2014 season) | dw stadium | 25138 | wigan, greater manchester | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select year where venue = 'johannesburg, south africa' col : year | competition | venue | position | notes row 1 : 1994 | commonwealth games | victoria, canada | 6th | 400 m h row 2 : 1995 | world championships | gothenburg, sweden | 6th | 400 m h row 3 : 1997 | world championships | athens, greece | 7th | 4x400 m relay row 4 : 1998 | commonwealth games | kuala lumpur, malaysia | 3rd | 400 m h row 5 : 1998 | african championships | dakar, senegal | 2nd | 400 m h row 6 : 1999 | all-africa games | johannesburg, south africa | 2nd | 400 m h | col : year row 1 : 1999 | select year where venue = 'johannesburg, south africa' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & competition & venue & position & notes \\
\midrule
0 & 1994 & commonwealth games & victoria, canada & 6th & 400 m h \\
1 & 1995 & world championships & gothenburg, sweden & 6th & 400 m h \\
2 & 1997 & world championships & athens, greece & 7th & 4x400 m relay \\
3 & 1998 & commonwealth games & kuala lumpur, malaysia & 3rd & 400 m h \\
4 & 1998 & african championships & dakar, senegal & 2nd & 400 m h \\
5 & 1999 & all-africa games & johannesburg, south africa & 2nd & 400 m h \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1999 \\
\bottomrule
\end{tabular}
| select year where venue = 'johannesburg, south africa' <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>1994</td>
<td>commonwealth games</td>
<td>victoria, canada</td>
<td>6th</td>
<td>400 m h</td>
</tr>
<tr>
<th>1</th>
<td>1995</td>
<td>world championships</td>
<td>gothenburg, sweden</td>
<td>6th</td>
<td>400 m h</td>
</tr>
<tr>
<th>2</th>
<td>1997</td>
<td>world championships</td>
<td>athens, greece</td>
<td>7th</td>
<td>4x400 m relay</td>
</tr>
<tr>
<th>3</th>
<td>1998</td>
<td>commonwealth games</td>
<td>kuala lumpur, malaysia</td>
<td>3rd</td>
<td>400 m h</td>
</tr>
<tr>
<th>4</th>
<td>1998</td>
<td>african championships</td>
<td>dakar, senegal</td>
<td>2nd</td>
<td>400 m h</td>
</tr>
<tr>
<th>5</th>
<td>1999</td>
<td>all-africa games</td>
<td>johannesburg, south africa</td>
<td>2nd</td>
<td>400 m h</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>1999</td>
</tr>
</tbody>
</table> | select year where venue = 'johannesburg, south africa' <table_name> : table | | year | competition | venue | position | notes |
|---:|-------:|:----------------------|:---------------------------|:-----------|:--------------|
| 0 | 1994 | commonwealth games | victoria, canada | 6th | 400 m h |
| 1 | 1995 | world championships | gothenburg, sweden | 6th | 400 m h |
| 2 | 1997 | world championships | athens, greece | 7th | 4x400 m relay |
| 3 | 1998 | commonwealth games | kuala lumpur, malaysia | 3rd | 400 m h |
| 4 | 1998 | african championships | dakar, senegal | 2nd | 400 m h |
| 5 | 1999 | all-africa games | johannesburg, south africa | 2nd | 400 m h | | | | year |
|---:|-------:|
| 0 | 1999 | | [
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select count ( state ) where state = 'virginia' col : state | passed | referendum | vote row 1 : s. carolina | december 20, 1860 | none | none row 2 : mississippi | january 9, 1861 | none | none row 3 : florida | january 10, 1861 | none | none row 4 : alabama | january 11, 1861 | none | none row 5 : georgia | january 19, 1861 | none | none row 6 : louisiana | january 26, 1861 | none | none row 7 : texas | february 1, 1861 | february 23 | 46,153-14,747 row 8 : virginia | april 17, 1861 | may 23 | 132,201-37,451 row 9 : arkansas | may 6, 1861 | none | none row 10 : tennessee | may 6, 1861 | june 8 | 104,471-47,183 row 11 : n. carolina | may 20, 1861 | none | none row 12 : missouri | october 31, 1861 | none | none row 13 : kentucky | november 20, 1861 | none | none | col : count ( "state" ) row 1 : 1 | select count ( state ) where state = 'virginia' <table_name> : table \begin{tabular}{lllll}
\toprule
& state & passed & referendum & vote \\
\midrule
0 & s. carolina & december 20, 1860 & none & none \\
1 & mississippi & january 9, 1861 & none & none \\
2 & florida & january 10, 1861 & none & none \\
3 & alabama & january 11, 1861 & none & none \\
4 & georgia & january 19, 1861 & none & none \\
5 & louisiana & january 26, 1861 & none & none \\
6 & texas & february 1, 1861 & february 23 & 46,153-14,747 \\
7 & virginia & april 17, 1861 & may 23 & 132,201-37,451 \\
8 & arkansas & may 6, 1861 & none & none \\
9 & tennessee & may 6, 1861 & june 8 & 104,471-47,183 \\
10 & n. carolina & may 20, 1861 & none & none \\
11 & missouri & october 31, 1861 & none & none \\
12 & kentucky & november 20, 1861 & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "state" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( state ) where state = 'virginia' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>state</th>
<th>passed</th>
<th>referendum</th>
<th>vote</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>s. carolina</td>
<td>december 20, 1860</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>mississippi</td>
<td>january 9, 1861</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>florida</td>
<td>january 10, 1861</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>alabama</td>
<td>january 11, 1861</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>georgia</td>
<td>january 19, 1861</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>louisiana</td>
<td>january 26, 1861</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>texas</td>
<td>february 1, 1861</td>
<td>february 23</td>
<td>46,153-14,747</td>
</tr>
<tr>
<th>7</th>
<td>virginia</td>
<td>april 17, 1861</td>
<td>may 23</td>
<td>132,201-37,451</td>
</tr>
<tr>
<th>8</th>
<td>arkansas</td>
<td>may 6, 1861</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>tennessee</td>
<td>may 6, 1861</td>
<td>june 8</td>
<td>104,471-47,183</td>
</tr>
<tr>
<th>10</th>
<td>n. carolina</td>
<td>may 20, 1861</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>missouri</td>
<td>october 31, 1861</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>kentucky</td>
<td>november 20, 1861</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 ( "state" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( state ) where state = 'virginia' <table_name> : table | | state | passed | referendum | vote |
|---:|:------------|:------------------|:-------------|:---------------|
| 0 | s. carolina | december 20, 1860 | none | none |
| 1 | mississippi | january 9, 1861 | none | none |
| 2 | florida | january 10, 1861 | none | none |
| 3 | alabama | january 11, 1861 | none | none |
| 4 | georgia | january 19, 1861 | none | none |
| 5 | louisiana | january 26, 1861 | none | none |
| 6 | texas | february 1, 1861 | february 23 | 46,153-14,747 |
| 7 | virginia | april 17, 1861 | may 23 | 132,201-37,451 |
| 8 | arkansas | may 6, 1861 | none | none |
| 9 | tennessee | may 6, 1861 | june 8 | 104,471-47,183 |
| 10 | n. carolina | may 20, 1861 | none | none |
| 11 | missouri | october 31, 1861 | none | none |
| 12 | kentucky | november 20, 1861 | none | none | | | | count ( "state" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select count ( to par ) where country = 'united states' 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 : count ( "to par" ) row 1 : 10 | select count ( to par ) where country = 'united states' <table_name> : table \begin{tabular}{lllllll}
\toprule
& place & player & country & score & to par & money ($) \\
\midrule
0 & t1 & larry nelson & united states & 70-72-73-72=287 & -1 & playoff \\
1 & t1 & lanny wadkins & united states & 70-70-74-73=287 & -1 & playoff \\
2 & t3 & scott hoch & united states & 74-74-71-69=288 & e & 58750 \\
3 & t3 & d. a. weibring & united states & 73-72-67-76=288 & e & 58750 \\
4 & t5 & mark mccumber & united states & 74-69-69-77=289 & 1 & 37500 \\
5 & t5 & don pooley & united states & 73-71-73-72=289 & 1 & 37500 \\
6 & t7 & ben crenshaw & united states & 72-70-74-74=290 & 2 & 27500 \\
7 & t7 & bobby wadkins & united states & 68-74-71-77=290 & 2 & 27500 \\
8 & 9 & curtis strange & united states & 70-76-71-74=291 & 3 & 22500 \\
9 & t10 & seve ballesteros & spain & 72-70-72-78=292 & 4 & 17000 \\
10 & t10 & david frost & south africa & 75-70-71-76=292 & 4 & 17000 \\
11 & t10 & tom kite & united states & 72-77-71-72=292 & 4 & 17000 \\
12 & t10 & nick price & zimbabwe & 76-71-70-75=292 & 4 & 17000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "to par" ) \\
\midrule
0 & 10 \\
\bottomrule
\end{tabular}
| select count ( to par ) where country = 'united states' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
<th>player</th>
<th>country</th>
<th>score</th>
<th>to par</th>
<th>money ($)</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>count ( "to par" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>10</td>
</tr>
</tbody>
</table> | select count ( to par ) where country = 'united states' <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 | | | | count ( "to par" ) |
|---:|---------------------:|
| 0 | 10 | | [
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select count ( * ) where episode = '"welcome to the club"' col : # | episode | air date | rating | share | 18-49 (rating/share) | viewers (m) | rank (night) | rank (timeslot) | rank (overall) row 1 : 1 | "welcome to the club" | october 12, 2007 | 7.3 | 13 | 2.5/8 | 10.82 | #1 | #1 | #26 row 2 : 2 | "train in vain" | october 19, 2007 | 6.5 | 12 | 2.0/6 | 9.69 | #2 | #1 | #37 row 3 : 3 | "blind dates and bleeding hearts" | october 26, 2007 | 6.1 | 11 | 1.9/6 | 8.9 | #1 | #1 | #41 row 4 : 4 | "grannies, guns, love mints" | november 2, 2007 | 6.4 | 11 | 1.9/6 | 9.47 | #1 | #1 | #35 row 5 : 5 | "maybe, baby" | november 9, 2007 | 6.5 | 11 | 2.0/6 | 9.7 | #1 | #1 | #36 row 6 : 6 | "play through the pain" | november 15, 2007 | 6.1 | 10 | 3.3/9 | 8.93 | #8 | #3 | #45 row 7 : 7 | "the past comes back to haunt you" | november 16, 2007 | 6.2 | 11 | 1.7/5 | 8.94 | #4 | #1 | #41 row 8 : 8 | "no opportunity necessary" | november 23, 2007 | 5.3 | 9 | 1.6/5 | 7.76 | #3 | #1 | #45 row 9 : 9 | "to drag & to hold" | december 7, 2007 | 5.8 | 10 | 1.8/5 | 8.58 | #2 | #1 | #32 row 10 : 10 | "fbi guy" | january 4, 2008 | 5.2 | 9 | 1.8/5 | 7.68 | #2 | #1 | #36 row 11 : 11 | "father's day" | april 29, 2008 | 5.8 | 9 | 1.9/5 | 8.14 | #7 | #2 | #42 row 12 : 12 | "and the truth will (sometimes) set you free" | may 6, 2008 | 6.1 | 10 | 2.2/6 | 8.68 | #8 | #2 | none row 13 : 13 | "never tell" | may 13, 2008 | 5.8 | 10 | 2.1/6 | 8.46 | none | #2 | none | col : count ( "*" ) row 1 : 0 | select count ( * ) where episode = '"welcome to the club"' <table_name> : table \begin{tabular}{lllllllllll}
\toprule
& # & episode & air date & rating & share & 18-49 (rating/share) & viewers (m) & rank (night) & rank (timeslot) & rank (overall) \\
\midrule
0 & 1 & "welcome to the club" & october 12, 2007 & 7.3 & 13 & 2.5/8 & 10.82 & #1 & #1 & #26 \\
1 & 2 & "train in vain" & october 19, 2007 & 6.5 & 12 & 2.0/6 & 9.69 & #2 & #1 & #37 \\
2 & 3 & "blind dates and bleeding hearts" & october 26, 2007 & 6.1 & 11 & 1.9/6 & 8.9 & #1 & #1 & #41 \\
3 & 4 & "grannies, guns, love mints" & november 2, 2007 & 6.4 & 11 & 1.9/6 & 9.47 & #1 & #1 & #35 \\
4 & 5 & "maybe, baby" & november 9, 2007 & 6.5 & 11 & 2.0/6 & 9.7 & #1 & #1 & #36 \\
5 & 6 & "play through the pain" & november 15, 2007 & 6.1 & 10 & 3.3/9 & 8.93 & #8 & #3 & #45 \\
6 & 7 & "the past comes back to haunt you" & november 16, 2007 & 6.2 & 11 & 1.7/5 & 8.94 & #4 & #1 & #41 \\
7 & 8 & "no opportunity necessary" & november 23, 2007 & 5.3 & 9 & 1.6/5 & 7.76 & #3 & #1 & #45 \\
8 & 9 & "to drag & to hold" & december 7, 2007 & 5.8 & 10 & 1.8/5 & 8.58 & #2 & #1 & #32 \\
9 & 10 & "fbi guy" & january 4, 2008 & 5.2 & 9 & 1.8/5 & 7.68 & #2 & #1 & #36 \\
10 & 11 & "father's day" & april 29, 2008 & 5.8 & 9 & 1.9/5 & 8.14 & #7 & #2 & #42 \\
11 & 12 & "and the truth will (sometimes) set you free" & may 6, 2008 & 6.1 & 10 & 2.2/6 & 8.68 & #8 & #2 & none \\
12 & 13 & "never tell" & may 13, 2008 & 5.8 & 10 & 2.1/6 & 8.46 & none & #2 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where episode = '"welcome to the club"' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>episode</th>
<th>air date</th>
<th>rating</th>
<th>share</th>
<th>18-49 (rating/share)</th>
<th>viewers (m)</th>
<th>rank (night)</th>
<th>rank (timeslot)</th>
<th>rank (overall)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>"welcome to the club"</td>
<td>october 12, 2007</td>
<td>7.3</td>
<td>13</td>
<td>2.5/8</td>
<td>10.82</td>
<td>#1</td>
<td>#1</td>
<td>#26</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>"train in vain"</td>
<td>october 19, 2007</td>
<td>6.5</td>
<td>12</td>
<td>2.0/6</td>
<td>9.69</td>
<td>#2</td>
<td>#1</td>
<td>#37</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>"blind dates and bleeding hearts"</td>
<td>october 26, 2007</td>
<td>6.1</td>
<td>11</td>
<td>1.9/6</td>
<td>8.9</td>
<td>#1</td>
<td>#1</td>
<td>#41</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>"grannies, guns, love mints"</td>
<td>november 2, 2007</td>
<td>6.4</td>
<td>11</td>
<td>1.9/6</td>
<td>9.47</td>
<td>#1</td>
<td>#1</td>
<td>#35</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>"maybe, baby"</td>
<td>november 9, 2007</td>
<td>6.5</td>
<td>11</td>
<td>2.0/6</td>
<td>9.7</td>
<td>#1</td>
<td>#1</td>
<td>#36</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>"play through the pain"</td>
<td>november 15, 2007</td>
<td>6.1</td>
<td>10</td>
<td>3.3/9</td>
<td>8.93</td>
<td>#8</td>
<td>#3</td>
<td>#45</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>"the past comes back to haunt you"</td>
<td>november 16, 2007</td>
<td>6.2</td>
<td>11</td>
<td>1.7/5</td>
<td>8.94</td>
<td>#4</td>
<td>#1</td>
<td>#41</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>"no opportunity necessary"</td>
<td>november 23, 2007</td>
<td>5.3</td>
<td>9</td>
<td>1.6/5</td>
<td>7.76</td>
<td>#3</td>
<td>#1</td>
<td>#45</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>"to drag & to hold"</td>
<td>december 7, 2007</td>
<td>5.8</td>
<td>10</td>
<td>1.8/5</td>
<td>8.58</td>
<td>#2</td>
<td>#1</td>
<td>#32</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>"fbi guy"</td>
<td>january 4, 2008</td>
<td>5.2</td>
<td>9</td>
<td>1.8/5</td>
<td>7.68</td>
<td>#2</td>
<td>#1</td>
<td>#36</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>"father's day"</td>
<td>april 29, 2008</td>
<td>5.8</td>
<td>9</td>
<td>1.9/5</td>
<td>8.14</td>
<td>#7</td>
<td>#2</td>
<td>#42</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>"and the truth will (sometimes) set you free"</td>
<td>may 6, 2008</td>
<td>6.1</td>
<td>10</td>
<td>2.2/6</td>
<td>8.68</td>
<td>#8</td>
<td>#2</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>"never tell"</td>
<td>may 13, 2008</td>
<td>5.8</td>
<td>10</td>
<td>2.1/6</td>
<td>8.46</td>
<td>none</td>
<td>#2</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 episode = '"welcome to the club"' <table_name> : table | | # | episode | air date | rating | share | 18-49 (rating/share) | viewers (m) | rank (night) | rank (timeslot) | rank (overall) |
|---:|----:|:----------------------------------------------|:------------------|---------:|--------:|:-----------------------|--------------:|:---------------|:------------------|:-----------------|
| 0 | 1 | "welcome to the club" | october 12, 2007 | 7.3 | 13 | 2.5/8 | 10.82 | #1 | #1 | #26 |
| 1 | 2 | "train in vain" | october 19, 2007 | 6.5 | 12 | 2.0/6 | 9.69 | #2 | #1 | #37 |
| 2 | 3 | "blind dates and bleeding hearts" | october 26, 2007 | 6.1 | 11 | 1.9/6 | 8.9 | #1 | #1 | #41 |
| 3 | 4 | "grannies, guns, love mints" | november 2, 2007 | 6.4 | 11 | 1.9/6 | 9.47 | #1 | #1 | #35 |
| 4 | 5 | "maybe, baby" | november 9, 2007 | 6.5 | 11 | 2.0/6 | 9.7 | #1 | #1 | #36 |
| 5 | 6 | "play through the pain" | november 15, 2007 | 6.1 | 10 | 3.3/9 | 8.93 | #8 | #3 | #45 |
| 6 | 7 | "the past comes back to haunt you" | november 16, 2007 | 6.2 | 11 | 1.7/5 | 8.94 | #4 | #1 | #41 |
| 7 | 8 | "no opportunity necessary" | november 23, 2007 | 5.3 | 9 | 1.6/5 | 7.76 | #3 | #1 | #45 |
| 8 | 9 | "to drag & to hold" | december 7, 2007 | 5.8 | 10 | 1.8/5 | 8.58 | #2 | #1 | #32 |
| 9 | 10 | "fbi guy" | january 4, 2008 | 5.2 | 9 | 1.8/5 | 7.68 | #2 | #1 | #36 |
| 10 | 11 | "father's day" | april 29, 2008 | 5.8 | 9 | 1.9/5 | 8.14 | #7 | #2 | #42 |
| 11 | 12 | "and the truth will (sometimes) set you free" | may 6, 2008 | 6.1 | 10 | 2.2/6 | 8.68 | #8 | #2 | none |
| 12 | 13 | "never tell" | may 13, 2008 | 5.8 | 10 | 2.1/6 | 8.46 | none | #2 | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select # where date = '17 february 2005' col : # | date | venue | opponent | result | competition | scored row 1 : 1 | 2002-03-05 00:00:00 | lagos | sweden | 3-6 | algarve cup | 1 row 2 : 2 | 2002-09-22 00:00:00 | st andrew's, birmingham | iceland | 1-0 | 2003 fifa world cup qual | 1 row 3 : 3 | 2003-10-21 00:00:00 | kryoia soveto, moscow | russia | 2-2 | friendly | 1 row 4 : 4 | 2003-11-14 00:00:00 | deepdale, preston | scotland | 5-0 | friendly | 1 row 5 : 5 | 2004-09-16 00:00:00 | sportpark de wending, heerhugowaard | netherlands | 2-1 | friendly | 1 row 6 : 6 | 2005-02-17 00:00:00 | national hockey stadium, milton keynes | italy | 4-1 | friendly | 1 row 7 : 7 | 2005-03-09 00:00:00 | faro | portugal | 4-0 | algarve cup | 1 row 8 : 8 | 2005-04-21 00:00:00 | prenton park, tranmere | scotland | 2-1 | friendly | 1 row 9 : 9 | 2005-06-05 00:00:00 | city of manchester stadium, manchester | finland | 3-2 | 2005 uefa championship | 1 row 10 : 10 | 2005-09-01 00:00:00 | ertl-glas-stadion, amstetten | austria | 4-1 | 2007 fifa world cup qual | 1 | col : # row 1 : 6 | select # where date = '17 february 2005' <table_name> : table \begin{tabular}{llllllll}
\toprule
& # & date & venue & opponent & result & competition & scored \\
\midrule
0 & 1 & 2002-03-05 00:00:00 & lagos & sweden & 3-6 & algarve cup & 1 \\
1 & 2 & 2002-09-22 00:00:00 & st andrew's, birmingham & iceland & 1-0 & 2003 fifa world cup qual & 1 \\
2 & 3 & 2003-10-21 00:00:00 & kryoia soveto, moscow & russia & 2-2 & friendly & 1 \\
3 & 4 & 2003-11-14 00:00:00 & deepdale, preston & scotland & 5-0 & friendly & 1 \\
4 & 5 & 2004-09-16 00:00:00 & sportpark de wending, heerhugowaard & netherlands & 2-1 & friendly & 1 \\
5 & 6 & 2005-02-17 00:00:00 & national hockey stadium, milton keynes & italy & 4-1 & friendly & 1 \\
6 & 7 & 2005-03-09 00:00:00 & faro & portugal & 4-0 & algarve cup & 1 \\
7 & 8 & 2005-04-21 00:00:00 & prenton park, tranmere & scotland & 2-1 & friendly & 1 \\
8 & 9 & 2005-06-05 00:00:00 & city of manchester stadium, manchester & finland & 3-2 & 2005 uefa championship & 1 \\
9 & 10 & 2005-09-01 00:00:00 & ertl-glas-stadion, amstetten & austria & 4-1 & 2007 fifa world cup qual & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& # \\
\midrule
0 & 6 \\
\bottomrule
\end{tabular}
| select # where date = '17 february 2005' <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>result</th>
<th>competition</th>
<th>scored</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2002-03-05 00:00:00</td>
<td>lagos</td>
<td>sweden</td>
<td>3-6</td>
<td>algarve cup</td>
<td>1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2002-09-22 00:00:00</td>
<td>st andrew's, birmingham</td>
<td>iceland</td>
<td>1-0</td>
<td>2003 fifa world cup qual</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2003-10-21 00:00:00</td>
<td>kryoia soveto, moscow</td>
<td>russia</td>
<td>2-2</td>
<td>friendly</td>
<td>1</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2003-11-14 00:00:00</td>
<td>deepdale, preston</td>
<td>scotland</td>
<td>5-0</td>
<td>friendly</td>
<td>1</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2004-09-16 00:00:00</td>
<td>sportpark de wending, heerhugowaard</td>
<td>netherlands</td>
<td>2-1</td>
<td>friendly</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2005-02-17 00:00:00</td>
<td>national hockey stadium, milton keynes</td>
<td>italy</td>
<td>4-1</td>
<td>friendly</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2005-03-09 00:00:00</td>
<td>faro</td>
<td>portugal</td>
<td>4-0</td>
<td>algarve cup</td>
<td>1</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2005-04-21 00:00:00</td>
<td>prenton park, tranmere</td>
<td>scotland</td>
<td>2-1</td>
<td>friendly</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2005-06-05 00:00:00</td>
<td>city of manchester stadium, manchester</td>
<td>finland</td>
<td>3-2</td>
<td>2005 uefa championship</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2005-09-01 00:00:00</td>
<td>ertl-glas-stadion, amstetten</td>
<td>austria</td>
<td>4-1</td>
<td>2007 fifa world cup qual</td>
<td>1</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>6</td>
</tr>
</tbody>
</table> | select # where date = '17 february 2005' <table_name> : table | | # | date | venue | opponent | result | competition | scored |
|---:|----:|:--------------------|:---------------------------------------|:------------|:---------|:-------------------------|---------:|
| 0 | 1 | 2002-03-05 00:00:00 | lagos | sweden | 3-6 | algarve cup | 1 |
| 1 | 2 | 2002-09-22 00:00:00 | st andrew's, birmingham | iceland | 1-0 | 2003 fifa world cup qual | 1 |
| 2 | 3 | 2003-10-21 00:00:00 | kryoia soveto, moscow | russia | 2-2 | friendly | 1 |
| 3 | 4 | 2003-11-14 00:00:00 | deepdale, preston | scotland | 5-0 | friendly | 1 |
| 4 | 5 | 2004-09-16 00:00:00 | sportpark de wending, heerhugowaard | netherlands | 2-1 | friendly | 1 |
| 5 | 6 | 2005-02-17 00:00:00 | national hockey stadium, milton keynes | italy | 4-1 | friendly | 1 |
| 6 | 7 | 2005-03-09 00:00:00 | faro | portugal | 4-0 | algarve cup | 1 |
| 7 | 8 | 2005-04-21 00:00:00 | prenton park, tranmere | scotland | 2-1 | friendly | 1 |
| 8 | 9 | 2005-06-05 00:00:00 | city of manchester stadium, manchester | finland | 3-2 | 2005 uefa championship | 1 |
| 9 | 10 | 2005-09-01 00:00:00 | ertl-glas-stadion, amstetten | austria | 4-1 | 2007 fifa world cup qual | 1 | | | | # |
|---:|----:|
| 0 | 6 | | [
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select nation where nation = 'mexico' col : rank | nation | gold | silver | bronze | total row 1 : 1 | russia | 7 | 3 | 0 | 10 row 2 : 2 | italy | 1 | 3 | 0 | 4 row 3 : 3 | france | 1 | 1 | 2 | 4 row 4 : 4 | austria | 1 | 1 | 0 | 2 row 5 : 4 | germany | 1 | 1 | 0 | 2 row 6 : 4 | iran | 1 | 1 | 0 | 2 row 7 : 4 | israel | 1 | 1 | 0 | 2 row 8 : 8 | poland | 1 | 0 | 5 | 6 row 9 : 9 | netherlands | 1 | 0 | 1 | 2 row 10 : 9 | romania | 1 | 0 | 1 | 2 row 11 : 11 | belgium | 1 | 0 | 0 | 1 row 12 : 11 | mexico | 1 | 0 | 0 | 1 row 13 : 13 | spain | 0 | 2 | 0 | 2 row 14 : 14 | sweden | 0 | 1 | 3 | 4 row 15 : 15 | colombia | 0 | 1 | 1 | 2 row 16 : 15 | ukraine | 0 | 1 | 1 | 2 row 17 : 17 | denmark | 0 | 1 | 0 | 1 row 18 : 17 | switzerland | 0 | 1 | 0 | 1 row 19 : 19 | algeria | 0 | 0 | 1 | 1 row 20 : 19 | greece | 0 | 0 | 1 | 1 row 21 : 19 | kazakhstan | 0 | 0 | 1 | 1 row 22 : 19 | slovenia | 0 | 0 | 1 | 1 row 23 : total | total | 18 | 18 | 18 | 54 | col : nation row 1 : mexico | select nation where nation = 'mexico' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & russia & 7 & 3 & 0 & 10 \\
1 & 2 & italy & 1 & 3 & 0 & 4 \\
2 & 3 & france & 1 & 1 & 2 & 4 \\
3 & 4 & austria & 1 & 1 & 0 & 2 \\
4 & 4 & germany & 1 & 1 & 0 & 2 \\
5 & 4 & iran & 1 & 1 & 0 & 2 \\
6 & 4 & israel & 1 & 1 & 0 & 2 \\
7 & 8 & poland & 1 & 0 & 5 & 6 \\
8 & 9 & netherlands & 1 & 0 & 1 & 2 \\
9 & 9 & romania & 1 & 0 & 1 & 2 \\
10 & 11 & belgium & 1 & 0 & 0 & 1 \\
11 & 11 & mexico & 1 & 0 & 0 & 1 \\
12 & 13 & spain & 0 & 2 & 0 & 2 \\
13 & 14 & sweden & 0 & 1 & 3 & 4 \\
14 & 15 & colombia & 0 & 1 & 1 & 2 \\
15 & 15 & ukraine & 0 & 1 & 1 & 2 \\
16 & 17 & denmark & 0 & 1 & 0 & 1 \\
17 & 17 & switzerland & 0 & 1 & 0 & 1 \\
18 & 19 & algeria & 0 & 0 & 1 & 1 \\
19 & 19 & greece & 0 & 0 & 1 & 1 \\
20 & 19 & kazakhstan & 0 & 0 & 1 & 1 \\
21 & 19 & slovenia & 0 & 0 & 1 & 1 \\
22 & total & total & 18 & 18 & 18 & 54 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & mexico \\
\bottomrule
\end{tabular}
| select nation where nation = 'mexico' <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>russia</td>
<td>7</td>
<td>3</td>
<td>0</td>
<td>10</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>italy</td>
<td>1</td>
<td>3</td>
<td>0</td>
<td>4</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>france</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>austria</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>germany</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>iran</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>4</td>
<td>israel</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>poland</td>
<td>1</td>
<td>0</td>
<td>5</td>
<td>6</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>netherlands</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>romania</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>belgium</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>mexico</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>spain</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>sweden</td>
<td>0</td>
<td>1</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>colombia</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>15</th>
<td>15</td>
<td>ukraine</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>denmark</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>17</th>
<td>17</td>
<td>switzerland</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>algeria</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>19</th>
<td>19</td>
<td>greece</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>20</th>
<td>19</td>
<td>kazakhstan</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>21</th>
<td>19</td>
<td>slovenia</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>22</th>
<td>total</td>
<td>total</td>
<td>18</td>
<td>18</td>
<td>18</td>
<td>54</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>mexico</td>
</tr>
</tbody>
</table> | select nation where nation = 'mexico' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:------------|-------:|---------:|---------:|--------:|
| 0 | 1 | russia | 7 | 3 | 0 | 10 |
| 1 | 2 | italy | 1 | 3 | 0 | 4 |
| 2 | 3 | france | 1 | 1 | 2 | 4 |
| 3 | 4 | austria | 1 | 1 | 0 | 2 |
| 4 | 4 | germany | 1 | 1 | 0 | 2 |
| 5 | 4 | iran | 1 | 1 | 0 | 2 |
| 6 | 4 | israel | 1 | 1 | 0 | 2 |
| 7 | 8 | poland | 1 | 0 | 5 | 6 |
| 8 | 9 | netherlands | 1 | 0 | 1 | 2 |
| 9 | 9 | romania | 1 | 0 | 1 | 2 |
| 10 | 11 | belgium | 1 | 0 | 0 | 1 |
| 11 | 11 | mexico | 1 | 0 | 0 | 1 |
| 12 | 13 | spain | 0 | 2 | 0 | 2 |
| 13 | 14 | sweden | 0 | 1 | 3 | 4 |
| 14 | 15 | colombia | 0 | 1 | 1 | 2 |
| 15 | 15 | ukraine | 0 | 1 | 1 | 2 |
| 16 | 17 | denmark | 0 | 1 | 0 | 1 |
| 17 | 17 | switzerland | 0 | 1 | 0 | 1 |
| 18 | 19 | algeria | 0 | 0 | 1 | 1 |
| 19 | 19 | greece | 0 | 0 | 1 | 1 |
| 20 | 19 | kazakhstan | 0 | 0 | 1 | 1 |
| 21 | 19 | slovenia | 0 | 0 | 1 | 1 |
| 22 | total | total | 18 | 18 | 18 | 54 | | | | nation |
|---:|:---------|
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select count ( cabinet ) where cabinet = 899 col : year | vote % | place -1 | seats | place -2 | cabinet row 1 : 1945 | none | none | 25 | 1st | yes row 2 : 1948 | none | none | 22 | 1st | yes row 3 : 1951 | none | none | 21 | 1st | yes row 4 : 1954 | 42.4 | 1st | 26 | 1st | yes row 5 : 1959 | 36.9 | 1st | 21 | 1st | yes row 6 : 1964 | 33.3 | 2nd | 22 | 1st | yes row 7 : 1968 | 35.2 | 1st | 21 | 1st | yes row 8 : 1974 | 27.6 | 2nd | 18 | 1st | no row 9 : 1979 | 34.5 | 1st | 24 | 1st | yes row 10 : 1984 | 34.9 | 1st | 25 | 1st | yes row 11 : 1989 | 32.4 | 1st | 22 | 1st | yes row 12 : 1994 | 30.3 | 1st | 21 | 1st | yes row 13 : 1999 | 30.1 | 1st | 19 | 1st | yes row 14 : 2004 | 36.1 | 1st | 24 | 1st | yes row 15 : 2009 | 38 | 1st | 26 | 1st | yes row 16 : 2013 | 33.6 | 1st | 23 | 1st | no | col : count ( "cabinet" ) row 1 : 0 | select count ( cabinet ) where cabinet = 899 <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & vote % & place -1 & seats & place -2 & cabinet \\
\midrule
0 & 1945 & none & none & 25 & 1st & yes \\
1 & 1948 & none & none & 22 & 1st & yes \\
2 & 1951 & none & none & 21 & 1st & yes \\
3 & 1954 & 42.4 & 1st & 26 & 1st & yes \\
4 & 1959 & 36.9 & 1st & 21 & 1st & yes \\
5 & 1964 & 33.3 & 2nd & 22 & 1st & yes \\
6 & 1968 & 35.2 & 1st & 21 & 1st & yes \\
7 & 1974 & 27.6 & 2nd & 18 & 1st & no \\
8 & 1979 & 34.5 & 1st & 24 & 1st & yes \\
9 & 1984 & 34.9 & 1st & 25 & 1st & yes \\
10 & 1989 & 32.4 & 1st & 22 & 1st & yes \\
11 & 1994 & 30.3 & 1st & 21 & 1st & yes \\
12 & 1999 & 30.1 & 1st & 19 & 1st & yes \\
13 & 2004 & 36.1 & 1st & 24 & 1st & yes \\
14 & 2009 & 38 & 1st & 26 & 1st & yes \\
15 & 2013 & 33.6 & 1st & 23 & 1st & no \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "cabinet" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( cabinet ) where cabinet = 899 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>vote %</th>
<th>place -1</th>
<th>seats</th>
<th>place -2</th>
<th>cabinet</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1945</td>
<td>none</td>
<td>none</td>
<td>25</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>1</th>
<td>1948</td>
<td>none</td>
<td>none</td>
<td>22</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>2</th>
<td>1951</td>
<td>none</td>
<td>none</td>
<td>21</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>3</th>
<td>1954</td>
<td>42.4</td>
<td>1st</td>
<td>26</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>4</th>
<td>1959</td>
<td>36.9</td>
<td>1st</td>
<td>21</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>5</th>
<td>1964</td>
<td>33.3</td>
<td>2nd</td>
<td>22</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>6</th>
<td>1968</td>
<td>35.2</td>
<td>1st</td>
<td>21</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>7</th>
<td>1974</td>
<td>27.6</td>
<td>2nd</td>
<td>18</td>
<td>1st</td>
<td>no</td>
</tr>
<tr>
<th>8</th>
<td>1979</td>
<td>34.5</td>
<td>1st</td>
<td>24</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>9</th>
<td>1984</td>
<td>34.9</td>
<td>1st</td>
<td>25</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>10</th>
<td>1989</td>
<td>32.4</td>
<td>1st</td>
<td>22</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>11</th>
<td>1994</td>
<td>30.3</td>
<td>1st</td>
<td>21</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>12</th>
<td>1999</td>
<td>30.1</td>
<td>1st</td>
<td>19</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>13</th>
<td>2004</td>
<td>36.1</td>
<td>1st</td>
<td>24</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>14</th>
<td>2009</td>
<td>38</td>
<td>1st</td>
<td>26</td>
<td>1st</td>
<td>yes</td>
</tr>
<tr>
<th>15</th>
<td>2013</td>
<td>33.6</td>
<td>1st</td>
<td>23</td>
<td>1st</td>
<td>no</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "cabinet" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( cabinet ) where cabinet = 899 <table_name> : table | | year | vote % | place -1 | seats | place -2 | cabinet |
|---:|-------:|:---------|:-----------|--------:|:-----------|:----------|
| 0 | 1945 | none | none | 25 | 1st | yes |
| 1 | 1948 | none | none | 22 | 1st | yes |
| 2 | 1951 | none | none | 21 | 1st | yes |
| 3 | 1954 | 42.4 | 1st | 26 | 1st | yes |
| 4 | 1959 | 36.9 | 1st | 21 | 1st | yes |
| 5 | 1964 | 33.3 | 2nd | 22 | 1st | yes |
| 6 | 1968 | 35.2 | 1st | 21 | 1st | yes |
| 7 | 1974 | 27.6 | 2nd | 18 | 1st | no |
| 8 | 1979 | 34.5 | 1st | 24 | 1st | yes |
| 9 | 1984 | 34.9 | 1st | 25 | 1st | yes |
| 10 | 1989 | 32.4 | 1st | 22 | 1st | yes |
| 11 | 1994 | 30.3 | 1st | 21 | 1st | yes |
| 12 | 1999 | 30.1 | 1st | 19 | 1st | yes |
| 13 | 2004 | 36.1 | 1st | 24 | 1st | yes |
| 14 | 2009 | 38 | 1st | 26 | 1st | yes |
| 15 | 2013 | 33.6 | 1st | 23 | 1st | no | | | | count ( "cabinet" ) |
|---:|----------------------:|
| 0 | 0 | | [
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select count ( winner ) where tournament = 'roberto de vicenzo classic' col : date | tournament | winner | purse ($) | notes row 1 : 25 feb | pinamar open | miguel rodriguez | 70000 | none row 2 : 3 mar | south open | rafael gomez | 100000 | none row 3 : 10 mar | parana open | julio zapata | 70000 | none row 4 : 8 apr | norpatagonico open | luciano dodda (amateur) | none | pga argentina- no valid tpg row 5 : 15 apr | center open | angel cabrera | 200000 | co-sanctioned by the tla row 6 : 22 apr | angel cabrera classic | rafael gomez | 120000 | none row 7 : 29 apr | chaco open | fabian gomez | 70000 | none row 8 : 9 jun | north open | ricardo gonzalez, andres romero (tie) | 80000 | none row 9 : 10 jul | metropolitano open | jose coceres | none | pga argentina- no valid tpg row 10 : 11 aug | misiones open | sergio acevedo | 70000 | none row 11 : 19 aug | carlos franco invitational | marco ruiz | 93000 | none row 12 : 29 sep | salta open | andres romero | 80000 | none row 13 : 7 oct | tandil open | diego ortiz | 70000 | none row 14 : 27 oct | argentine masters | angel cabrera | 420000 | co-sanctioned by the tla row 15 : 4 nov | mendoza open | rafael echenique | 80000 | none row 16 : 11 nov | roberto de vicenzo classic | miguel guzman | 120000 | none row 17 : 25 nov | san luis open | emilio dominguez | 450000 | co-sanctioned by the tla row 18 : 2 dec | abierto del litoral | miguel rodriguez | 520000 | co-sanctioned by the tla and challenge tour row 19 : 9 dec | argentine open | marco ruiz | 600000 | co-sanctioned by the tla and challenge tour | col : count ( "winner" ) row 1 : 1 | select count ( winner ) where tournament = 'roberto de vicenzo classic' <table_name> : table \begin{tabular}{llllll}
\toprule
& date & tournament & winner & purse ($) & notes \\
\midrule
0 & 25 feb & pinamar open & miguel rodriguez & 70000 & none \\
1 & 3 mar & south open & rafael gomez & 100000 & none \\
2 & 10 mar & parana open & julio zapata & 70000 & none \\
3 & 8 apr & norpatagonico open & luciano dodda (amateur) & none & pga argentina- no valid tpg \\
4 & 15 apr & center open & angel cabrera & 200000 & co-sanctioned by the tla \\
5 & 22 apr & angel cabrera classic & rafael gomez & 120000 & none \\
6 & 29 apr & chaco open & fabian gomez & 70000 & none \\
7 & 9 jun & north open & ricardo gonzalez, andres romero (tie) & 80000 & none \\
8 & 10 jul & metropolitano open & jose coceres & none & pga argentina- no valid tpg \\
9 & 11 aug & misiones open & sergio acevedo & 70000 & none \\
10 & 19 aug & carlos franco invitational & marco ruiz & 93000 & none \\
11 & 29 sep & salta open & andres romero & 80000 & none \\
12 & 7 oct & tandil open & diego ortiz & 70000 & none \\
13 & 27 oct & argentine masters & angel cabrera & 420000 & co-sanctioned by the tla \\
14 & 4 nov & mendoza open & rafael echenique & 80000 & none \\
15 & 11 nov & roberto de vicenzo classic & miguel guzman & 120000 & none \\
16 & 25 nov & san luis open & emilio dominguez & 450000 & co-sanctioned by the tla \\
17 & 2 dec & abierto del litoral & miguel rodriguez & 520000 & co-sanctioned by the tla and challenge tour \\
18 & 9 dec & argentine open & marco ruiz & 600000 & co-sanctioned by the tla and challenge tour \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "winner" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( winner ) where tournament = 'roberto de vicenzo classic' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>tournament</th>
<th>winner</th>
<th>purse ($)</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>25 feb</td>
<td>pinamar open</td>
<td>miguel rodriguez</td>
<td>70000</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>3 mar</td>
<td>south open</td>
<td>rafael gomez</td>
<td>100000</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>10 mar</td>
<td>parana open</td>
<td>julio zapata</td>
<td>70000</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>8 apr</td>
<td>norpatagonico open</td>
<td>luciano dodda (amateur)</td>
<td>none</td>
<td>pga argentina- no valid tpg</td>
</tr>
<tr>
<th>4</th>
<td>15 apr</td>
<td>center open</td>
<td>angel cabrera</td>
<td>200000</td>
<td>co-sanctioned by the tla</td>
</tr>
<tr>
<th>5</th>
<td>22 apr</td>
<td>angel cabrera classic</td>
<td>rafael gomez</td>
<td>120000</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>29 apr</td>
<td>chaco open</td>
<td>fabian gomez</td>
<td>70000</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>9 jun</td>
<td>north open</td>
<td>ricardo gonzalez, andres romero (tie)</td>
<td>80000</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>10 jul</td>
<td>metropolitano open</td>
<td>jose coceres</td>
<td>none</td>
<td>pga argentina- no valid tpg</td>
</tr>
<tr>
<th>9</th>
<td>11 aug</td>
<td>misiones open</td>
<td>sergio acevedo</td>
<td>70000</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>19 aug</td>
<td>carlos franco invitational</td>
<td>marco ruiz</td>
<td>93000</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>29 sep</td>
<td>salta open</td>
<td>andres romero</td>
<td>80000</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>7 oct</td>
<td>tandil open</td>
<td>diego ortiz</td>
<td>70000</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>27 oct</td>
<td>argentine masters</td>
<td>angel cabrera</td>
<td>420000</td>
<td>co-sanctioned by the tla</td>
</tr>
<tr>
<th>14</th>
<td>4 nov</td>
<td>mendoza open</td>
<td>rafael echenique</td>
<td>80000</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>11 nov</td>
<td>roberto de vicenzo classic</td>
<td>miguel guzman</td>
<td>120000</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>25 nov</td>
<td>san luis open</td>
<td>emilio dominguez</td>
<td>450000</td>
<td>co-sanctioned by the tla</td>
</tr>
<tr>
<th>17</th>
<td>2 dec</td>
<td>abierto del litoral</td>
<td>miguel rodriguez</td>
<td>520000</td>
<td>co-sanctioned by the tla and challenge tour</td>
</tr>
<tr>
<th>18</th>
<td>9 dec</td>
<td>argentine open</td>
<td>marco ruiz</td>
<td>600000</td>
<td>co-sanctioned by the tla and challenge tour</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "winner" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( winner ) where tournament = 'roberto de vicenzo classic' <table_name> : table | | date | tournament | winner | purse ($) | notes |
|---:|:-------|:---------------------------|:--------------------------------------|:------------|:--------------------------------------------|
| 0 | 25 feb | pinamar open | miguel rodriguez | 70000 | none |
| 1 | 3 mar | south open | rafael gomez | 100000 | none |
| 2 | 10 mar | parana open | julio zapata | 70000 | none |
| 3 | 8 apr | norpatagonico open | luciano dodda (amateur) | none | pga argentina- no valid tpg |
| 4 | 15 apr | center open | angel cabrera | 200000 | co-sanctioned by the tla |
| 5 | 22 apr | angel cabrera classic | rafael gomez | 120000 | none |
| 6 | 29 apr | chaco open | fabian gomez | 70000 | none |
| 7 | 9 jun | north open | ricardo gonzalez, andres romero (tie) | 80000 | none |
| 8 | 10 jul | metropolitano open | jose coceres | none | pga argentina- no valid tpg |
| 9 | 11 aug | misiones open | sergio acevedo | 70000 | none |
| 10 | 19 aug | carlos franco invitational | marco ruiz | 93000 | none |
| 11 | 29 sep | salta open | andres romero | 80000 | none |
| 12 | 7 oct | tandil open | diego ortiz | 70000 | none |
| 13 | 27 oct | argentine masters | angel cabrera | 420000 | co-sanctioned by the tla |
| 14 | 4 nov | mendoza open | rafael echenique | 80000 | none |
| 15 | 11 nov | roberto de vicenzo classic | miguel guzman | 120000 | none |
| 16 | 25 nov | san luis open | emilio dominguez | 450000 | co-sanctioned by the tla |
| 17 | 2 dec | abierto del litoral | miguel rodriguez | 520000 | co-sanctioned by the tla and challenge tour |
| 18 | 9 dec | argentine open | marco ruiz | 600000 | co-sanctioned by the tla and challenge tour | | | | count ( "winner" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select foe where foe = 'enemy fighter' col : no. | date/time | aircraft | foe | result | location | notes row 1 : u/c | 14 june 1917 | nieuport 17 | enemy aircraft | none | mount verena | victory originally confirmed, but disallowed postwar row 2 : 1 | 25 october 1917 @ 0800 hours | none | enemy aircraft | forced to land | marcesina | none row 3 : 2 | 7 november 1917 circa 1615 hours | none | enemy aircraft | forced to land | fonsazo | awarded silver medal for military valor row 4 : 3 | 7 december 1917 @ 1130 hours | none | enemy aircraft | none | val d'assa | none row 5 : 4 | 13 december 1917 ca. 1130 hours | none | enemy aircraft | none | asiago | none row 6 : 5 | 30 january 1918 @ 1000 hours | none | enemy two-seater | none | col d'eshele, asiago | awarded silver medal for military valor row 7 : u/c | 4 february 1918 ca. 1100 hours | none | black enemy fighter craft | none | valstagna | claim shared with antonio reali row 8 : 6 | 5 february 1918 ca. 0830 hours | none | enemy two-seater | forced to land | case girardi | shared with marziale cerutti row 9 : 7 | 13 february 1918 @ 0915 hours | none | enemy fighter | none | marcesina | none row 10 : u/c | 24 february 1918 | none | enemy aircraft | none | mount grappa | none row 11 : 8 | 4 may 1918 @ 0850 hours | nieuport 27 | enemy aircraft | none | montello | austro-hungarians reported no matching loss row 12 : 9 | 4 may 1918 @ 1025 hours | nieuport 27 | enemy fighter | none | montello | austro-hungarians reported no matching loss | col : foe row 1 : enemy fighter row 2 : enemy fighter | select foe where foe = 'enemy fighter' <table_name> : table \begin{tabular}{llllllll}
\toprule
& no. & date/time & aircraft & foe & result & location & notes \\
\midrule
0 & u/c & 14 june 1917 & nieuport 17 & enemy aircraft & none & mount verena & victory originally confirmed, but disallowed postwar \\
1 & 1 & 25 october 1917 @ 0800 hours & none & enemy aircraft & forced to land & marcesina & none \\
2 & 2 & 7 november 1917 circa 1615 hours & none & enemy aircraft & forced to land & fonsazo & awarded silver medal for military valor \\
3 & 3 & 7 december 1917 @ 1130 hours & none & enemy aircraft & none & val d'assa & none \\
4 & 4 & 13 december 1917 ca. 1130 hours & none & enemy aircraft & none & asiago & none \\
5 & 5 & 30 january 1918 @ 1000 hours & none & enemy two-seater & none & col d'eshele, asiago & awarded silver medal for military valor \\
6 & u/c & 4 february 1918 ca. 1100 hours & none & black enemy fighter craft & none & valstagna & claim shared with antonio reali \\
7 & 6 & 5 february 1918 ca. 0830 hours & none & enemy two-seater & forced to land & case girardi & shared with marziale cerutti \\
8 & 7 & 13 february 1918 @ 0915 hours & none & enemy fighter & none & marcesina & none \\
9 & u/c & 24 february 1918 & none & enemy aircraft & none & mount grappa & none \\
10 & 8 & 4 may 1918 @ 0850 hours & nieuport 27 & enemy aircraft & none & montello & austro-hungarians reported no matching loss \\
11 & 9 & 4 may 1918 @ 1025 hours & nieuport 27 & enemy fighter & none & montello & austro-hungarians reported no matching loss \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& foe \\
\midrule
0 & enemy fighter \\
1 & enemy fighter \\
\bottomrule
\end{tabular}
| select foe where foe = 'enemy fighter' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no.</th>
<th>date/time</th>
<th>aircraft</th>
<th>foe</th>
<th>result</th>
<th>location</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>u/c</td>
<td>14 june 1917</td>
<td>nieuport 17</td>
<td>enemy aircraft</td>
<td>none</td>
<td>mount verena</td>
<td>victory originally confirmed, but disallowed postwar</td>
</tr>
<tr>
<th>1</th>
<td>1</td>
<td>25 october 1917 @ 0800 hours</td>
<td>none</td>
<td>enemy aircraft</td>
<td>forced to land</td>
<td>marcesina</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2</td>
<td>7 november 1917 circa 1615 hours</td>
<td>none</td>
<td>enemy aircraft</td>
<td>forced to land</td>
<td>fonsazo</td>
<td>awarded silver medal for military valor</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>7 december 1917 @ 1130 hours</td>
<td>none</td>
<td>enemy aircraft</td>
<td>none</td>
<td>val d'assa</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>13 december 1917 ca. 1130 hours</td>
<td>none</td>
<td>enemy aircraft</td>
<td>none</td>
<td>asiago</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>30 january 1918 @ 1000 hours</td>
<td>none</td>
<td>enemy two-seater</td>
<td>none</td>
<td>col d'eshele, asiago</td>
<td>awarded silver medal for military valor</td>
</tr>
<tr>
<th>6</th>
<td>u/c</td>
<td>4 february 1918 ca. 1100 hours</td>
<td>none</td>
<td>black enemy fighter craft</td>
<td>none</td>
<td>valstagna</td>
<td>claim shared with antonio reali</td>
</tr>
<tr>
<th>7</th>
<td>6</td>
<td>5 february 1918 ca. 0830 hours</td>
<td>none</td>
<td>enemy two-seater</td>
<td>forced to land</td>
<td>case girardi</td>
<td>shared with marziale cerutti</td>
</tr>
<tr>
<th>8</th>
<td>7</td>
<td>13 february 1918 @ 0915 hours</td>
<td>none</td>
<td>enemy fighter</td>
<td>none</td>
<td>marcesina</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>u/c</td>
<td>24 february 1918</td>
<td>none</td>
<td>enemy aircraft</td>
<td>none</td>
<td>mount grappa</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>8</td>
<td>4 may 1918 @ 0850 hours</td>
<td>nieuport 27</td>
<td>enemy aircraft</td>
<td>none</td>
<td>montello</td>
<td>austro-hungarians reported no matching loss</td>
</tr>
<tr>
<th>11</th>
<td>9</td>
<td>4 may 1918 @ 1025 hours</td>
<td>nieuport 27</td>
<td>enemy fighter</td>
<td>none</td>
<td>montello</td>
<td>austro-hungarians reported no matching loss</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>foe</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>enemy fighter</td>
</tr>
<tr>
<th>1</th>
<td>enemy fighter</td>
</tr>
</tbody>
</table> | select foe where foe = 'enemy fighter' <table_name> : table | | no. | date/time | aircraft | foe | result | location | notes |
|---:|:------|:---------------------------------|:------------|:--------------------------|:---------------|:---------------------|:-----------------------------------------------------|
| 0 | u/c | 14 june 1917 | nieuport 17 | enemy aircraft | none | mount verena | victory originally confirmed, but disallowed postwar |
| 1 | 1 | 25 october 1917 @ 0800 hours | none | enemy aircraft | forced to land | marcesina | none |
| 2 | 2 | 7 november 1917 circa 1615 hours | none | enemy aircraft | forced to land | fonsazo | awarded silver medal for military valor |
| 3 | 3 | 7 december 1917 @ 1130 hours | none | enemy aircraft | none | val d'assa | none |
| 4 | 4 | 13 december 1917 ca. 1130 hours | none | enemy aircraft | none | asiago | none |
| 5 | 5 | 30 january 1918 @ 1000 hours | none | enemy two-seater | none | col d'eshele, asiago | awarded silver medal for military valor |
| 6 | u/c | 4 february 1918 ca. 1100 hours | none | black enemy fighter craft | none | valstagna | claim shared with antonio reali |
| 7 | 6 | 5 february 1918 ca. 0830 hours | none | enemy two-seater | forced to land | case girardi | shared with marziale cerutti |
| 8 | 7 | 13 february 1918 @ 0915 hours | none | enemy fighter | none | marcesina | none |
| 9 | u/c | 24 february 1918 | none | enemy aircraft | none | mount grappa | none |
| 10 | 8 | 4 may 1918 @ 0850 hours | nieuport 27 | enemy aircraft | none | montello | austro-hungarians reported no matching loss |
| 11 | 9 | 4 may 1918 @ 1025 hours | nieuport 27 | enemy fighter | none | montello | austro-hungarians reported no matching loss | | | | foe |
|---:|:--------------|
| 0 | enemy fighter |
| 1 | enemy fighter | | [
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select count ( former local authority ) where population > 16 col : name | status | population | district | former local authority row 1 : cronton | civil parish | 1379 | knowsley | whiston rural district row 2 : halewood | town | 20309 | knowsley | whiston rural district row 3 : huyton with roby | unparished area | 49859 | knowsley | huyton with roby urban district row 4 : kirkby | unparished area | 40374 | knowsley | kirkby urban district row 5 : knowsley | civil parish | 11343 | knowsley | whiston rural district row 6 : prescot | town | 11184 | knowsley | prescot urban district row 7 : tarbock | civil parish | 2382 | knowsley | whiston rural district row 8 : whiston | town | 13629 | knowsley | whiston rural district row 9 : liverpool | unparished area | 439473 | liverpool | liverpool county borough row 10 : aintree village | civil parish | 7126 | sefton | west lancashire rural district row 11 : bootle | unparished area | 59011 | sefton | bootle county borough row 12 : crosby | unparished area | 45872 | sefton | crosby municipal borough row 13 : formby | civil parish | 23586 | sefton | formby urban district row 14 : hightown | civil parish | 2247 | sefton | crosby municipal borough row 15 : ince blundell | civil parish | 518 | sefton | west lancashire rural district row 16 : litherland | unparished area | 18629 | sefton | litherland urban district row 17 : little altcar | civil parish | 892 | sefton | west lancashire rural district row 18 : lydiate | civil parish | 6672 | sefton | west lancashire rural district row 19 : maghull | town | 22225 | sefton | west lancashire rural district row 20 : melling | civil parish | 2810 | sefton | west lancashire rural district row 21 : sefton | civil parish | 772 | sefton | west lancashire rural district row 22 : southport | unparished area | 90336 | sefton | southport county borough row 23 : thornton | civil parish | 2262 | sefton | west lancashire rural district row 24 : billinge chapel end | civil parish | 6554 | st helens | billinge and winstanley urban district row 25 : bold | civil parish | 2283 | st helens | whiston rural district row 26 : eccleston | civil parish | 10528 | st helens | whiston rural district row 27 : haydock | unparished area | 15684 | st helens | haydock urban district row 28 : newton le willows | unparished area | 21418 | st helens | newton le willows urban district row 29 : rainford | civil parish | 8344 | st helens | rainford urban district row 30 : rainhill | civil parish | 11913 | st helens | whiston rural district row 31 : seneley green | civil parish | 6163 | st helens | ashton in makerfield urban district row 32 : st helens | unparished area | 91414 | st helens | st helens county borough row 33 : windle | civil parish | 2542 | st helens | whiston rural district row 34 : bebington | unparished area | 58226 | wirral | bebington municipal borough row 35 : birkenhead | unparished area | 103206 | wirral | birkenhead county borough row 36 : heswall | unparished area | 29977 | wirral | wirral urban district row 37 : hoylake | unparished area | 35655 | wirral | hoylake urban district row 38 : wallasey | unparished area | 84348 | wirral | wallasey county borough | col : count ( "former local authority" ) row 1 : 30 | select count ( former local authority ) where population > 16 <table_name> : table \begin{tabular}{llllll}
\toprule
& name & status & population & district & former local authority \\
\midrule
0 & cronton & civil parish & 1379 & knowsley & whiston rural district \\
1 & halewood & town & 20309 & knowsley & whiston rural district \\
2 & huyton with roby & unparished area & 49859 & knowsley & huyton with roby urban district \\
3 & kirkby & unparished area & 40374 & knowsley & kirkby urban district \\
4 & knowsley & civil parish & 11343 & knowsley & whiston rural district \\
5 & prescot & town & 11184 & knowsley & prescot urban district \\
6 & tarbock & civil parish & 2382 & knowsley & whiston rural district \\
7 & whiston & town & 13629 & knowsley & whiston rural district \\
8 & liverpool & unparished area & 439473 & liverpool & liverpool county borough \\
9 & aintree village & civil parish & 7126 & sefton & west lancashire rural district \\
10 & bootle & unparished area & 59011 & sefton & bootle county borough \\
11 & crosby & unparished area & 45872 & sefton & crosby municipal borough \\
12 & formby & civil parish & 23586 & sefton & formby urban district \\
13 & hightown & civil parish & 2247 & sefton & crosby municipal borough \\
14 & ince blundell & civil parish & 518 & sefton & west lancashire rural district \\
15 & litherland & unparished area & 18629 & sefton & litherland urban district \\
16 & little altcar & civil parish & 892 & sefton & west lancashire rural district \\
17 & lydiate & civil parish & 6672 & sefton & west lancashire rural district \\
18 & maghull & town & 22225 & sefton & west lancashire rural district \\
19 & melling & civil parish & 2810 & sefton & west lancashire rural district \\
20 & sefton & civil parish & 772 & sefton & west lancashire rural district \\
21 & southport & unparished area & 90336 & sefton & southport county borough \\
22 & thornton & civil parish & 2262 & sefton & west lancashire rural district \\
23 & billinge chapel end & civil parish & 6554 & st helens & billinge and winstanley urban district \\
24 & bold & civil parish & 2283 & st helens & whiston rural district \\
25 & eccleston & civil parish & 10528 & st helens & whiston rural district \\
26 & haydock & unparished area & 15684 & st helens & haydock urban district \\
27 & newton le willows & unparished area & 21418 & st helens & newton le willows urban district \\
28 & rainford & civil parish & 8344 & st helens & rainford urban district \\
29 & rainhill & civil parish & 11913 & st helens & whiston rural district \\
30 & seneley green & civil parish & 6163 & st helens & ashton in makerfield urban district \\
31 & st helens & unparished area & 91414 & st helens & st helens county borough \\
32 & windle & civil parish & 2542 & st helens & whiston rural district \\
33 & bebington & unparished area & 58226 & wirral & bebington municipal borough \\
34 & birkenhead & unparished area & 103206 & wirral & birkenhead county borough \\
35 & heswall & unparished area & 29977 & wirral & wirral urban district \\
36 & hoylake & unparished area & 35655 & wirral & hoylake urban district \\
37 & wallasey & unparished area & 84348 & wirral & wallasey county borough \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "former local authority" ) \\
\midrule
0 & 30 \\
\bottomrule
\end{tabular}
| select count ( former local authority ) where population > 16 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>status</th>
<th>population</th>
<th>district</th>
<th>former local authority</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>cronton</td>
<td>civil parish</td>
<td>1379</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>1</th>
<td>halewood</td>
<td>town</td>
<td>20309</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>2</th>
<td>huyton with roby</td>
<td>unparished area</td>
<td>49859</td>
<td>knowsley</td>
<td>huyton with roby urban district</td>
</tr>
<tr>
<th>3</th>
<td>kirkby</td>
<td>unparished area</td>
<td>40374</td>
<td>knowsley</td>
<td>kirkby urban district</td>
</tr>
<tr>
<th>4</th>
<td>knowsley</td>
<td>civil parish</td>
<td>11343</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>5</th>
<td>prescot</td>
<td>town</td>
<td>11184</td>
<td>knowsley</td>
<td>prescot urban district</td>
</tr>
<tr>
<th>6</th>
<td>tarbock</td>
<td>civil parish</td>
<td>2382</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>7</th>
<td>whiston</td>
<td>town</td>
<td>13629</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>8</th>
<td>liverpool</td>
<td>unparished area</td>
<td>439473</td>
<td>liverpool</td>
<td>liverpool county borough</td>
</tr>
<tr>
<th>9</th>
<td>aintree village</td>
<td>civil parish</td>
<td>7126</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>10</th>
<td>bootle</td>
<td>unparished area</td>
<td>59011</td>
<td>sefton</td>
<td>bootle county borough</td>
</tr>
<tr>
<th>11</th>
<td>crosby</td>
<td>unparished area</td>
<td>45872</td>
<td>sefton</td>
<td>crosby municipal borough</td>
</tr>
<tr>
<th>12</th>
<td>formby</td>
<td>civil parish</td>
<td>23586</td>
<td>sefton</td>
<td>formby urban district</td>
</tr>
<tr>
<th>13</th>
<td>hightown</td>
<td>civil parish</td>
<td>2247</td>
<td>sefton</td>
<td>crosby municipal borough</td>
</tr>
<tr>
<th>14</th>
<td>ince blundell</td>
<td>civil parish</td>
<td>518</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>15</th>
<td>litherland</td>
<td>unparished area</td>
<td>18629</td>
<td>sefton</td>
<td>litherland urban district</td>
</tr>
<tr>
<th>16</th>
<td>little altcar</td>
<td>civil parish</td>
<td>892</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>17</th>
<td>lydiate</td>
<td>civil parish</td>
<td>6672</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>18</th>
<td>maghull</td>
<td>town</td>
<td>22225</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>19</th>
<td>melling</td>
<td>civil parish</td>
<td>2810</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>20</th>
<td>sefton</td>
<td>civil parish</td>
<td>772</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>21</th>
<td>southport</td>
<td>unparished area</td>
<td>90336</td>
<td>sefton</td>
<td>southport county borough</td>
</tr>
<tr>
<th>22</th>
<td>thornton</td>
<td>civil parish</td>
<td>2262</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>23</th>
<td>billinge chapel end</td>
<td>civil parish</td>
<td>6554</td>
<td>st helens</td>
<td>billinge and winstanley urban district</td>
</tr>
<tr>
<th>24</th>
<td>bold</td>
<td>civil parish</td>
<td>2283</td>
<td>st helens</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>25</th>
<td>eccleston</td>
<td>civil parish</td>
<td>10528</td>
<td>st helens</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>26</th>
<td>haydock</td>
<td>unparished area</td>
<td>15684</td>
<td>st helens</td>
<td>haydock urban district</td>
</tr>
<tr>
<th>27</th>
<td>newton le willows</td>
<td>unparished area</td>
<td>21418</td>
<td>st helens</td>
<td>newton le willows urban district</td>
</tr>
<tr>
<th>28</th>
<td>rainford</td>
<td>civil parish</td>
<td>8344</td>
<td>st helens</td>
<td>rainford urban district</td>
</tr>
<tr>
<th>29</th>
<td>rainhill</td>
<td>civil parish</td>
<td>11913</td>
<td>st helens</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>30</th>
<td>seneley green</td>
<td>civil parish</td>
<td>6163</td>
<td>st helens</td>
<td>ashton in makerfield urban district</td>
</tr>
<tr>
<th>31</th>
<td>st helens</td>
<td>unparished area</td>
<td>91414</td>
<td>st helens</td>
<td>st helens county borough</td>
</tr>
<tr>
<th>32</th>
<td>windle</td>
<td>civil parish</td>
<td>2542</td>
<td>st helens</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>33</th>
<td>bebington</td>
<td>unparished area</td>
<td>58226</td>
<td>wirral</td>
<td>bebington municipal borough</td>
</tr>
<tr>
<th>34</th>
<td>birkenhead</td>
<td>unparished area</td>
<td>103206</td>
<td>wirral</td>
<td>birkenhead county borough</td>
</tr>
<tr>
<th>35</th>
<td>heswall</td>
<td>unparished area</td>
<td>29977</td>
<td>wirral</td>
<td>wirral urban district</td>
</tr>
<tr>
<th>36</th>
<td>hoylake</td>
<td>unparished area</td>
<td>35655</td>
<td>wirral</td>
<td>hoylake urban district</td>
</tr>
<tr>
<th>37</th>
<td>wallasey</td>
<td>unparished area</td>
<td>84348</td>
<td>wirral</td>
<td>wallasey county borough</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "former local authority" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>30</td>
</tr>
</tbody>
</table> | select count ( former local authority ) where population > 16 <table_name> : table | | name | status | population | district | former local authority |
|---:|:--------------------|:----------------|-------------:|:-----------|:---------------------------------------|
| 0 | cronton | civil parish | 1379 | knowsley | whiston rural district |
| 1 | halewood | town | 20309 | knowsley | whiston rural district |
| 2 | huyton with roby | unparished area | 49859 | knowsley | huyton with roby urban district |
| 3 | kirkby | unparished area | 40374 | knowsley | kirkby urban district |
| 4 | knowsley | civil parish | 11343 | knowsley | whiston rural district |
| 5 | prescot | town | 11184 | knowsley | prescot urban district |
| 6 | tarbock | civil parish | 2382 | knowsley | whiston rural district |
| 7 | whiston | town | 13629 | knowsley | whiston rural district |
| 8 | liverpool | unparished area | 439473 | liverpool | liverpool county borough |
| 9 | aintree village | civil parish | 7126 | sefton | west lancashire rural district |
| 10 | bootle | unparished area | 59011 | sefton | bootle county borough |
| 11 | crosby | unparished area | 45872 | sefton | crosby municipal borough |
| 12 | formby | civil parish | 23586 | sefton | formby urban district |
| 13 | hightown | civil parish | 2247 | sefton | crosby municipal borough |
| 14 | ince blundell | civil parish | 518 | sefton | west lancashire rural district |
| 15 | litherland | unparished area | 18629 | sefton | litherland urban district |
| 16 | little altcar | civil parish | 892 | sefton | west lancashire rural district |
| 17 | lydiate | civil parish | 6672 | sefton | west lancashire rural district |
| 18 | maghull | town | 22225 | sefton | west lancashire rural district |
| 19 | melling | civil parish | 2810 | sefton | west lancashire rural district |
| 20 | sefton | civil parish | 772 | sefton | west lancashire rural district |
| 21 | southport | unparished area | 90336 | sefton | southport county borough |
| 22 | thornton | civil parish | 2262 | sefton | west lancashire rural district |
| 23 | billinge chapel end | civil parish | 6554 | st helens | billinge and winstanley urban district |
| 24 | bold | civil parish | 2283 | st helens | whiston rural district |
| 25 | eccleston | civil parish | 10528 | st helens | whiston rural district |
| 26 | haydock | unparished area | 15684 | st helens | haydock urban district |
| 27 | newton le willows | unparished area | 21418 | st helens | newton le willows urban district |
| 28 | rainford | civil parish | 8344 | st helens | rainford urban district |
| 29 | rainhill | civil parish | 11913 | st helens | whiston rural district |
| 30 | seneley green | civil parish | 6163 | st helens | ashton in makerfield urban district |
| 31 | st helens | unparished area | 91414 | st helens | st helens county borough |
| 32 | windle | civil parish | 2542 | st helens | whiston rural district |
| 33 | bebington | unparished area | 58226 | wirral | bebington municipal borough |
| 34 | birkenhead | unparished area | 103206 | wirral | birkenhead county borough |
| 35 | heswall | unparished area | 29977 | wirral | wirral urban district |
| 36 | hoylake | unparished area | 35655 | wirral | hoylake urban district |
| 37 | wallasey | unparished area | 84348 | wirral | wallasey county borough | | | | count ( "former local authority" ) |
|---:|-------------------------------------:|
| 0 | 30 | | [
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select count ( * ) where finish = 'none' col : year | w | l | t | finish | coach row 1 : 1910 | 11 | 0 | 1 | none | earl ball row 2 : 1911 | 7 | 1 | 2 | none | earl ball row 3 : 1912 | 6 | 3 | 2 | none | earl ball row 4 : 1913 | 8 | 2 | 0 | indiana state champs | earl ball row 5 : 1914 | 5 | 3 | 1 | none | earl ball row 6 : 1915 | 8 | 2 | 1 | none | earl ball row 7 : 1916 | 2 | 7 | 1 | none | f.w. smith row 8 : 1917 | 2 | 2 | 0 | none | ky foster, ralph dawson, zach toliner row 9 : 1918 | none | none | none | none | none row 10 : 1919 | 4 | 1 | 1 | none | cooney checkaye row 11 : 1920 | 0 | 1 | 0 | 14th apfa | ken huffine row 12 : 1921 | 0 | 2 | 0 | 18th apfa | cooney checkaye row 13 : 1922 | 5 | 1 | 3 | none | cooney checkaye row 14 : 1923 | 3 | 4 | 0 | none | cooney checkaye row 15 : 1924 | 3 | 3 | 0 | none | cooney checkaye row 16 : 1925 | 6 | 2 | 3 | none | cooney checkaye row 17 : 1926 | 0 | 1 | 0 | incomplete | none | col : count ( "*" ) row 1 : 13 | select count ( * ) where finish = 'none' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & w & l & t & finish & coach \\
\midrule
0 & 1910 & 11 & 0 & 1 & none & earl ball \\
1 & 1911 & 7 & 1 & 2 & none & earl ball \\
2 & 1912 & 6 & 3 & 2 & none & earl ball \\
3 & 1913 & 8 & 2 & 0 & indiana state champs & earl ball \\
4 & 1914 & 5 & 3 & 1 & none & earl ball \\
5 & 1915 & 8 & 2 & 1 & none & earl ball \\
6 & 1916 & 2 & 7 & 1 & none & f.w. smith \\
7 & 1917 & 2 & 2 & 0 & none & ky foster, ralph dawson, zach toliner \\
8 & 1918 & none & none & none & none & none \\
9 & 1919 & 4 & 1 & 1 & none & cooney checkaye \\
10 & 1920 & 0 & 1 & 0 & 14th apfa & ken huffine \\
11 & 1921 & 0 & 2 & 0 & 18th apfa & cooney checkaye \\
12 & 1922 & 5 & 1 & 3 & none & cooney checkaye \\
13 & 1923 & 3 & 4 & 0 & none & cooney checkaye \\
14 & 1924 & 3 & 3 & 0 & none & cooney checkaye \\
15 & 1925 & 6 & 2 & 3 & none & cooney checkaye \\
16 & 1926 & 0 & 1 & 0 & incomplete & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 13 \\
\bottomrule
\end{tabular}
| select count ( * ) where finish = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>w</th>
<th>l</th>
<th>t</th>
<th>finish</th>
<th>coach</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1910</td>
<td>11</td>
<td>0</td>
<td>1</td>
<td>none</td>
<td>earl ball</td>
</tr>
<tr>
<th>1</th>
<td>1911</td>
<td>7</td>
<td>1</td>
<td>2</td>
<td>none</td>
<td>earl ball</td>
</tr>
<tr>
<th>2</th>
<td>1912</td>
<td>6</td>
<td>3</td>
<td>2</td>
<td>none</td>
<td>earl ball</td>
</tr>
<tr>
<th>3</th>
<td>1913</td>
<td>8</td>
<td>2</td>
<td>0</td>
<td>indiana state champs</td>
<td>earl ball</td>
</tr>
<tr>
<th>4</th>
<td>1914</td>
<td>5</td>
<td>3</td>
<td>1</td>
<td>none</td>
<td>earl ball</td>
</tr>
<tr>
<th>5</th>
<td>1915</td>
<td>8</td>
<td>2</td>
<td>1</td>
<td>none</td>
<td>earl ball</td>
</tr>
<tr>
<th>6</th>
<td>1916</td>
<td>2</td>
<td>7</td>
<td>1</td>
<td>none</td>
<td>f.w. smith</td>
</tr>
<tr>
<th>7</th>
<td>1917</td>
<td>2</td>
<td>2</td>
<td>0</td>
<td>none</td>
<td>ky foster, ralph dawson, zach toliner</td>
</tr>
<tr>
<th>8</th>
<td>1918</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1919</td>
<td>4</td>
<td>1</td>
<td>1</td>
<td>none</td>
<td>cooney checkaye</td>
</tr>
<tr>
<th>10</th>
<td>1920</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>14th apfa</td>
<td>ken huffine</td>
</tr>
<tr>
<th>11</th>
<td>1921</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>18th apfa</td>
<td>cooney checkaye</td>
</tr>
<tr>
<th>12</th>
<td>1922</td>
<td>5</td>
<td>1</td>
<td>3</td>
<td>none</td>
<td>cooney checkaye</td>
</tr>
<tr>
<th>13</th>
<td>1923</td>
<td>3</td>
<td>4</td>
<td>0</td>
<td>none</td>
<td>cooney checkaye</td>
</tr>
<tr>
<th>14</th>
<td>1924</td>
<td>3</td>
<td>3</td>
<td>0</td>
<td>none</td>
<td>cooney checkaye</td>
</tr>
<tr>
<th>15</th>
<td>1925</td>
<td>6</td>
<td>2</td>
<td>3</td>
<td>none</td>
<td>cooney checkaye</td>
</tr>
<tr>
<th>16</th>
<td>1926</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>incomplete</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>13</td>
</tr>
</tbody>
</table> | select count ( * ) where finish = 'none' <table_name> : table | | year | w | l | t | finish | coach |
|---:|-------:|:-----|:-----|:-----|:---------------------|:--------------------------------------|
| 0 | 1910 | 11 | 0 | 1 | none | earl ball |
| 1 | 1911 | 7 | 1 | 2 | none | earl ball |
| 2 | 1912 | 6 | 3 | 2 | none | earl ball |
| 3 | 1913 | 8 | 2 | 0 | indiana state champs | earl ball |
| 4 | 1914 | 5 | 3 | 1 | none | earl ball |
| 5 | 1915 | 8 | 2 | 1 | none | earl ball |
| 6 | 1916 | 2 | 7 | 1 | none | f.w. smith |
| 7 | 1917 | 2 | 2 | 0 | none | ky foster, ralph dawson, zach toliner |
| 8 | 1918 | none | none | none | none | none |
| 9 | 1919 | 4 | 1 | 1 | none | cooney checkaye |
| 10 | 1920 | 0 | 1 | 0 | 14th apfa | ken huffine |
| 11 | 1921 | 0 | 2 | 0 | 18th apfa | cooney checkaye |
| 12 | 1922 | 5 | 1 | 3 | none | cooney checkaye |
| 13 | 1923 | 3 | 4 | 0 | none | cooney checkaye |
| 14 | 1924 | 3 | 3 | 0 | none | cooney checkaye |
| 15 | 1925 | 6 | 2 | 3 | none | cooney checkaye |
| 16 | 1926 | 0 | 1 | 0 | incomplete | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 13 | | [
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] |
select count ( * ) where career = '1985-1993' col : # | player | goals | caps | career row 1 : 1 | landon donovan | 57 | 155 | 2000-present row 2 : 2 | clint dempsey | 36 | 103 | 2004-present row 3 : 3 | eric wynalda | 34 | 106 | 1990-2000 row 4 : 4 | brian mcbride | 30 | 95 | 1993-2006 row 5 : 5 | joe-max moore | 24 | 100 | 1992-2002 row 6 : 6 | jozy altidore | 21 | 67 | 2007-present row 7 : 6 | bruce murray | 21 | 86 | 1985-1993 row 8 : 8 | eddie johnson | 19 | 62 | 2004-present row 9 : 9 | earnie stewart | 17 | 101 | 1990-2004 row 10 : 9 | damarcus beasley | 17 | 114 | 2001-present | col : count ( "*" ) row 1 : 1 | select count ( * ) where career = '1985-1993' <table_name> : table \begin{tabular}{llllll}
\toprule
& # & player & goals & caps & career \\
\midrule
0 & 1 & landon donovan & 57 & 155 & 2000-present \\
1 & 2 & clint dempsey & 36 & 103 & 2004-present \\
2 & 3 & eric wynalda & 34 & 106 & 1990-2000 \\
3 & 4 & brian mcbride & 30 & 95 & 1993-2006 \\
4 & 5 & joe-max moore & 24 & 100 & 1992-2002 \\
5 & 6 & jozy altidore & 21 & 67 & 2007-present \\
6 & 6 & bruce murray & 21 & 86 & 1985-1993 \\
7 & 8 & eddie johnson & 19 & 62 & 2004-present \\
8 & 9 & earnie stewart & 17 & 101 & 1990-2004 \\
9 & 9 & damarcus beasley & 17 & 114 & 2001-present \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where career = '1985-1993' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>player</th>
<th>goals</th>
<th>caps</th>
<th>career</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>landon donovan</td>
<td>57</td>
<td>155</td>
<td>2000-present</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>clint dempsey</td>
<td>36</td>
<td>103</td>
<td>2004-present</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>eric wynalda</td>
<td>34</td>
<td>106</td>
<td>1990-2000</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>brian mcbride</td>
<td>30</td>
<td>95</td>
<td>1993-2006</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>joe-max moore</td>
<td>24</td>
<td>100</td>
<td>1992-2002</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>jozy altidore</td>
<td>21</td>
<td>67</td>
<td>2007-present</td>
</tr>
<tr>
<th>6</th>
<td>6</td>
<td>bruce murray</td>
<td>21</td>
<td>86</td>
<td>1985-1993</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>eddie johnson</td>
<td>19</td>
<td>62</td>
<td>2004-present</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>earnie stewart</td>
<td>17</td>
<td>101</td>
<td>1990-2004</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>damarcus beasley</td>
<td>17</td>
<td>114</td>
<td>2001-present</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 career = '1985-1993' <table_name> : table | | # | player | goals | caps | career |
|---:|----:|:-----------------|--------:|-------:|:-------------|
| 0 | 1 | landon donovan | 57 | 155 | 2000-present |
| 1 | 2 | clint dempsey | 36 | 103 | 2004-present |
| 2 | 3 | eric wynalda | 34 | 106 | 1990-2000 |
| 3 | 4 | brian mcbride | 30 | 95 | 1993-2006 |
| 4 | 5 | joe-max moore | 24 | 100 | 1992-2002 |
| 5 | 6 | jozy altidore | 21 | 67 | 2007-present |
| 6 | 6 | bruce murray | 21 | 86 | 1985-1993 |
| 7 | 8 | eddie johnson | 19 | 62 | 2004-present |
| 8 | 9 | earnie stewart | 17 | 101 | 1990-2004 |
| 9 | 9 | damarcus beasley | 17 | 114 | 2001-present | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where painter = 'palma il giovane' col : painter | composition | drawing | color | expression row 1 : andrea del sarto | 12 | 16 | 9 | 8 row 2 : federico barocci | 14 | 15 | 6 | 10 row 3 : jacopo bassano | 6 | 8 | 17 | 0 row 4 : giovanni bellini | 4 | 6 | 14 | 0 row 5 : sebastian bourdon | 10 | 8 | 8 | 4 row 6 : charles le brun | 16 | 16 | 8 | 16 row 7 : i carracci | 15 | 17 | 13 | 13 row 8 : cavalier d'arpino | 10 | 10 | 6 | 2 row 9 : correggio | 13 | 13 | 15 | 12 row 10 : daniele da volterra | 12 | 15 | 5 | 8 row 11 : abraham van diepenbeeck | 11 | 10 | 14 | 6 row 12 : il domenichino | 15 | 17 | 9 | 17 row 13 : albrecht durer | 8 | 10 | 10 | 8 row 14 : giorgione | 8 | 9 | 18 | 4 row 15 : giovanni da udine | 10 | 8 | 16 | 3 row 16 : giulio romano | 15 | 16 | 4 | 14 row 17 : guercino | 18 | 10 | 10 | 4 row 18 : guido reni | x | 13 | 9 | 12 row 19 : holbein | 9 | 10 | 16 | 3 row 20 : jacob jordaens | 10 | 8 | 16 | 6 row 21 : lucas jordaens | 13 | 12 | 9 | 6 row 22 : giovanni lanfranco | 14 | 13 | 10 | 5 row 23 : leonardo da vinci | 15 | 16 | 4 | 14 row 24 : lucas van leyden | 8 | 6 | 6 | 4 row 25 : michelangelo | 8 | 17 | 4 | 8 row 26 : caravaggio | 6 | 6 | 16 | 0 row 27 : murillo | 6 | 8 | 15 | 4 row 28 : otho venius | 13 | 14 | 10 | 10 row 29 : palma il vecchio | 5 | 6 | 16 | 0 row 30 : palma il giovane | 12 | 9 | 14 | 6 row 31 : il parmigianino | 10 | 15 | 6 | 6 row 32 : gianfrancesco penni | 0 | 15 | 8 | 0 row 33 : perin del vaga | 15 | 16 | 7 | 6 row 34 : sebastiano del piombo | 8 | 13 | 16 | 7 row 35 : primaticcio | 15 | 14 | 7 | 10 row 36 : raphael | 17 | 18 | 12 | 18 row 37 : rembrandt | 15 | 6 | 17 | 12 row 38 : rubens | 18 | 13 | 17 | 17 row 39 : francesco salviati | 13 | 15 | 8 | 8 row 40 : eustache le sueur | 15 | 15 | 4 | 15 row 41 : teniers | 15 | 12 | 13 | 6 row 42 : pietro testa | 11 | 15 | 0 | 6 row 43 : tintoretto | 15 | 14 | 16 | 4 row 44 : titian | 12 | 15 | 18 | 6 row 45 : van dyck | 15 | 10 | 17 | 13 row 46 : vanius | 15 | 15 | 12 | 13 row 47 : veronese | 15 | 10 | 16 | 3 row 48 : taddeo zuccari | 13 | 14 | 10 | 9 row 49 : federico zuccari | 10 | 10 | 8 | 8 | col : count ( "*" ) row 1 : 1 | select count ( * ) where painter = 'palma il giovane' <table_name> : table \begin{tabular}{llllll}
\toprule
& painter & composition & drawing & color & expression \\
\midrule
0 & andrea del sarto & 12 & 16 & 9 & 8 \\
1 & federico barocci & 14 & 15 & 6 & 10 \\
2 & jacopo bassano & 6 & 8 & 17 & 0 \\
3 & giovanni bellini & 4 & 6 & 14 & 0 \\
4 & sebastian bourdon & 10 & 8 & 8 & 4 \\
5 & charles le brun & 16 & 16 & 8 & 16 \\
6 & i carracci & 15 & 17 & 13 & 13 \\
7 & cavalier d'arpino & 10 & 10 & 6 & 2 \\
8 & correggio & 13 & 13 & 15 & 12 \\
9 & daniele da volterra & 12 & 15 & 5 & 8 \\
10 & abraham van diepenbeeck & 11 & 10 & 14 & 6 \\
11 & il domenichino & 15 & 17 & 9 & 17 \\
12 & albrecht durer & 8 & 10 & 10 & 8 \\
13 & giorgione & 8 & 9 & 18 & 4 \\
14 & giovanni da udine & 10 & 8 & 16 & 3 \\
15 & giulio romano & 15 & 16 & 4 & 14 \\
16 & guercino & 18 & 10 & 10 & 4 \\
17 & guido reni & x & 13 & 9 & 12 \\
18 & holbein & 9 & 10 & 16 & 3 \\
19 & jacob jordaens & 10 & 8 & 16 & 6 \\
20 & lucas jordaens & 13 & 12 & 9 & 6 \\
21 & giovanni lanfranco & 14 & 13 & 10 & 5 \\
22 & leonardo da vinci & 15 & 16 & 4 & 14 \\
23 & lucas van leyden & 8 & 6 & 6 & 4 \\
24 & michelangelo & 8 & 17 & 4 & 8 \\
25 & caravaggio & 6 & 6 & 16 & 0 \\
26 & murillo & 6 & 8 & 15 & 4 \\
27 & otho venius & 13 & 14 & 10 & 10 \\
28 & palma il vecchio & 5 & 6 & 16 & 0 \\
29 & palma il giovane & 12 & 9 & 14 & 6 \\
30 & il parmigianino & 10 & 15 & 6 & 6 \\
31 & gianfrancesco penni & 0 & 15 & 8 & 0 \\
32 & perin del vaga & 15 & 16 & 7 & 6 \\
33 & sebastiano del piombo & 8 & 13 & 16 & 7 \\
34 & primaticcio & 15 & 14 & 7 & 10 \\
35 & raphael & 17 & 18 & 12 & 18 \\
36 & rembrandt & 15 & 6 & 17 & 12 \\
37 & rubens & 18 & 13 & 17 & 17 \\
38 & francesco salviati & 13 & 15 & 8 & 8 \\
39 & eustache le sueur & 15 & 15 & 4 & 15 \\
40 & teniers & 15 & 12 & 13 & 6 \\
41 & pietro testa & 11 & 15 & 0 & 6 \\
42 & tintoretto & 15 & 14 & 16 & 4 \\
43 & titian & 12 & 15 & 18 & 6 \\
44 & van dyck & 15 & 10 & 17 & 13 \\
45 & vanius & 15 & 15 & 12 & 13 \\
46 & veronese & 15 & 10 & 16 & 3 \\
47 & taddeo zuccari & 13 & 14 & 10 & 9 \\
48 & federico zuccari & 10 & 10 & 8 & 8 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where painter = 'palma il giovane' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>painter</th>
<th>composition</th>
<th>drawing</th>
<th>color</th>
<th>expression</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>andrea del sarto</td>
<td>12</td>
<td>16</td>
<td>9</td>
<td>8</td>
</tr>
<tr>
<th>1</th>
<td>federico barocci</td>
<td>14</td>
<td>15</td>
<td>6</td>
<td>10</td>
</tr>
<tr>
<th>2</th>
<td>jacopo bassano</td>
<td>6</td>
<td>8</td>
<td>17</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>giovanni bellini</td>
<td>4</td>
<td>6</td>
<td>14</td>
<td>0</td>
</tr>
<tr>
<th>4</th>
<td>sebastian bourdon</td>
<td>10</td>
<td>8</td>
<td>8</td>
<td>4</td>
</tr>
<tr>
<th>5</th>
<td>charles le brun</td>
<td>16</td>
<td>16</td>
<td>8</td>
<td>16</td>
</tr>
<tr>
<th>6</th>
<td>i carracci</td>
<td>15</td>
<td>17</td>
<td>13</td>
<td>13</td>
</tr>
<tr>
<th>7</th>
<td>cavalier d'arpino</td>
<td>10</td>
<td>10</td>
<td>6</td>
<td>2</td>
</tr>
<tr>
<th>8</th>
<td>correggio</td>
<td>13</td>
<td>13</td>
<td>15</td>
<td>12</td>
</tr>
<tr>
<th>9</th>
<td>daniele da volterra</td>
<td>12</td>
<td>15</td>
<td>5</td>
<td>8</td>
</tr>
<tr>
<th>10</th>
<td>abraham van diepenbeeck</td>
<td>11</td>
<td>10</td>
<td>14</td>
<td>6</td>
</tr>
<tr>
<th>11</th>
<td>il domenichino</td>
<td>15</td>
<td>17</td>
<td>9</td>
<td>17</td>
</tr>
<tr>
<th>12</th>
<td>albrecht durer</td>
<td>8</td>
<td>10</td>
<td>10</td>
<td>8</td>
</tr>
<tr>
<th>13</th>
<td>giorgione</td>
<td>8</td>
<td>9</td>
<td>18</td>
<td>4</td>
</tr>
<tr>
<th>14</th>
<td>giovanni da udine</td>
<td>10</td>
<td>8</td>
<td>16</td>
<td>3</td>
</tr>
<tr>
<th>15</th>
<td>giulio romano</td>
<td>15</td>
<td>16</td>
<td>4</td>
<td>14</td>
</tr>
<tr>
<th>16</th>
<td>guercino</td>
<td>18</td>
<td>10</td>
<td>10</td>
<td>4</td>
</tr>
<tr>
<th>17</th>
<td>guido reni</td>
<td>x</td>
<td>13</td>
<td>9</td>
<td>12</td>
</tr>
<tr>
<th>18</th>
<td>holbein</td>
<td>9</td>
<td>10</td>
<td>16</td>
<td>3</td>
</tr>
<tr>
<th>19</th>
<td>jacob jordaens</td>
<td>10</td>
<td>8</td>
<td>16</td>
<td>6</td>
</tr>
<tr>
<th>20</th>
<td>lucas jordaens</td>
<td>13</td>
<td>12</td>
<td>9</td>
<td>6</td>
</tr>
<tr>
<th>21</th>
<td>giovanni lanfranco</td>
<td>14</td>
<td>13</td>
<td>10</td>
<td>5</td>
</tr>
<tr>
<th>22</th>
<td>leonardo da vinci</td>
<td>15</td>
<td>16</td>
<td>4</td>
<td>14</td>
</tr>
<tr>
<th>23</th>
<td>lucas van leyden</td>
<td>8</td>
<td>6</td>
<td>6</td>
<td>4</td>
</tr>
<tr>
<th>24</th>
<td>michelangelo</td>
<td>8</td>
<td>17</td>
<td>4</td>
<td>8</td>
</tr>
<tr>
<th>25</th>
<td>caravaggio</td>
<td>6</td>
<td>6</td>
<td>16</td>
<td>0</td>
</tr>
<tr>
<th>26</th>
<td>murillo</td>
<td>6</td>
<td>8</td>
<td>15</td>
<td>4</td>
</tr>
<tr>
<th>27</th>
<td>otho venius</td>
<td>13</td>
<td>14</td>
<td>10</td>
<td>10</td>
</tr>
<tr>
<th>28</th>
<td>palma il vecchio</td>
<td>5</td>
<td>6</td>
<td>16</td>
<td>0</td>
</tr>
<tr>
<th>29</th>
<td>palma il giovane</td>
<td>12</td>
<td>9</td>
<td>14</td>
<td>6</td>
</tr>
<tr>
<th>30</th>
<td>il parmigianino</td>
<td>10</td>
<td>15</td>
<td>6</td>
<td>6</td>
</tr>
<tr>
<th>31</th>
<td>gianfrancesco penni</td>
<td>0</td>
<td>15</td>
<td>8</td>
<td>0</td>
</tr>
<tr>
<th>32</th>
<td>perin del vaga</td>
<td>15</td>
<td>16</td>
<td>7</td>
<td>6</td>
</tr>
<tr>
<th>33</th>
<td>sebastiano del piombo</td>
<td>8</td>
<td>13</td>
<td>16</td>
<td>7</td>
</tr>
<tr>
<th>34</th>
<td>primaticcio</td>
<td>15</td>
<td>14</td>
<td>7</td>
<td>10</td>
</tr>
<tr>
<th>35</th>
<td>raphael</td>
<td>17</td>
<td>18</td>
<td>12</td>
<td>18</td>
</tr>
<tr>
<th>36</th>
<td>rembrandt</td>
<td>15</td>
<td>6</td>
<td>17</td>
<td>12</td>
</tr>
<tr>
<th>37</th>
<td>rubens</td>
<td>18</td>
<td>13</td>
<td>17</td>
<td>17</td>
</tr>
<tr>
<th>38</th>
<td>francesco salviati</td>
<td>13</td>
<td>15</td>
<td>8</td>
<td>8</td>
</tr>
<tr>
<th>39</th>
<td>eustache le sueur</td>
<td>15</td>
<td>15</td>
<td>4</td>
<td>15</td>
</tr>
<tr>
<th>40</th>
<td>teniers</td>
<td>15</td>
<td>12</td>
<td>13</td>
<td>6</td>
</tr>
<tr>
<th>41</th>
<td>pietro testa</td>
<td>11</td>
<td>15</td>
<td>0</td>
<td>6</td>
</tr>
<tr>
<th>42</th>
<td>tintoretto</td>
<td>15</td>
<td>14</td>
<td>16</td>
<td>4</td>
</tr>
<tr>
<th>43</th>
<td>titian</td>
<td>12</td>
<td>15</td>
<td>18</td>
<td>6</td>
</tr>
<tr>
<th>44</th>
<td>van dyck</td>
<td>15</td>
<td>10</td>
<td>17</td>
<td>13</td>
</tr>
<tr>
<th>45</th>
<td>vanius</td>
<td>15</td>
<td>15</td>
<td>12</td>
<td>13</td>
</tr>
<tr>
<th>46</th>
<td>veronese</td>
<td>15</td>
<td>10</td>
<td>16</td>
<td>3</td>
</tr>
<tr>
<th>47</th>
<td>taddeo zuccari</td>
<td>13</td>
<td>14</td>
<td>10</td>
<td>9</td>
</tr>
<tr>
<th>48</th>
<td>federico zuccari</td>
<td>10</td>
<td>10</td>
<td>8</td>
<td>8</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 painter = 'palma il giovane' <table_name> : table | | painter | composition | drawing | color | expression |
|---:|:------------------------|:--------------|----------:|--------:|-------------:|
| 0 | andrea del sarto | 12 | 16 | 9 | 8 |
| 1 | federico barocci | 14 | 15 | 6 | 10 |
| 2 | jacopo bassano | 6 | 8 | 17 | 0 |
| 3 | giovanni bellini | 4 | 6 | 14 | 0 |
| 4 | sebastian bourdon | 10 | 8 | 8 | 4 |
| 5 | charles le brun | 16 | 16 | 8 | 16 |
| 6 | i carracci | 15 | 17 | 13 | 13 |
| 7 | cavalier d'arpino | 10 | 10 | 6 | 2 |
| 8 | correggio | 13 | 13 | 15 | 12 |
| 9 | daniele da volterra | 12 | 15 | 5 | 8 |
| 10 | abraham van diepenbeeck | 11 | 10 | 14 | 6 |
| 11 | il domenichino | 15 | 17 | 9 | 17 |
| 12 | albrecht durer | 8 | 10 | 10 | 8 |
| 13 | giorgione | 8 | 9 | 18 | 4 |
| 14 | giovanni da udine | 10 | 8 | 16 | 3 |
| 15 | giulio romano | 15 | 16 | 4 | 14 |
| 16 | guercino | 18 | 10 | 10 | 4 |
| 17 | guido reni | x | 13 | 9 | 12 |
| 18 | holbein | 9 | 10 | 16 | 3 |
| 19 | jacob jordaens | 10 | 8 | 16 | 6 |
| 20 | lucas jordaens | 13 | 12 | 9 | 6 |
| 21 | giovanni lanfranco | 14 | 13 | 10 | 5 |
| 22 | leonardo da vinci | 15 | 16 | 4 | 14 |
| 23 | lucas van leyden | 8 | 6 | 6 | 4 |
| 24 | michelangelo | 8 | 17 | 4 | 8 |
| 25 | caravaggio | 6 | 6 | 16 | 0 |
| 26 | murillo | 6 | 8 | 15 | 4 |
| 27 | otho venius | 13 | 14 | 10 | 10 |
| 28 | palma il vecchio | 5 | 6 | 16 | 0 |
| 29 | palma il giovane | 12 | 9 | 14 | 6 |
| 30 | il parmigianino | 10 | 15 | 6 | 6 |
| 31 | gianfrancesco penni | 0 | 15 | 8 | 0 |
| 32 | perin del vaga | 15 | 16 | 7 | 6 |
| 33 | sebastiano del piombo | 8 | 13 | 16 | 7 |
| 34 | primaticcio | 15 | 14 | 7 | 10 |
| 35 | raphael | 17 | 18 | 12 | 18 |
| 36 | rembrandt | 15 | 6 | 17 | 12 |
| 37 | rubens | 18 | 13 | 17 | 17 |
| 38 | francesco salviati | 13 | 15 | 8 | 8 |
| 39 | eustache le sueur | 15 | 15 | 4 | 15 |
| 40 | teniers | 15 | 12 | 13 | 6 |
| 41 | pietro testa | 11 | 15 | 0 | 6 |
| 42 | tintoretto | 15 | 14 | 16 | 4 |
| 43 | titian | 12 | 15 | 18 | 6 |
| 44 | van dyck | 15 | 10 | 17 | 13 |
| 45 | vanius | 15 | 15 | 12 | 13 |
| 46 | veronese | 15 | 10 | 16 | 3 |
| 47 | taddeo zuccari | 13 | 14 | 10 | 9 |
| 48 | federico zuccari | 10 | 10 | 8 | 8 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select category where speed (mph) = 541 col : category | speed (km/h) | speed (mph) | vehicle | pilot | date row 1 : rocket-powered aircraft | 7258.0 | 4510.0 | north american x-15 | william j. knight | 1967-10-03 00:00:00 row 2 : manned air-breathing craft | 3530.0 | 2194.0 | lockheed sr-71 blackbird | eldon w. joersz | 1976-07-28 00:00:00 row 3 : propeller-driven aircraft | 870.0 | 541.0 | tupolev tu-114 | ivan soukhomline | 1960-01-01 00:00:00 row 4 : piston-engined propeller-driven aircraft | 850.1 | 528.33 | grumman f8f bearcat rare bear (n777l) | lyle shelton | 1989-08-21 00:00:00 row 5 : helicopter | 401.0 | 249.1 | westland lynx 800 g-lynx | john egginton | 1986-08-11 00:00:00 row 6 : glider (sailplane) | 306.8 | 190.6 | schempp-hirth nimbus-4dm | klaus ohlmann and matias garcia mazzaro | 2006-12-22 00:00:00 row 7 : human-powered aircraft | 32.0 | 19.8 | mit monarch b | frank scarabino | 1984-05-01 00:00:00 | col : category row 1 : propeller-driven aircraft | select category where speed (mph) = 541 <table_name> : table \begin{tabular}{lllllll}
\toprule
& category & speed (km/h) & speed (mph) & vehicle & pilot & date \\
\midrule
0 & rocket-powered aircraft & 7258.0 & 4510.0 & north american x-15 & william j. knight & 1967-10-03 00:00:00 \\
1 & manned air-breathing craft & 3530.0 & 2194.0 & lockheed sr-71 blackbird & eldon w. joersz & 1976-07-28 00:00:00 \\
2 & propeller-driven aircraft & 870.0 & 541.0 & tupolev tu-114 & ivan soukhomline & 1960-01-01 00:00:00 \\
3 & piston-engined propeller-driven aircraft & 850.1 & 528.33 & grumman f8f bearcat rare bear (n777l) & lyle shelton & 1989-08-21 00:00:00 \\
4 & helicopter & 401.0 & 249.1 & westland lynx 800 g-lynx & john egginton & 1986-08-11 00:00:00 \\
5 & glider (sailplane) & 306.8 & 190.6 & schempp-hirth nimbus-4dm & klaus ohlmann and matias garcia mazzaro & 2006-12-22 00:00:00 \\
6 & human-powered aircraft & 32.0 & 19.8 & mit monarch b & frank scarabino & 1984-05-01 00:00:00 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& category \\
\midrule
0 & propeller-driven aircraft \\
\bottomrule
\end{tabular}
| select category where speed (mph) = 541 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>category</th>
<th>speed (km/h)</th>
<th>speed (mph)</th>
<th>vehicle</th>
<th>pilot</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>rocket-powered aircraft</td>
<td>7258.0</td>
<td>4510.0</td>
<td>north american x-15</td>
<td>william j. knight</td>
<td>1967-10-03 00:00:00</td>
</tr>
<tr>
<th>1</th>
<td>manned air-breathing craft</td>
<td>3530.0</td>
<td>2194.0</td>
<td>lockheed sr-71 blackbird</td>
<td>eldon w. joersz</td>
<td>1976-07-28 00:00:00</td>
</tr>
<tr>
<th>2</th>
<td>propeller-driven aircraft</td>
<td>870.0</td>
<td>541.0</td>
<td>tupolev tu-114</td>
<td>ivan soukhomline</td>
<td>1960-01-01 00:00:00</td>
</tr>
<tr>
<th>3</th>
<td>piston-engined propeller-driven aircraft</td>
<td>850.1</td>
<td>528.33</td>
<td>grumman f8f bearcat rare bear (n777l)</td>
<td>lyle shelton</td>
<td>1989-08-21 00:00:00</td>
</tr>
<tr>
<th>4</th>
<td>helicopter</td>
<td>401.0</td>
<td>249.1</td>
<td>westland lynx 800 g-lynx</td>
<td>john egginton</td>
<td>1986-08-11 00:00:00</td>
</tr>
<tr>
<th>5</th>
<td>glider (sailplane)</td>
<td>306.8</td>
<td>190.6</td>
<td>schempp-hirth nimbus-4dm</td>
<td>klaus ohlmann and matias garcia mazzaro</td>
<td>2006-12-22 00:00:00</td>
</tr>
<tr>
<th>6</th>
<td>human-powered aircraft</td>
<td>32.0</td>
<td>19.8</td>
<td>mit monarch b</td>
<td>frank scarabino</td>
<td>1984-05-01 00:00:00</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>category</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>propeller-driven aircraft</td>
</tr>
</tbody>
</table> | select category where speed (mph) = 541 <table_name> : table | | category | speed (km/h) | speed (mph) | vehicle | pilot | date |
|---:|:-----------------------------------------|---------------:|--------------:|:--------------------------------------|:----------------------------------------|:--------------------|
| 0 | rocket-powered aircraft | 7258 | 4510 | north american x-15 | william j. knight | 1967-10-03 00:00:00 |
| 1 | manned air-breathing craft | 3530 | 2194 | lockheed sr-71 blackbird | eldon w. joersz | 1976-07-28 00:00:00 |
| 2 | propeller-driven aircraft | 870 | 541 | tupolev tu-114 | ivan soukhomline | 1960-01-01 00:00:00 |
| 3 | piston-engined propeller-driven aircraft | 850.1 | 528.33 | grumman f8f bearcat rare bear (n777l) | lyle shelton | 1989-08-21 00:00:00 |
| 4 | helicopter | 401 | 249.1 | westland lynx 800 g-lynx | john egginton | 1986-08-11 00:00:00 |
| 5 | glider (sailplane) | 306.8 | 190.6 | schempp-hirth nimbus-4dm | klaus ohlmann and matias garcia mazzaro | 2006-12-22 00:00:00 |
| 6 | human-powered aircraft | 32 | 19.8 | mit monarch b | frank scarabino | 1984-05-01 00:00:00 | | | | category |
|---:|:--------------------------|
| 0 | propeller-driven aircraft | | [
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select count ( * ) where charter = 'none' col : school name | city | grades | establishment | charter row 1 : aliamanu intermediate school | honolulu | 7-8 | 1958 | none row 2 : anuenue school | honolulu | k-12 | 1958 | charter row 3 : central middle school | honolulu | 6-8 | 1926 | none row 4 : dole middle school | honolulu | 6-8 | 1955 | none row 5 : halau ku mana ncpcs | honolulu | 6-12 | 2000 | charter row 6 : jarrett middle school | honolulu | 6-8 | 1955 | none row 7 : kaimuki middle school | honolulu | 6-8 | 1939 | none row 8 : kalakaua middle school | honolulu | 6-8 | 1928 | none row 9 : kawananakoa middle school | honolulu | 6-8 | 1927 | none row 10 : moanalua middle school | honolulu | 7-8 | 1967 | none row 11 : niu valley middle school | honolulu | 6-8 | 1955 | none row 12 : stevenson middle school | honolulu | 6-8 | 1937 | none row 13 : washington middle school | honolulu | 6-8 | 1854 | none | col : count ( "*" ) row 1 : 11 | select count ( * ) where charter = 'none' <table_name> : table \begin{tabular}{llllll}
\toprule
& school name & city & grades & establishment & charter \\
\midrule
0 & aliamanu intermediate school & honolulu & 7-8 & 1958 & none \\
1 & anuenue school & honolulu & k-12 & 1958 & charter \\
2 & central middle school & honolulu & 6-8 & 1926 & none \\
3 & dole middle school & honolulu & 6-8 & 1955 & none \\
4 & halau ku mana ncpcs & honolulu & 6-12 & 2000 & charter \\
5 & jarrett middle school & honolulu & 6-8 & 1955 & none \\
6 & kaimuki middle school & honolulu & 6-8 & 1939 & none \\
7 & kalakaua middle school & honolulu & 6-8 & 1928 & none \\
8 & kawananakoa middle school & honolulu & 6-8 & 1927 & none \\
9 & moanalua middle school & honolulu & 7-8 & 1967 & none \\
10 & niu valley middle school & honolulu & 6-8 & 1955 & none \\
11 & stevenson middle school & honolulu & 6-8 & 1937 & none \\
12 & washington middle school & honolulu & 6-8 & 1854 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 11 \\
\bottomrule
\end{tabular}
| select count ( * ) where charter = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>school name</th>
<th>city</th>
<th>grades</th>
<th>establishment</th>
<th>charter</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>aliamanu intermediate school</td>
<td>honolulu</td>
<td>7-8</td>
<td>1958</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>anuenue school</td>
<td>honolulu</td>
<td>k-12</td>
<td>1958</td>
<td>charter</td>
</tr>
<tr>
<th>2</th>
<td>central middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1926</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>dole middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1955</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>halau ku mana ncpcs</td>
<td>honolulu</td>
<td>6-12</td>
<td>2000</td>
<td>charter</td>
</tr>
<tr>
<th>5</th>
<td>jarrett middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1955</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>kaimuki middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1939</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>kalakaua middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1928</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>kawananakoa middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1927</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>moanalua middle school</td>
<td>honolulu</td>
<td>7-8</td>
<td>1967</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>niu valley middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1955</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>stevenson middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1937</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>washington middle school</td>
<td>honolulu</td>
<td>6-8</td>
<td>1854</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>11</td>
</tr>
</tbody>
</table> | select count ( * ) where charter = 'none' <table_name> : table | | school name | city | grades | establishment | charter |
|---:|:-----------------------------|:---------|:---------|----------------:|:----------|
| 0 | aliamanu intermediate school | honolulu | 7-8 | 1958 | none |
| 1 | anuenue school | honolulu | k-12 | 1958 | charter |
| 2 | central middle school | honolulu | 6-8 | 1926 | none |
| 3 | dole middle school | honolulu | 6-8 | 1955 | none |
| 4 | halau ku mana ncpcs | honolulu | 6-12 | 2000 | charter |
| 5 | jarrett middle school | honolulu | 6-8 | 1955 | none |
| 6 | kaimuki middle school | honolulu | 6-8 | 1939 | none |
| 7 | kalakaua middle school | honolulu | 6-8 | 1928 | none |
| 8 | kawananakoa middle school | honolulu | 6-8 | 1927 | none |
| 9 | moanalua middle school | honolulu | 7-8 | 1967 | none |
| 10 | niu valley middle school | honolulu | 6-8 | 1955 | none |
| 11 | stevenson middle school | honolulu | 6-8 | 1937 | none |
| 12 | washington middle school | honolulu | 6-8 | 1854 | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 11 | | [
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select year where event = '10,000 m' col : year | competition | venue | position | event | notes row 1 : 1990 | central american and caribbean games | mexico city, mexico | 1st | 3000 m s'chase | none row 2 : 1991 | pan american games | havana city, cuba | 6th | 3000 m s'chase | none row 3 : 1992 | olympic games | barcelona, spain | 6th | 10,000 m | none row 4 : 1993 | world championships | stuttgart, germany | 9th | 10,000 m | none row 5 : 1994 | world half marathon championships | oslo, norway | 2nd | half marathon | 1:00:28 pb row 6 : 1994 | new york city marathon | new york city, united states | 1st | marathon | none row 7 : 1994 | london marathon | london, england | 3rd | marathon | none row 8 : 1995 | world championships | gothenburg, sweden | 13th | 10,000 m | none row 9 : 1995 | new york city marathon | new york city, united states | 1st | marathon | none row 10 : 1996 | olympic games | atlanta, united states | 6th | marathon | none row 11 : 1997 | new york city marathon | new york city, united states | 5th | marathon | none row 12 : 1997 | boston marathon | boston, united states | 4th | marathon | none | col : year row 1 : 1992 row 2 : 1993 row 3 : 1995 | select year where event = '10,000 m' <table_name> : table \begin{tabular}{lllllll}
\toprule
& year & competition & venue & position & event & notes \\
\midrule
0 & 1990 & central american and caribbean games & mexico city, mexico & 1st & 3000 m s'chase & none \\
1 & 1991 & pan american games & havana city, cuba & 6th & 3000 m s'chase & none \\
2 & 1992 & olympic games & barcelona, spain & 6th & 10,000 m & none \\
3 & 1993 & world championships & stuttgart, germany & 9th & 10,000 m & none \\
4 & 1994 & world half marathon championships & oslo, norway & 2nd & half marathon & 1:00:28 pb \\
5 & 1994 & new york city marathon & new york city, united states & 1st & marathon & none \\
6 & 1994 & london marathon & london, england & 3rd & marathon & none \\
7 & 1995 & world championships & gothenburg, sweden & 13th & 10,000 m & none \\
8 & 1995 & new york city marathon & new york city, united states & 1st & marathon & none \\
9 & 1996 & olympic games & atlanta, united states & 6th & marathon & none \\
10 & 1997 & new york city marathon & new york city, united states & 5th & marathon & none \\
11 & 1997 & boston marathon & boston, united states & 4th & marathon & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1992 \\
1 & 1993 \\
2 & 1995 \\
\bottomrule
\end{tabular}
| select year where event = '10,000 m' <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>1990</td>
<td>central american and caribbean games</td>
<td>mexico city, mexico</td>
<td>1st</td>
<td>3000 m s'chase</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1991</td>
<td>pan american games</td>
<td>havana city, cuba</td>
<td>6th</td>
<td>3000 m s'chase</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1992</td>
<td>olympic games</td>
<td>barcelona, spain</td>
<td>6th</td>
<td>10,000 m</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1993</td>
<td>world championships</td>
<td>stuttgart, germany</td>
<td>9th</td>
<td>10,000 m</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1994</td>
<td>world half marathon championships</td>
<td>oslo, norway</td>
<td>2nd</td>
<td>half marathon</td>
<td>1:00:28 pb</td>
</tr>
<tr>
<th>5</th>
<td>1994</td>
<td>new york city marathon</td>
<td>new york city, united states</td>
<td>1st</td>
<td>marathon</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1994</td>
<td>london marathon</td>
<td>london, england</td>
<td>3rd</td>
<td>marathon</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1995</td>
<td>world championships</td>
<td>gothenburg, sweden</td>
<td>13th</td>
<td>10,000 m</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1995</td>
<td>new york city marathon</td>
<td>new york city, united states</td>
<td>1st</td>
<td>marathon</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1996</td>
<td>olympic games</td>
<td>atlanta, united states</td>
<td>6th</td>
<td>marathon</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>1997</td>
<td>new york city marathon</td>
<td>new york city, united states</td>
<td>5th</td>
<td>marathon</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>1997</td>
<td>boston marathon</td>
<td>boston, united states</td>
<td>4th</td>
<td>marathon</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>1992</td>
</tr>
<tr>
<th>1</th>
<td>1993</td>
</tr>
<tr>
<th>2</th>
<td>1995</td>
</tr>
</tbody>
</table> | select year where event = '10,000 m' <table_name> : table | | year | competition | venue | position | event | notes |
|---:|-------:|:-------------------------------------|:-----------------------------|:-----------|:---------------|:-----------|
| 0 | 1990 | central american and caribbean games | mexico city, mexico | 1st | 3000 m s'chase | none |
| 1 | 1991 | pan american games | havana city, cuba | 6th | 3000 m s'chase | none |
| 2 | 1992 | olympic games | barcelona, spain | 6th | 10,000 m | none |
| 3 | 1993 | world championships | stuttgart, germany | 9th | 10,000 m | none |
| 4 | 1994 | world half marathon championships | oslo, norway | 2nd | half marathon | 1:00:28 pb |
| 5 | 1994 | new york city marathon | new york city, united states | 1st | marathon | none |
| 6 | 1994 | london marathon | london, england | 3rd | marathon | none |
| 7 | 1995 | world championships | gothenburg, sweden | 13th | 10,000 m | none |
| 8 | 1995 | new york city marathon | new york city, united states | 1st | marathon | none |
| 9 | 1996 | olympic games | atlanta, united states | 6th | marathon | none |
| 10 | 1997 | new york city marathon | new york city, united states | 5th | marathon | none |
| 11 | 1997 | boston marathon | boston, united states | 4th | marathon | none | | | | year |
|---:|-------:|
| 0 | 1992 |
| 1 | 1993 |
| 2 | 1995 | | [
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select count ( notes ) where notes = 'none' col : year | film | role | notes row 1 : 1976 | liebesfallen | liane bruckner | none row 2 : 1976 | unser stiller mann | regina | none row 3 : 1979 | bildnis einer trinkerin | singer in a taxi drivers' bar | none row 4 : 1979 | cha-cha | none | none row 5 : 1983 | pankow '95 | jungfrau maria | none row 6 : 1996 | lilien in der bank | suzanne | none row 7 : 2000 | vasilisa | the witch | none row 8 : 2004 | 7 dwarves - men alone in the wood | the evil queen | hagen's daughter cosma played snow white row 9 : 2006 | 7 zwerge - der wald ist nicht genug | the evil queen | hagen's daughter cosma played snow white | col : count ( "notes" ) row 1 : 7 | select count ( notes ) where notes = 'none' <table_name> : table \begin{tabular}{lllll}
\toprule
& year & film & role & notes \\
\midrule
0 & 1976 & liebesfallen & liane bruckner & none \\
1 & 1976 & unser stiller mann & regina & none \\
2 & 1979 & bildnis einer trinkerin & singer in a taxi drivers' bar & none \\
3 & 1979 & cha-cha & none & none \\
4 & 1983 & pankow '95 & jungfrau maria & none \\
5 & 1996 & lilien in der bank & suzanne & none \\
6 & 2000 & vasilisa & the witch & none \\
7 & 2004 & 7 dwarves - men alone in the wood & the evil queen & hagen's daughter cosma played snow white \\
8 & 2006 & 7 zwerge - der wald ist nicht genug & the evil queen & hagen's daughter cosma played snow white \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "notes" ) \\
\midrule
0 & 7 \\
\bottomrule
\end{tabular}
| select count ( notes ) where notes = 'none' <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>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1976</td>
<td>liebesfallen</td>
<td>liane bruckner</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1976</td>
<td>unser stiller mann</td>
<td>regina</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1979</td>
<td>bildnis einer trinkerin</td>
<td>singer in a taxi drivers' bar</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1979</td>
<td>cha-cha</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1983</td>
<td>pankow '95</td>
<td>jungfrau maria</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1996</td>
<td>lilien in der bank</td>
<td>suzanne</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2000</td>
<td>vasilisa</td>
<td>the witch</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>2004</td>
<td>7 dwarves - men alone in the wood</td>
<td>the evil queen</td>
<td>hagen's daughter cosma played snow white</td>
</tr>
<tr>
<th>8</th>
<td>2006</td>
<td>7 zwerge - der wald ist nicht genug</td>
<td>the evil queen</td>
<td>hagen's daughter cosma played snow white</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "notes" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
</tbody>
</table> | select count ( notes ) where notes = 'none' <table_name> : table | | year | film | role | notes |
|---:|-------:|:------------------------------------|:------------------------------|:-----------------------------------------|
| 0 | 1976 | liebesfallen | liane bruckner | none |
| 1 | 1976 | unser stiller mann | regina | none |
| 2 | 1979 | bildnis einer trinkerin | singer in a taxi drivers' bar | none |
| 3 | 1979 | cha-cha | none | none |
| 4 | 1983 | pankow '95 | jungfrau maria | none |
| 5 | 1996 | lilien in der bank | suzanne | none |
| 6 | 2000 | vasilisa | the witch | none |
| 7 | 2004 | 7 dwarves - men alone in the wood | the evil queen | hagen's daughter cosma played snow white |
| 8 | 2006 | 7 zwerge - der wald ist nicht genug | the evil queen | hagen's daughter cosma played snow white | | | | count ( "notes" ) |
|---:|--------------------:|
| 0 | 7 | | [
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select count ( * ) where team = 'mexico' col : rank | cyclist | team | laps down | notes row 1 : 1 | iryna shpylova | ukraine | none | q row 2 : 2 | jessie daams | belgium | none | q row 3 : 3 | eunmi park | south korea | -1 | q row 4 : 4 | evgeniya romanyuta | russia | -1 | q row 5 : 5 | andrea wolfer | switzerland | -1 | q row 6 : 6 | giorgia bronzini | italy | -1 | q row 7 : 7 | leire olaberria dorronsoro | spain | -1 | q row 8 : 8 | joanne kiesanowski | new zealand | -1 | q row 9 : 9 | dulce pliego | mexico | -1 | q row 10 : 10 | jessie maclean | verducci breakaway racing | -1 | q row 11 : 11 | lisa brennauer | germany | -1 | q row 12 : 12 | ashlee ankudinoff | australia | -1 | q row 13 : 13 | wan yiu jamie wong | hong kong | -1 | none row 14 : 14 | lauren franges | united states | -1 | none row 15 : 15 | skye lee armstrong | rodin | -1 | none row 16 : 16 | rosy mccall | gis | -1 | none row 17 : 17 | fatehah mustapa | malaysia | -1 | none row 18 : 18 | yekatsiryna barazna | belarus | -1 | none | col : count ( "*" ) row 1 : 1 | select count ( * ) where team = 'mexico' <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & cyclist & team & laps down & notes \\
\midrule
0 & 1 & iryna shpylova & ukraine & none & q \\
1 & 2 & jessie daams & belgium & none & q \\
2 & 3 & eunmi park & south korea & -1 & q \\
3 & 4 & evgeniya romanyuta & russia & -1 & q \\
4 & 5 & andrea wolfer & switzerland & -1 & q \\
5 & 6 & giorgia bronzini & italy & -1 & q \\
6 & 7 & leire olaberria dorronsoro & spain & -1 & q \\
7 & 8 & joanne kiesanowski & new zealand & -1 & q \\
8 & 9 & dulce pliego & mexico & -1 & q \\
9 & 10 & jessie maclean & verducci breakaway racing & -1 & q \\
10 & 11 & lisa brennauer & germany & -1 & q \\
11 & 12 & ashlee ankudinoff & australia & -1 & q \\
12 & 13 & wan yiu jamie wong & hong kong & -1 & none \\
13 & 14 & lauren franges & united states & -1 & none \\
14 & 15 & skye lee armstrong & rodin & -1 & none \\
15 & 16 & rosy mccall & gis & -1 & none \\
16 & 17 & fatehah mustapa & malaysia & -1 & none \\
17 & 18 & yekatsiryna barazna & belarus & -1 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where team = 'mexico' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>cyclist</th>
<th>team</th>
<th>laps down</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>iryna shpylova</td>
<td>ukraine</td>
<td>none</td>
<td>q</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>jessie daams</td>
<td>belgium</td>
<td>none</td>
<td>q</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>eunmi park</td>
<td>south korea</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>evgeniya romanyuta</td>
<td>russia</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>andrea wolfer</td>
<td>switzerland</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>giorgia bronzini</td>
<td>italy</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>leire olaberria dorronsoro</td>
<td>spain</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>joanne kiesanowski</td>
<td>new zealand</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>dulce pliego</td>
<td>mexico</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>jessie maclean</td>
<td>verducci breakaway racing</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>lisa brennauer</td>
<td>germany</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>ashlee ankudinoff</td>
<td>australia</td>
<td>-1</td>
<td>q</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>wan yiu jamie wong</td>
<td>hong kong</td>
<td>-1</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>lauren franges</td>
<td>united states</td>
<td>-1</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>skye lee armstrong</td>
<td>rodin</td>
<td>-1</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>rosy mccall</td>
<td>gis</td>
<td>-1</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>fatehah mustapa</td>
<td>malaysia</td>
<td>-1</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>yekatsiryna barazna</td>
<td>belarus</td>
<td>-1</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 team = 'mexico' <table_name> : table | | rank | cyclist | team | laps down | notes |
|---:|-------:|:---------------------------|:--------------------------|:------------|:--------|
| 0 | 1 | iryna shpylova | ukraine | none | q |
| 1 | 2 | jessie daams | belgium | none | q |
| 2 | 3 | eunmi park | south korea | -1 | q |
| 3 | 4 | evgeniya romanyuta | russia | -1 | q |
| 4 | 5 | andrea wolfer | switzerland | -1 | q |
| 5 | 6 | giorgia bronzini | italy | -1 | q |
| 6 | 7 | leire olaberria dorronsoro | spain | -1 | q |
| 7 | 8 | joanne kiesanowski | new zealand | -1 | q |
| 8 | 9 | dulce pliego | mexico | -1 | q |
| 9 | 10 | jessie maclean | verducci breakaway racing | -1 | q |
| 10 | 11 | lisa brennauer | germany | -1 | q |
| 11 | 12 | ashlee ankudinoff | australia | -1 | q |
| 12 | 13 | wan yiu jamie wong | hong kong | -1 | none |
| 13 | 14 | lauren franges | united states | -1 | none |
| 14 | 15 | skye lee armstrong | rodin | -1 | none |
| 15 | 16 | rosy mccall | gis | -1 | none |
| 16 | 17 | fatehah mustapa | malaysia | -1 | none |
| 17 | 18 | yekatsiryna barazna | belarus | -1 | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( * ) where airdate > airdate col : episode no. | airdate | viewers | bbc three weekly ranking | multichannels rank row 1 : 1 | 25 april 2013 | 979,000 | 2 | 9 row 2 : 2 | 2 may 2013 | 978,000 | 1 | 11 row 3 : 3 | 9 may 2013 | 885,000 | 1 | 11 row 4 : 4 | 16 may 2013 | 880,000 | 1 | 13 row 5 : 5 | 23 may 2013 | 1,092,000 | 1 | 5 row 6 : 6 | 30 may 2013 | 1,094,000 | 1 | 3 row 7 : 7 | 6 june 2013 | 975,000 | 2 | 6 row 8 : 8 | 13 june 2013 | 840,000 | 5 | 19 row 9 : 9 | 20 june 2013 | 1,204,000 | 6 | 9 row 10 : 10 | 27 june 2013 | 730,000 | none | 28 row 11 : 11 | 4 july 2013 | none | none | none row 12 : 12 | 11 july 2013 | none | none | none | col : count ( "*" ) row 1 : 0 | select count ( * ) where airdate > airdate <table_name> : table \begin{tabular}{llllll}
\toprule
& episode no. & airdate & viewers & bbc three weekly ranking & multichannels rank \\
\midrule
0 & 1 & 25 april 2013 & 979,000 & 2 & 9 \\
1 & 2 & 2 may 2013 & 978,000 & 1 & 11 \\
2 & 3 & 9 may 2013 & 885,000 & 1 & 11 \\
3 & 4 & 16 may 2013 & 880,000 & 1 & 13 \\
4 & 5 & 23 may 2013 & 1,092,000 & 1 & 5 \\
5 & 6 & 30 may 2013 & 1,094,000 & 1 & 3 \\
6 & 7 & 6 june 2013 & 975,000 & 2 & 6 \\
7 & 8 & 13 june 2013 & 840,000 & 5 & 19 \\
8 & 9 & 20 june 2013 & 1,204,000 & 6 & 9 \\
9 & 10 & 27 june 2013 & 730,000 & none & 28 \\
10 & 11 & 4 july 2013 & none & none & none \\
11 & 12 & 11 july 2013 & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where airdate > airdate <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>episode no.</th>
<th>airdate</th>
<th>viewers</th>
<th>bbc three weekly ranking</th>
<th>multichannels rank</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>25 april 2013</td>
<td>979,000</td>
<td>2</td>
<td>9</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2 may 2013</td>
<td>978,000</td>
<td>1</td>
<td>11</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>9 may 2013</td>
<td>885,000</td>
<td>1</td>
<td>11</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>16 may 2013</td>
<td>880,000</td>
<td>1</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>23 may 2013</td>
<td>1,092,000</td>
<td>1</td>
<td>5</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>30 may 2013</td>
<td>1,094,000</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>6 june 2013</td>
<td>975,000</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>13 june 2013</td>
<td>840,000</td>
<td>5</td>
<td>19</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>20 june 2013</td>
<td>1,204,000</td>
<td>6</td>
<td>9</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>27 june 2013</td>
<td>730,000</td>
<td>none</td>
<td>28</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>4 july 2013</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>11 july 2013</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>0</td>
</tr>
</tbody>
</table> | select count ( * ) where airdate > airdate <table_name> : table | | episode no. | airdate | viewers | bbc three weekly ranking | multichannels rank |
|---:|--------------:|:--------------|:----------|:---------------------------|:---------------------|
| 0 | 1 | 25 april 2013 | 979,000 | 2 | 9 |
| 1 | 2 | 2 may 2013 | 978,000 | 1 | 11 |
| 2 | 3 | 9 may 2013 | 885,000 | 1 | 11 |
| 3 | 4 | 16 may 2013 | 880,000 | 1 | 13 |
| 4 | 5 | 23 may 2013 | 1,092,000 | 1 | 5 |
| 5 | 6 | 30 may 2013 | 1,094,000 | 1 | 3 |
| 6 | 7 | 6 june 2013 | 975,000 | 2 | 6 |
| 7 | 8 | 13 june 2013 | 840,000 | 5 | 19 |
| 8 | 9 | 20 june 2013 | 1,204,000 | 6 | 9 |
| 9 | 10 | 27 june 2013 | 730,000 | none | 28 |
| 10 | 11 | 4 july 2013 | none | none | none |
| 11 | 12 | 11 july 2013 | none | none | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( notes ) where name = 'ferdinando vicari' col : rank | name | nationality | time | notes row 1 : none | alberto garcia | spain | 7:43.89 | cr row 2 : none | antonio david jimenez | spain | 7:46.49 | pb row 3 : none | jesus espana | spain | 7:48.08 | pb row 4 : none | john mayock | great britain | 7:48.08 | none row 5 : 5 | michael buchleitner | austria | 7:54.39 | sb row 6 : 6 | mohammed mourhit | belgium | 7:59.79 | none row 7 : 7 | sergey ivanov | russia | 8:02.98 | none row 8 : 8 | mindaugas pukstas | lithuania | 8:03.21 | pb row 9 : 9 | irba lakhal | france | 8:03.38 | none row 10 : 10 | joakim johansson | denmark | 8:06.47 | none row 11 : 11 | harald steindorfer | austria | 8:09.21 | none row 12 : 12 | ferdinando vicari | italy | 8:17.46 | none row 13 : 13 | martin steinbauer | austria | 8:22.06 | none row 14 : 14 | christos papapetrou | cyprus | 8:30.59 | none | col : count ( "notes" ) row 1 : 1 | select count ( notes ) where name = 'ferdinando vicari' <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & nationality & time & notes \\
\midrule
0 & none & alberto garcia & spain & 7:43.89 & cr \\
1 & none & antonio david jimenez & spain & 7:46.49 & pb \\
2 & none & jesus espana & spain & 7:48.08 & pb \\
3 & none & john mayock & great britain & 7:48.08 & none \\
4 & 5 & michael buchleitner & austria & 7:54.39 & sb \\
5 & 6 & mohammed mourhit & belgium & 7:59.79 & none \\
6 & 7 & sergey ivanov & russia & 8:02.98 & none \\
7 & 8 & mindaugas pukstas & lithuania & 8:03.21 & pb \\
8 & 9 & irba lakhal & france & 8:03.38 & none \\
9 & 10 & joakim johansson & denmark & 8:06.47 & none \\
10 & 11 & harald steindorfer & austria & 8:09.21 & none \\
11 & 12 & ferdinando vicari & italy & 8:17.46 & none \\
12 & 13 & martin steinbauer & austria & 8:22.06 & none \\
13 & 14 & christos papapetrou & cyprus & 8:30.59 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "notes" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( notes ) where name = 'ferdinando vicari' <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>alberto garcia</td>
<td>spain</td>
<td>7:43.89</td>
<td>cr</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>antonio david jimenez</td>
<td>spain</td>
<td>7:46.49</td>
<td>pb</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>jesus espana</td>
<td>spain</td>
<td>7:48.08</td>
<td>pb</td>
</tr>
<tr>
<th>3</th>
<td>none</td>
<td>john mayock</td>
<td>great britain</td>
<td>7:48.08</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>michael buchleitner</td>
<td>austria</td>
<td>7:54.39</td>
<td>sb</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>mohammed mourhit</td>
<td>belgium</td>
<td>7:59.79</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>sergey ivanov</td>
<td>russia</td>
<td>8:02.98</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>mindaugas pukstas</td>
<td>lithuania</td>
<td>8:03.21</td>
<td>pb</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>irba lakhal</td>
<td>france</td>
<td>8:03.38</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>joakim johansson</td>
<td>denmark</td>
<td>8:06.47</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>harald steindorfer</td>
<td>austria</td>
<td>8:09.21</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>ferdinando vicari</td>
<td>italy</td>
<td>8:17.46</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>martin steinbauer</td>
<td>austria</td>
<td>8:22.06</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>christos papapetrou</td>
<td>cyprus</td>
<td>8:30.59</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "notes" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( notes ) where name = 'ferdinando vicari' <table_name> : table | | rank | name | nationality | time | notes |
|---:|:-------|:----------------------|:--------------|:--------|:--------|
| 0 | none | alberto garcia | spain | 7:43.89 | cr |
| 1 | none | antonio david jimenez | spain | 7:46.49 | pb |
| 2 | none | jesus espana | spain | 7:48.08 | pb |
| 3 | none | john mayock | great britain | 7:48.08 | none |
| 4 | 5 | michael buchleitner | austria | 7:54.39 | sb |
| 5 | 6 | mohammed mourhit | belgium | 7:59.79 | none |
| 6 | 7 | sergey ivanov | russia | 8:02.98 | none |
| 7 | 8 | mindaugas pukstas | lithuania | 8:03.21 | pb |
| 8 | 9 | irba lakhal | france | 8:03.38 | none |
| 9 | 10 | joakim johansson | denmark | 8:06.47 | none |
| 10 | 11 | harald steindorfer | austria | 8:09.21 | none |
| 11 | 12 | ferdinando vicari | italy | 8:17.46 | none |
| 12 | 13 | martin steinbauer | austria | 8:22.06 | none |
| 13 | 14 | christos papapetrou | cyprus | 8:30.59 | none | | | | count ( "notes" ) |
|---:|--------------------:|
| 0 | 1 | | [
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] |
select count ( attendance ) where result = '0-1' col : date | opponents | venue | result | scorers | attendance row 1 : 1920-08-28 00:00:00 | reading | h | 0-1 | none | 14500 row 2 : 1920-09-01 00:00:00 | bristol rovers | a | 2-3 | walker, wolstenholme | 10000 row 3 : 1920-09-04 00:00:00 | reading | a | 0-4 | none | 10000 row 4 : 1920-09-09 00:00:00 | bristol rovers | h | 0-2 | none | 8000 row 5 : 1920-09-11 00:00:00 | plymouth argyle | a | 1-5 | wolstenholme | 12000 row 6 : 1920-09-18 00:00:00 | plymouth argyle | h | 0-0 | none | 8000 row 7 : 1920-09-25 00:00:00 | exeter city | a | 1-0 | wolstenholme | 8000 row 8 : 1920-10-02 00:00:00 | exeter city | h | 2-0 | wolstenholme 2 | 8000 row 9 : 1920-10-09 00:00:00 | millwall | h | 3-1 | devlin 2, walker | 14000 row 10 : 1920-10-16 00:00:00 | millwall | a | 0-1 | none | 20000 row 11 : 1920-10-21 00:00:00 | swindon town | h | 0-1 | none | 10000 row 12 : 1920-10-23 00:00:00 | portsmouth | h | 1-0 | devlin | 9000 row 13 : 1920-10-30 00:00:00 | portsmouth | a | 2-0 | devlin, dobson | 13679 row 14 : 1920-11-06 00:00:00 | gillingham | h | 1-0 | wolstenholme | 7000 row 15 : 1920-11-13 00:00:00 | gillingham | a | 4-1 | dobson, wolstenholme, blott, devlin | 8000 row 16 : 1920-11-27 00:00:00 | swindon town | a | 0-5 | none | 7000 row 17 : 1920-12-04 00:00:00 | watford | h | 0-2 | none | 6000 row 18 : 1920-12-11 00:00:00 | watford | a | 1-5 | wright | 7000 row 19 : 1920-12-18 00:00:00 | brentford | a | 2-2 | wright, thompson | 6000 row 20 : 1920-12-25 00:00:00 | southend united | h | 1-1 | dobson | 9000 row 21 : 1920-12-27 00:00:00 | southend united | a | 1-2 | walker | 10000 row 22 : 1921-01-01 00:00:00 | brentford | h | 3-1 | dobson, walker, cox | 7500 row 23 : 1921-01-13 00:00:00 | norwich city | h | 2-0 | wright, cox | 4000 row 24 : 1921-01-22 00:00:00 | norwich city | a | 0-3 | none | 5000 row 25 : 1921-01-29 00:00:00 | northampton town | h | 1-1 | dobson | 8000 row 26 : 1921-02-05 00:00:00 | northampton town | a | 2-0 | groves, wright | 8000 row 27 : 1921-02-12 00:00:00 | crystal palace | h | 0-1 | none | 12000 row 28 : 1921-02-19 00:00:00 | crystal palace | a | 0-2 | none | 7000 row 29 : 1921-02-26 00:00:00 | brighton & hove albion | h | 0-4 | none | 8000 row 30 : 1921-03-05 00:00:00 | brighton & hove albion | a | 0-1 | none | 8000 row 31 : 1921-03-12 00:00:00 | grimsby town | h | 2-1 | devlin, kelson | 8000 row 32 : 1921-03-19 00:00:00 | grimsby town | a | 1-1 | devlin | 9000 row 33 : 1921-03-25 00:00:00 | merthyr town | h | 0-3 | none | 12600 row 34 : 1921-03-26 00:00:00 | queens park rangers | a | 0-2 | none | 10000 row 35 : 1921-03-28 00:00:00 | merthyr town | a | 2-1 | gaughan, devlin | 6000 row 36 : 1921-04-02 00:00:00 | queens park rangers | h | 1-3 | devlin | 7500 row 37 : 1921-04-09 00:00:00 | swansea town | h | 1-1 | walker | 6000 row 38 : 1921-04-16 00:00:00 | swansea town | a | 2-1 | dobson, wolstenholme | 14000 row 39 : 1921-04-23 00:00:00 | luton town | a | 2-2 | walker, devlin | 9000 row 40 : 1921-04-30 00:00:00 | luton town | h | 2-0 | devlin 2 | 5000 row 41 : 1921-05-02 00:00:00 | southampton | a | 0-0 | none | 6000 row 42 : 1921-05-07 00:00:00 | southampton | h | 0-0 | none | 8000 | col : count ( "attendance" ) row 1 : 5 | select count ( attendance ) where result = '0-1' <table_name> : table \begin{tabular}{lllllll}
\toprule
& date & opponents & venue & result & scorers & attendance \\
\midrule
0 & 1920-08-28 00:00:00 & reading & h & 0-1 & none & 14500 \\
1 & 1920-09-01 00:00:00 & bristol rovers & a & 2-3 & walker, wolstenholme & 10000 \\
2 & 1920-09-04 00:00:00 & reading & a & 0-4 & none & 10000 \\
3 & 1920-09-09 00:00:00 & bristol rovers & h & 0-2 & none & 8000 \\
4 & 1920-09-11 00:00:00 & plymouth argyle & a & 1-5 & wolstenholme & 12000 \\
5 & 1920-09-18 00:00:00 & plymouth argyle & h & 0-0 & none & 8000 \\
6 & 1920-09-25 00:00:00 & exeter city & a & 1-0 & wolstenholme & 8000 \\
7 & 1920-10-02 00:00:00 & exeter city & h & 2-0 & wolstenholme 2 & 8000 \\
8 & 1920-10-09 00:00:00 & millwall & h & 3-1 & devlin 2, walker & 14000 \\
9 & 1920-10-16 00:00:00 & millwall & a & 0-1 & none & 20000 \\
10 & 1920-10-21 00:00:00 & swindon town & h & 0-1 & none & 10000 \\
11 & 1920-10-23 00:00:00 & portsmouth & h & 1-0 & devlin & 9000 \\
12 & 1920-10-30 00:00:00 & portsmouth & a & 2-0 & devlin, dobson & 13679 \\
13 & 1920-11-06 00:00:00 & gillingham & h & 1-0 & wolstenholme & 7000 \\
14 & 1920-11-13 00:00:00 & gillingham & a & 4-1 & dobson, wolstenholme, blott, devlin & 8000 \\
15 & 1920-11-27 00:00:00 & swindon town & a & 0-5 & none & 7000 \\
16 & 1920-12-04 00:00:00 & watford & h & 0-2 & none & 6000 \\
17 & 1920-12-11 00:00:00 & watford & a & 1-5 & wright & 7000 \\
18 & 1920-12-18 00:00:00 & brentford & a & 2-2 & wright, thompson & 6000 \\
19 & 1920-12-25 00:00:00 & southend united & h & 1-1 & dobson & 9000 \\
20 & 1920-12-27 00:00:00 & southend united & a & 1-2 & walker & 10000 \\
21 & 1921-01-01 00:00:00 & brentford & h & 3-1 & dobson, walker, cox & 7500 \\
22 & 1921-01-13 00:00:00 & norwich city & h & 2-0 & wright, cox & 4000 \\
23 & 1921-01-22 00:00:00 & norwich city & a & 0-3 & none & 5000 \\
24 & 1921-01-29 00:00:00 & northampton town & h & 1-1 & dobson & 8000 \\
25 & 1921-02-05 00:00:00 & northampton town & a & 2-0 & groves, wright & 8000 \\
26 & 1921-02-12 00:00:00 & crystal palace & h & 0-1 & none & 12000 \\
27 & 1921-02-19 00:00:00 & crystal palace & a & 0-2 & none & 7000 \\
28 & 1921-02-26 00:00:00 & brighton & hove albion & h & 0-4 & none & 8000 \\
29 & 1921-03-05 00:00:00 & brighton & hove albion & a & 0-1 & none & 8000 \\
30 & 1921-03-12 00:00:00 & grimsby town & h & 2-1 & devlin, kelson & 8000 \\
31 & 1921-03-19 00:00:00 & grimsby town & a & 1-1 & devlin & 9000 \\
32 & 1921-03-25 00:00:00 & merthyr town & h & 0-3 & none & 12600 \\
33 & 1921-03-26 00:00:00 & queens park rangers & a & 0-2 & none & 10000 \\
34 & 1921-03-28 00:00:00 & merthyr town & a & 2-1 & gaughan, devlin & 6000 \\
35 & 1921-04-02 00:00:00 & queens park rangers & h & 1-3 & devlin & 7500 \\
36 & 1921-04-09 00:00:00 & swansea town & h & 1-1 & walker & 6000 \\
37 & 1921-04-16 00:00:00 & swansea town & a & 2-1 & dobson, wolstenholme & 14000 \\
38 & 1921-04-23 00:00:00 & luton town & a & 2-2 & walker, devlin & 9000 \\
39 & 1921-04-30 00:00:00 & luton town & h & 2-0 & devlin 2 & 5000 \\
40 & 1921-05-02 00:00:00 & southampton & a & 0-0 & none & 6000 \\
41 & 1921-05-07 00:00:00 & southampton & h & 0-0 & none & 8000 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "attendance" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( attendance ) where result = '0-1' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>opponents</th>
<th>venue</th>
<th>result</th>
<th>scorers</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1920-08-28 00:00:00</td>
<td>reading</td>
<td>h</td>
<td>0-1</td>
<td>none</td>
<td>14500</td>
</tr>
<tr>
<th>1</th>
<td>1920-09-01 00:00:00</td>
<td>bristol rovers</td>
<td>a</td>
<td>2-3</td>
<td>walker, wolstenholme</td>
<td>10000</td>
</tr>
<tr>
<th>2</th>
<td>1920-09-04 00:00:00</td>
<td>reading</td>
<td>a</td>
<td>0-4</td>
<td>none</td>
<td>10000</td>
</tr>
<tr>
<th>3</th>
<td>1920-09-09 00:00:00</td>
<td>bristol rovers</td>
<td>h</td>
<td>0-2</td>
<td>none</td>
<td>8000</td>
</tr>
<tr>
<th>4</th>
<td>1920-09-11 00:00:00</td>
<td>plymouth argyle</td>
<td>a</td>
<td>1-5</td>
<td>wolstenholme</td>
<td>12000</td>
</tr>
<tr>
<th>5</th>
<td>1920-09-18 00:00:00</td>
<td>plymouth argyle</td>
<td>h</td>
<td>0-0</td>
<td>none</td>
<td>8000</td>
</tr>
<tr>
<th>6</th>
<td>1920-09-25 00:00:00</td>
<td>exeter city</td>
<td>a</td>
<td>1-0</td>
<td>wolstenholme</td>
<td>8000</td>
</tr>
<tr>
<th>7</th>
<td>1920-10-02 00:00:00</td>
<td>exeter city</td>
<td>h</td>
<td>2-0</td>
<td>wolstenholme 2</td>
<td>8000</td>
</tr>
<tr>
<th>8</th>
<td>1920-10-09 00:00:00</td>
<td>millwall</td>
<td>h</td>
<td>3-1</td>
<td>devlin 2, walker</td>
<td>14000</td>
</tr>
<tr>
<th>9</th>
<td>1920-10-16 00:00:00</td>
<td>millwall</td>
<td>a</td>
<td>0-1</td>
<td>none</td>
<td>20000</td>
</tr>
<tr>
<th>10</th>
<td>1920-10-21 00:00:00</td>
<td>swindon town</td>
<td>h</td>
<td>0-1</td>
<td>none</td>
<td>10000</td>
</tr>
<tr>
<th>11</th>
<td>1920-10-23 00:00:00</td>
<td>portsmouth</td>
<td>h</td>
<td>1-0</td>
<td>devlin</td>
<td>9000</td>
</tr>
<tr>
<th>12</th>
<td>1920-10-30 00:00:00</td>
<td>portsmouth</td>
<td>a</td>
<td>2-0</td>
<td>devlin, dobson</td>
<td>13679</td>
</tr>
<tr>
<th>13</th>
<td>1920-11-06 00:00:00</td>
<td>gillingham</td>
<td>h</td>
<td>1-0</td>
<td>wolstenholme</td>
<td>7000</td>
</tr>
<tr>
<th>14</th>
<td>1920-11-13 00:00:00</td>
<td>gillingham</td>
<td>a</td>
<td>4-1</td>
<td>dobson, wolstenholme, blott, devlin</td>
<td>8000</td>
</tr>
<tr>
<th>15</th>
<td>1920-11-27 00:00:00</td>
<td>swindon town</td>
<td>a</td>
<td>0-5</td>
<td>none</td>
<td>7000</td>
</tr>
<tr>
<th>16</th>
<td>1920-12-04 00:00:00</td>
<td>watford</td>
<td>h</td>
<td>0-2</td>
<td>none</td>
<td>6000</td>
</tr>
<tr>
<th>17</th>
<td>1920-12-11 00:00:00</td>
<td>watford</td>
<td>a</td>
<td>1-5</td>
<td>wright</td>
<td>7000</td>
</tr>
<tr>
<th>18</th>
<td>1920-12-18 00:00:00</td>
<td>brentford</td>
<td>a</td>
<td>2-2</td>
<td>wright, thompson</td>
<td>6000</td>
</tr>
<tr>
<th>19</th>
<td>1920-12-25 00:00:00</td>
<td>southend united</td>
<td>h</td>
<td>1-1</td>
<td>dobson</td>
<td>9000</td>
</tr>
<tr>
<th>20</th>
<td>1920-12-27 00:00:00</td>
<td>southend united</td>
<td>a</td>
<td>1-2</td>
<td>walker</td>
<td>10000</td>
</tr>
<tr>
<th>21</th>
<td>1921-01-01 00:00:00</td>
<td>brentford</td>
<td>h</td>
<td>3-1</td>
<td>dobson, walker, cox</td>
<td>7500</td>
</tr>
<tr>
<th>22</th>
<td>1921-01-13 00:00:00</td>
<td>norwich city</td>
<td>h</td>
<td>2-0</td>
<td>wright, cox</td>
<td>4000</td>
</tr>
<tr>
<th>23</th>
<td>1921-01-22 00:00:00</td>
<td>norwich city</td>
<td>a</td>
<td>0-3</td>
<td>none</td>
<td>5000</td>
</tr>
<tr>
<th>24</th>
<td>1921-01-29 00:00:00</td>
<td>northampton town</td>
<td>h</td>
<td>1-1</td>
<td>dobson</td>
<td>8000</td>
</tr>
<tr>
<th>25</th>
<td>1921-02-05 00:00:00</td>
<td>northampton town</td>
<td>a</td>
<td>2-0</td>
<td>groves, wright</td>
<td>8000</td>
</tr>
<tr>
<th>26</th>
<td>1921-02-12 00:00:00</td>
<td>crystal palace</td>
<td>h</td>
<td>0-1</td>
<td>none</td>
<td>12000</td>
</tr>
<tr>
<th>27</th>
<td>1921-02-19 00:00:00</td>
<td>crystal palace</td>
<td>a</td>
<td>0-2</td>
<td>none</td>
<td>7000</td>
</tr>
<tr>
<th>28</th>
<td>1921-02-26 00:00:00</td>
<td>brighton & hove albion</td>
<td>h</td>
<td>0-4</td>
<td>none</td>
<td>8000</td>
</tr>
<tr>
<th>29</th>
<td>1921-03-05 00:00:00</td>
<td>brighton & hove albion</td>
<td>a</td>
<td>0-1</td>
<td>none</td>
<td>8000</td>
</tr>
<tr>
<th>30</th>
<td>1921-03-12 00:00:00</td>
<td>grimsby town</td>
<td>h</td>
<td>2-1</td>
<td>devlin, kelson</td>
<td>8000</td>
</tr>
<tr>
<th>31</th>
<td>1921-03-19 00:00:00</td>
<td>grimsby town</td>
<td>a</td>
<td>1-1</td>
<td>devlin</td>
<td>9000</td>
</tr>
<tr>
<th>32</th>
<td>1921-03-25 00:00:00</td>
<td>merthyr town</td>
<td>h</td>
<td>0-3</td>
<td>none</td>
<td>12600</td>
</tr>
<tr>
<th>33</th>
<td>1921-03-26 00:00:00</td>
<td>queens park rangers</td>
<td>a</td>
<td>0-2</td>
<td>none</td>
<td>10000</td>
</tr>
<tr>
<th>34</th>
<td>1921-03-28 00:00:00</td>
<td>merthyr town</td>
<td>a</td>
<td>2-1</td>
<td>gaughan, devlin</td>
<td>6000</td>
</tr>
<tr>
<th>35</th>
<td>1921-04-02 00:00:00</td>
<td>queens park rangers</td>
<td>h</td>
<td>1-3</td>
<td>devlin</td>
<td>7500</td>
</tr>
<tr>
<th>36</th>
<td>1921-04-09 00:00:00</td>
<td>swansea town</td>
<td>h</td>
<td>1-1</td>
<td>walker</td>
<td>6000</td>
</tr>
<tr>
<th>37</th>
<td>1921-04-16 00:00:00</td>
<td>swansea town</td>
<td>a</td>
<td>2-1</td>
<td>dobson, wolstenholme</td>
<td>14000</td>
</tr>
<tr>
<th>38</th>
<td>1921-04-23 00:00:00</td>
<td>luton town</td>
<td>a</td>
<td>2-2</td>
<td>walker, devlin</td>
<td>9000</td>
</tr>
<tr>
<th>39</th>
<td>1921-04-30 00:00:00</td>
<td>luton town</td>
<td>h</td>
<td>2-0</td>
<td>devlin 2</td>
<td>5000</td>
</tr>
<tr>
<th>40</th>
<td>1921-05-02 00:00:00</td>
<td>southampton</td>
<td>a</td>
<td>0-0</td>
<td>none</td>
<td>6000</td>
</tr>
<tr>
<th>41</th>
<td>1921-05-07 00:00:00</td>
<td>southampton</td>
<td>h</td>
<td>0-0</td>
<td>none</td>
<td>8000</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "attendance" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
</tr>
</tbody>
</table> | select count ( attendance ) where result = '0-1' <table_name> : table | | date | opponents | venue | result | scorers | attendance |
|---:|:--------------------|:-----------------------|:--------|:---------|:------------------------------------|-------------:|
| 0 | 1920-08-28 00:00:00 | reading | h | 0-1 | none | 14500 |
| 1 | 1920-09-01 00:00:00 | bristol rovers | a | 2-3 | walker, wolstenholme | 10000 |
| 2 | 1920-09-04 00:00:00 | reading | a | 0-4 | none | 10000 |
| 3 | 1920-09-09 00:00:00 | bristol rovers | h | 0-2 | none | 8000 |
| 4 | 1920-09-11 00:00:00 | plymouth argyle | a | 1-5 | wolstenholme | 12000 |
| 5 | 1920-09-18 00:00:00 | plymouth argyle | h | 0-0 | none | 8000 |
| 6 | 1920-09-25 00:00:00 | exeter city | a | 1-0 | wolstenholme | 8000 |
| 7 | 1920-10-02 00:00:00 | exeter city | h | 2-0 | wolstenholme 2 | 8000 |
| 8 | 1920-10-09 00:00:00 | millwall | h | 3-1 | devlin 2, walker | 14000 |
| 9 | 1920-10-16 00:00:00 | millwall | a | 0-1 | none | 20000 |
| 10 | 1920-10-21 00:00:00 | swindon town | h | 0-1 | none | 10000 |
| 11 | 1920-10-23 00:00:00 | portsmouth | h | 1-0 | devlin | 9000 |
| 12 | 1920-10-30 00:00:00 | portsmouth | a | 2-0 | devlin, dobson | 13679 |
| 13 | 1920-11-06 00:00:00 | gillingham | h | 1-0 | wolstenholme | 7000 |
| 14 | 1920-11-13 00:00:00 | gillingham | a | 4-1 | dobson, wolstenholme, blott, devlin | 8000 |
| 15 | 1920-11-27 00:00:00 | swindon town | a | 0-5 | none | 7000 |
| 16 | 1920-12-04 00:00:00 | watford | h | 0-2 | none | 6000 |
| 17 | 1920-12-11 00:00:00 | watford | a | 1-5 | wright | 7000 |
| 18 | 1920-12-18 00:00:00 | brentford | a | 2-2 | wright, thompson | 6000 |
| 19 | 1920-12-25 00:00:00 | southend united | h | 1-1 | dobson | 9000 |
| 20 | 1920-12-27 00:00:00 | southend united | a | 1-2 | walker | 10000 |
| 21 | 1921-01-01 00:00:00 | brentford | h | 3-1 | dobson, walker, cox | 7500 |
| 22 | 1921-01-13 00:00:00 | norwich city | h | 2-0 | wright, cox | 4000 |
| 23 | 1921-01-22 00:00:00 | norwich city | a | 0-3 | none | 5000 |
| 24 | 1921-01-29 00:00:00 | northampton town | h | 1-1 | dobson | 8000 |
| 25 | 1921-02-05 00:00:00 | northampton town | a | 2-0 | groves, wright | 8000 |
| 26 | 1921-02-12 00:00:00 | crystal palace | h | 0-1 | none | 12000 |
| 27 | 1921-02-19 00:00:00 | crystal palace | a | 0-2 | none | 7000 |
| 28 | 1921-02-26 00:00:00 | brighton & hove albion | h | 0-4 | none | 8000 |
| 29 | 1921-03-05 00:00:00 | brighton & hove albion | a | 0-1 | none | 8000 |
| 30 | 1921-03-12 00:00:00 | grimsby town | h | 2-1 | devlin, kelson | 8000 |
| 31 | 1921-03-19 00:00:00 | grimsby town | a | 1-1 | devlin | 9000 |
| 32 | 1921-03-25 00:00:00 | merthyr town | h | 0-3 | none | 12600 |
| 33 | 1921-03-26 00:00:00 | queens park rangers | a | 0-2 | none | 10000 |
| 34 | 1921-03-28 00:00:00 | merthyr town | a | 2-1 | gaughan, devlin | 6000 |
| 35 | 1921-04-02 00:00:00 | queens park rangers | h | 1-3 | devlin | 7500 |
| 36 | 1921-04-09 00:00:00 | swansea town | h | 1-1 | walker | 6000 |
| 37 | 1921-04-16 00:00:00 | swansea town | a | 2-1 | dobson, wolstenholme | 14000 |
| 38 | 1921-04-23 00:00:00 | luton town | a | 2-2 | walker, devlin | 9000 |
| 39 | 1921-04-30 00:00:00 | luton town | h | 2-0 | devlin 2 | 5000 |
| 40 | 1921-05-02 00:00:00 | southampton | a | 0-0 | none | 6000 |
| 41 | 1921-05-07 00:00:00 | southampton | h | 0-0 | none | 8000 | | | | count ( "attendance" ) |
|---:|-------------------------:|
| 0 | 5 | | [
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select chart positions uk where album = 'i' col : year | title | chart positions nor | chart positions aus | chart positions aut | chart positions bel | chart positions ger | chart positions nl | chart positions nz | chart positions swe | chart positions swi | chart positions uk | album row 1 : 2003 | "she's so high" | 1 | 60 | 42 | 9 | 25 | 16 | 38 | none | 91 | 25 | i row 2 : 2004 | "here she comes" | 12 | none | none | 53 | none | none | none | none | none | none | i row 3 : 2004 | "all you have to offer" | none | none | none | none | none | none | none | none | none | none | i row 4 : 2004 | "my street" | none | none | none | none | none | none | none | none | none | none | a part of me row 5 : 2004 | "before you leave" | none | none | none | 52 | none | none | none | none | none | none | a part of me row 6 : 2005 | "never easy" | none | none | none | none | none | none | none | none | none | none | a part of me row 7 : 2006 | "when the stars go blue" (featuring venke knutson) | 14 | none | none | none | none | none | none | none | none | none | venke knutson's places i've been row 8 : 2006 | "hallelujah" (with espen lind, askil holm and alejandro fuentes) | 1 | none | none | none | none | none | none | none | none | none | hallelujah - live row 9 : 2006 | "boys of summer" (with espen lind, askil holm and alejandro fuentes) | 12 | none | none | none | none | none | none | none | none | none | hallelujah - live row 10 : 2007 | "push, push" | 1 | none | none | none | none | none | none | none | none | none | push push row 11 : 2007 | "silence" | 9 | none | none | none | none | none | none | none | none | none | push push row 12 : 2008 | "reality kicks" | 20 | none | none | none | none | none | none | none | none | none | push push row 13 : 2008 | "lost highway" (featuring willie nelson) | 1 | none | none | none | none | none | none | none | none | none | rise to the occasion row 14 : 2008 | "don't have what it takes" | 19 | none | none | none | none | none | none | none | none | none | rise to the occasion row 15 : 2008 | "rise to the occasion" | none | none | none | none | none | none | none | 38 | none | none | rise to the occasion row 16 : 2009 | "with or without you" (with espen lind, askil holm and alejandro fuentes) | 1 | none | none | none | none | none | none | none | none | none | hallelujah - live volume 2 row 17 : 2010 | "himmel pa jord" | 5 | none | none | none | none | none | none | none | none | none | have yourself a merry little christmas row 18 : 2013 | "adieu" | 9 | none | none | none | none | none | none | none | none | none | none row 19 : 2013 | "engler i sneen" (with lene marlin) | 7 | none | none | none | none | none | none | none | none | none | none | col : chart positions uk row 1 : 25 row 2 : none row 3 : none | select chart positions uk where album = 'i' <table_name> : table \begin{tabular}{llllllllllllll}
\toprule
& year & title & chart positions nor & chart positions aus & chart positions aut & chart positions bel & chart positions ger & chart positions nl & chart positions nz & chart positions swe & chart positions swi & chart positions uk & album \\
\midrule
0 & 2003 & "she's so high" & 1 & 60 & 42 & 9 & 25 & 16 & 38 & none & 91 & 25 & i \\
1 & 2004 & "here she comes" & 12 & none & none & 53 & none & none & none & none & none & none & i \\
2 & 2004 & "all you have to offer" & none & none & none & none & none & none & none & none & none & none & i \\
3 & 2004 & "my street" & none & none & none & none & none & none & none & none & none & none & a part of me \\
4 & 2004 & "before you leave" & none & none & none & 52 & none & none & none & none & none & none & a part of me \\
5 & 2005 & "never easy" & none & none & none & none & none & none & none & none & none & none & a part of me \\
6 & 2006 & "when the stars go blue" (featuring venke knutson) & 14 & none & none & none & none & none & none & none & none & none & venke knutson's places i've been \\
7 & 2006 & "hallelujah" (with espen lind, askil holm and alejandro fuentes) & 1 & none & none & none & none & none & none & none & none & none & hallelujah - live \\
8 & 2006 & "boys of summer" (with espen lind, askil holm and alejandro fuentes) & 12 & none & none & none & none & none & none & none & none & none & hallelujah - live \\
9 & 2007 & "push, push" & 1 & none & none & none & none & none & none & none & none & none & push push \\
10 & 2007 & "silence" & 9 & none & none & none & none & none & none & none & none & none & push push \\
11 & 2008 & "reality kicks" & 20 & none & none & none & none & none & none & none & none & none & push push \\
12 & 2008 & "lost highway" (featuring willie nelson) & 1 & none & none & none & none & none & none & none & none & none & rise to the occasion \\
13 & 2008 & "don't have what it takes" & 19 & none & none & none & none & none & none & none & none & none & rise to the occasion \\
14 & 2008 & "rise to the occasion" & none & none & none & none & none & none & none & 38 & none & none & rise to the occasion \\
15 & 2009 & "with or without you" (with espen lind, askil holm and alejandro fuentes) & 1 & none & none & none & none & none & none & none & none & none & hallelujah - live volume 2 \\
16 & 2010 & "himmel pa jord" & 5 & none & none & none & none & none & none & none & none & none & have yourself a merry little christmas \\
17 & 2013 & "adieu" & 9 & none & none & none & none & none & none & none & none & none & none \\
18 & 2013 & "engler i sneen" (with lene marlin) & 7 & none & none & none & none & none & none & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& chart positions uk \\
\midrule
0 & 25 \\
1 & none \\
2 & none \\
\bottomrule
\end{tabular}
| select chart positions uk where album = 'i' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>chart positions nor</th>
<th>chart positions aus</th>
<th>chart positions aut</th>
<th>chart positions bel</th>
<th>chart positions ger</th>
<th>chart positions nl</th>
<th>chart positions nz</th>
<th>chart positions swe</th>
<th>chart positions swi</th>
<th>chart positions uk</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2003</td>
<td>"she's so high"</td>
<td>1</td>
<td>60</td>
<td>42</td>
<td>9</td>
<td>25</td>
<td>16</td>
<td>38</td>
<td>none</td>
<td>91</td>
<td>25</td>
<td>i</td>
</tr>
<tr>
<th>1</th>
<td>2004</td>
<td>"here she comes"</td>
<td>12</td>
<td>none</td>
<td>none</td>
<td>53</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>i</td>
</tr>
<tr>
<th>2</th>
<td>2004</td>
<td>"all you have to offer"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>i</td>
</tr>
<tr>
<th>3</th>
<td>2004</td>
<td>"my street"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>a part of me</td>
</tr>
<tr>
<th>4</th>
<td>2004</td>
<td>"before you leave"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>52</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>a part of me</td>
</tr>
<tr>
<th>5</th>
<td>2005</td>
<td>"never easy"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>a part of me</td>
</tr>
<tr>
<th>6</th>
<td>2006</td>
<td>"when the stars go blue" (featuring venke knutson)</td>
<td>14</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>venke knutson's places i've been</td>
</tr>
<tr>
<th>7</th>
<td>2006</td>
<td>"hallelujah" (with espen lind, askil holm and alejandro fuentes)</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>hallelujah - live</td>
</tr>
<tr>
<th>8</th>
<td>2006</td>
<td>"boys of summer" (with espen lind, askil holm and alejandro fuentes)</td>
<td>12</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>hallelujah - live</td>
</tr>
<tr>
<th>9</th>
<td>2007</td>
<td>"push, push"</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>push push</td>
</tr>
<tr>
<th>10</th>
<td>2007</td>
<td>"silence"</td>
<td>9</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>push push</td>
</tr>
<tr>
<th>11</th>
<td>2008</td>
<td>"reality kicks"</td>
<td>20</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>push push</td>
</tr>
<tr>
<th>12</th>
<td>2008</td>
<td>"lost highway" (featuring willie nelson)</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>rise to the occasion</td>
</tr>
<tr>
<th>13</th>
<td>2008</td>
<td>"don't have what it takes"</td>
<td>19</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>rise to the occasion</td>
</tr>
<tr>
<th>14</th>
<td>2008</td>
<td>"rise to the occasion"</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>38</td>
<td>none</td>
<td>none</td>
<td>rise to the occasion</td>
</tr>
<tr>
<th>15</th>
<td>2009</td>
<td>"with or without you" (with espen lind, askil holm and alejandro fuentes)</td>
<td>1</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>hallelujah - live volume 2</td>
</tr>
<tr>
<th>16</th>
<td>2010</td>
<td>"himmel pa jord"</td>
<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>none</td>
<td>none</td>
<td>have yourself a merry little christmas</td>
</tr>
<tr>
<th>17</th>
<td>2013</td>
<td>"adieu"</td>
<td>9</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>2013</td>
<td>"engler i sneen" (with lene marlin)</td>
<td>7</td>
<td>none</td>
<td>none</td>
<td>none</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>chart positions uk</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
</tr>
</tbody>
</table> | select chart positions uk where album = 'i' <table_name> : table | | year | title | chart positions nor | chart positions aus | chart positions aut | chart positions bel | chart positions ger | chart positions nl | chart positions nz | chart positions swe | chart positions swi | chart positions uk | album |
|---:|-------:|:--------------------------------------------------------------------------|:----------------------|:----------------------|:----------------------|:----------------------|:----------------------|:---------------------|:---------------------|:----------------------|:----------------------|:---------------------|:---------------------------------------|
| 0 | 2003 | "she's so high" | 1 | 60 | 42 | 9 | 25 | 16 | 38 | none | 91 | 25 | i |
| 1 | 2004 | "here she comes" | 12 | none | none | 53 | none | none | none | none | none | none | i |
| 2 | 2004 | "all you have to offer" | none | none | none | none | none | none | none | none | none | none | i |
| 3 | 2004 | "my street" | none | none | none | none | none | none | none | none | none | none | a part of me |
| 4 | 2004 | "before you leave" | none | none | none | 52 | none | none | none | none | none | none | a part of me |
| 5 | 2005 | "never easy" | none | none | none | none | none | none | none | none | none | none | a part of me |
| 6 | 2006 | "when the stars go blue" (featuring venke knutson) | 14 | none | none | none | none | none | none | none | none | none | venke knutson's places i've been |
| 7 | 2006 | "hallelujah" (with espen lind, askil holm and alejandro fuentes) | 1 | none | none | none | none | none | none | none | none | none | hallelujah - live |
| 8 | 2006 | "boys of summer" (with espen lind, askil holm and alejandro fuentes) | 12 | none | none | none | none | none | none | none | none | none | hallelujah - live |
| 9 | 2007 | "push, push" | 1 | none | none | none | none | none | none | none | none | none | push push |
| 10 | 2007 | "silence" | 9 | none | none | none | none | none | none | none | none | none | push push |
| 11 | 2008 | "reality kicks" | 20 | none | none | none | none | none | none | none | none | none | push push |
| 12 | 2008 | "lost highway" (featuring willie nelson) | 1 | none | none | none | none | none | none | none | none | none | rise to the occasion |
| 13 | 2008 | "don't have what it takes" | 19 | none | none | none | none | none | none | none | none | none | rise to the occasion |
| 14 | 2008 | "rise to the occasion" | none | none | none | none | none | none | none | 38 | none | none | rise to the occasion |
| 15 | 2009 | "with or without you" (with espen lind, askil holm and alejandro fuentes) | 1 | none | none | none | none | none | none | none | none | none | hallelujah - live volume 2 |
| 16 | 2010 | "himmel pa jord" | 5 | none | none | none | none | none | none | none | none | none | have yourself a merry little christmas |
| 17 | 2013 | "adieu" | 9 | none | none | none | none | none | none | none | none | none | none |
| 18 | 2013 | "engler i sneen" (with lene marlin) | 7 | none | none | none | none | none | none | none | none | none | none | | | | chart positions uk |
|---:|:---------------------|
| 0 | 25 |
| 1 | none |
| 2 | none | | [
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select silver where nation = 'russia' col : rank | nation | gold | silver | bronze | total row 1 : 1 | netherlands | 8 | 3 | 1 | 12 row 2 : 2 | australia | 3 | 3 | 4 | 10 row 3 : 3 | united states | 2 | 5 | 1 | 8 row 4 : 4 | hungary | 1 | 1 | 3 | 5 row 5 : 5 | canada | 1 | none | 3 | 4 row 6 : 6 | italy | none | 2 | 1 | 3 row 7 : 7 | russia | none | 1 | 1 | 2 row 8 : 8 | china | none | none | 1 | 1 | col : silver row 1 : 1 | select silver where nation = 'russia' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & netherlands & 8 & 3 & 1 & 12 \\
1 & 2 & australia & 3 & 3 & 4 & 10 \\
2 & 3 & united states & 2 & 5 & 1 & 8 \\
3 & 4 & hungary & 1 & 1 & 3 & 5 \\
4 & 5 & canada & 1 & none & 3 & 4 \\
5 & 6 & italy & none & 2 & 1 & 3 \\
6 & 7 & russia & none & 1 & 1 & 2 \\
7 & 8 & china & none & none & 1 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& silver \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select silver where nation = 'russia' <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>netherlands</td>
<td>8</td>
<td>3</td>
<td>1</td>
<td>12</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>australia</td>
<td>3</td>
<td>3</td>
<td>4</td>
<td>10</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>united states</td>
<td>2</td>
<td>5</td>
<td>1</td>
<td>8</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>hungary</td>
<td>1</td>
<td>1</td>
<td>3</td>
<td>5</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>canada</td>
<td>1</td>
<td>none</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>italy</td>
<td>none</td>
<td>2</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>russia</td>
<td>none</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>china</td>
<td>none</td>
<td>none</td>
<td>1</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>silver</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select silver where nation = 'russia' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|-------:|:--------------|:-------|:---------|---------:|--------:|
| 0 | 1 | netherlands | 8 | 3 | 1 | 12 |
| 1 | 2 | australia | 3 | 3 | 4 | 10 |
| 2 | 3 | united states | 2 | 5 | 1 | 8 |
| 3 | 4 | hungary | 1 | 1 | 3 | 5 |
| 4 | 5 | canada | 1 | none | 3 | 4 |
| 5 | 6 | italy | none | 2 | 1 | 3 |
| 6 | 7 | russia | none | 1 | 1 | 2 |
| 7 | 8 | china | none | none | 1 | 1 | | | | silver |
|---:|---------:|
| 0 | 1 | | [
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select sum ( notes ) where year = 2001 col : year | competition | venue | position | notes row 1 : 1999 | european junior championships | riga, latvia | 6th | 49.65 m row 2 : 2001 | european u23 championships | amsterdam, netherlands | 10th | 53.30 m row 3 : 2005 | universiade | izmir, turkey | 9th | 58.29 m row 4 : 2006 | european championships | gothenburg, sweden | 15th (q) | 59.54 m row 5 : 2007 | universiade | bangkok, thailand | 1st | 61.55 m row 6 : 2008 | olympic games | beijing, china | 18th (q) | 61.32 m row 7 : 2009 | world championships | berlin, germany | 8th | 63.17 m row 8 : 2010 | european championships | barcelona, spain | 15th (q) | 60.76 m row 9 : 2011 | world championships | daegu, south korea | 21st (q) | 61.47 m row 10 : 2012 | european championships | helsinki, finland | 7th | 62.85 m row 11 : 2012 | olympic games | london, united kingdom | 24th (q) | 60.81 m row 12 : 2013 | world championships | moscow, russia | 18th (q) | 59.85 m | col : sum ( "notes" ) row 1 : 53.3 | select sum ( notes ) where year = 2001 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & competition & venue & position & notes \\
\midrule
0 & 1999 & european junior championships & riga, latvia & 6th & 49.65 m \\
1 & 2001 & european u23 championships & amsterdam, netherlands & 10th & 53.30 m \\
2 & 2005 & universiade & izmir, turkey & 9th & 58.29 m \\
3 & 2006 & european championships & gothenburg, sweden & 15th (q) & 59.54 m \\
4 & 2007 & universiade & bangkok, thailand & 1st & 61.55 m \\
5 & 2008 & olympic games & beijing, china & 18th (q) & 61.32 m \\
6 & 2009 & world championships & berlin, germany & 8th & 63.17 m \\
7 & 2010 & european championships & barcelona, spain & 15th (q) & 60.76 m \\
8 & 2011 & world championships & daegu, south korea & 21st (q) & 61.47 m \\
9 & 2012 & european championships & helsinki, finland & 7th & 62.85 m \\
10 & 2012 & olympic games & london, united kingdom & 24th (q) & 60.81 m \\
11 & 2013 & world championships & moscow, russia & 18th (q) & 59.85 m \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& sum ( "notes" ) \\
\midrule
0 & 53.3 \\
\bottomrule
\end{tabular}
| select sum ( notes ) where year = 2001 <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>1999</td>
<td>european junior championships</td>
<td>riga, latvia</td>
<td>6th</td>
<td>49.65 m</td>
</tr>
<tr>
<th>1</th>
<td>2001</td>
<td>european u23 championships</td>
<td>amsterdam, netherlands</td>
<td>10th</td>
<td>53.30 m</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>universiade</td>
<td>izmir, turkey</td>
<td>9th</td>
<td>58.29 m</td>
</tr>
<tr>
<th>3</th>
<td>2006</td>
<td>european championships</td>
<td>gothenburg, sweden</td>
<td>15th (q)</td>
<td>59.54 m</td>
</tr>
<tr>
<th>4</th>
<td>2007</td>
<td>universiade</td>
<td>bangkok, thailand</td>
<td>1st</td>
<td>61.55 m</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>olympic games</td>
<td>beijing, china</td>
<td>18th (q)</td>
<td>61.32 m</td>
</tr>
<tr>
<th>6</th>
<td>2009</td>
<td>world championships</td>
<td>berlin, germany</td>
<td>8th</td>
<td>63.17 m</td>
</tr>
<tr>
<th>7</th>
<td>2010</td>
<td>european championships</td>
<td>barcelona, spain</td>
<td>15th (q)</td>
<td>60.76 m</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>world championships</td>
<td>daegu, south korea</td>
<td>21st (q)</td>
<td>61.47 m</td>
</tr>
<tr>
<th>9</th>
<td>2012</td>
<td>european championships</td>
<td>helsinki, finland</td>
<td>7th</td>
<td>62.85 m</td>
</tr>
<tr>
<th>10</th>
<td>2012</td>
<td>olympic games</td>
<td>london, united kingdom</td>
<td>24th (q)</td>
<td>60.81 m</td>
</tr>
<tr>
<th>11</th>
<td>2013</td>
<td>world championships</td>
<td>moscow, russia</td>
<td>18th (q)</td>
<td>59.85 m</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>sum ( "notes" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>53.3</td>
</tr>
</tbody>
</table> | select sum ( notes ) where year = 2001 <table_name> : table | | year | competition | venue | position | notes |
|---:|-------:|:------------------------------|:-----------------------|:-----------|:--------|
| 0 | 1999 | european junior championships | riga, latvia | 6th | 49.65 m |
| 1 | 2001 | european u23 championships | amsterdam, netherlands | 10th | 53.30 m |
| 2 | 2005 | universiade | izmir, turkey | 9th | 58.29 m |
| 3 | 2006 | european championships | gothenburg, sweden | 15th (q) | 59.54 m |
| 4 | 2007 | universiade | bangkok, thailand | 1st | 61.55 m |
| 5 | 2008 | olympic games | beijing, china | 18th (q) | 61.32 m |
| 6 | 2009 | world championships | berlin, germany | 8th | 63.17 m |
| 7 | 2010 | european championships | barcelona, spain | 15th (q) | 60.76 m |
| 8 | 2011 | world championships | daegu, south korea | 21st (q) | 61.47 m |
| 9 | 2012 | european championships | helsinki, finland | 7th | 62.85 m |
| 10 | 2012 | olympic games | london, united kingdom | 24th (q) | 60.81 m |
| 11 | 2013 | world championships | moscow, russia | 18th (q) | 59.85 m | | | | sum ( "notes" ) |
|---:|------------------:|
| 0 | 53.3 | | [
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select count ( * ) where country = '2' and country = 646 col : season | team | country | division | apps | goals | assists row 1 : 01/02 | esteghlal | iran | 1 | none | 3 | none row 2 : 02/03 | esteghlal | iran | 1 | none | 2 | none row 3 : 03/04 | esteghlal | iran | 1 | none | 6 | none row 4 : 04/05 | eseghlal | iran | 1 | 27 | 3 | none row 5 : 05/06 | esteghlal | iran | 1 | 21 | 0 | 2 row 6 : 06/07 | esteghlal | iran | 1 | 14 | 1 | 1 row 7 : 07/08 | steel azin | iran | 1 | none | 2 | none row 8 : 10/11 | gostaresh foolad | iran | 2 | 0 | 0 | 0 | col : count ( "*" ) row 1 : 0 | select count ( * ) where country = '2' and country = 646 <table_name> : table \begin{tabular}{llllllll}
\toprule
& season & team & country & division & apps & goals & assists \\
\midrule
0 & 01/02 & esteghlal & iran & 1 & none & 3 & none \\
1 & 02/03 & esteghlal & iran & 1 & none & 2 & none \\
2 & 03/04 & esteghlal & iran & 1 & none & 6 & none \\
3 & 04/05 & eseghlal & iran & 1 & 27 & 3 & none \\
4 & 05/06 & esteghlal & iran & 1 & 21 & 0 & 2 \\
5 & 06/07 & esteghlal & iran & 1 & 14 & 1 & 1 \\
6 & 07/08 & steel azin & iran & 1 & none & 2 & none \\
7 & 10/11 & gostaresh foolad & iran & 2 & 0 & 0 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where country = '2' and country = 646 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>team</th>
<th>country</th>
<th>division</th>
<th>apps</th>
<th>goals</th>
<th>assists</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>01/02</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>02/03</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>03/04</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>04/05</td>
<td>eseghlal</td>
<td>iran</td>
<td>1</td>
<td>27</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>05/06</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>21</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>06/07</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>14</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>07/08</td>
<td>steel azin</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>10/11</td>
<td>gostaresh foolad</td>
<td>iran</td>
<td>2</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>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where country = '2' and country = 646 <table_name> : table | | season | team | country | division | apps | goals | assists |
|---:|:---------|:-----------------|:----------|-----------:|:-------|--------:|:----------|
| 0 | 01/02 | esteghlal | iran | 1 | none | 3 | none |
| 1 | 02/03 | esteghlal | iran | 1 | none | 2 | none |
| 2 | 03/04 | esteghlal | iran | 1 | none | 6 | none |
| 3 | 04/05 | eseghlal | iran | 1 | 27 | 3 | none |
| 4 | 05/06 | esteghlal | iran | 1 | 21 | 0 | 2 |
| 5 | 06/07 | esteghlal | iran | 1 | 14 | 1 | 1 |
| 6 | 07/08 | steel azin | iran | 1 | none | 2 | none |
| 7 | 10/11 | gostaresh foolad | iran | 2 | 0 | 0 | 0 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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] |
select rank where silver = 0 col : rank | nation | gold | silver | bronze | total row 1 : 1 | soviet union (urs) | 4 | 1 | 6 | 11 row 2 : 2 | yugoslavia (yug) | 2 | 0 | 1 | 3 row 3 : 3 | west germany (frg) | 1 | 1 | 1 | 3 row 4 : 4 | bulgaria (bul) | 1 | 1 | 0 | 2 row 5 : 4 | czechoslovakia (tch) | 1 | 1 | 0 | 2 row 6 : 4 | east germany (gdr) | 1 | 1 | 0 | 2 row 7 : 4 | great britain (gbr) | 1 | 1 | 0 | 2 row 8 : 8 | norway (nor) | 1 | 0 | 0 | 1 row 9 : 8 | romania (rou) | 1 | 0 | 0 | 1 row 10 : 10 | china (chn) | 0 | 1 | 1 | 2 row 11 : 11 | chile (chi) | 0 | 1 | 0 | 1 row 12 : 11 | france (fra) | 0 | 1 | 0 | 1 row 13 : 11 | japan (jpn) | 0 | 1 | 0 | 1 row 14 : 11 | south korea (kor) | 0 | 1 | 0 | 1 row 15 : 11 | sweden (swe) | 0 | 1 | 0 | 1 row 16 : 11 | united states (usa) | 0 | 1 | 0 | 1 row 17 : 17 | hungary (hun) | 0 | 0 | 2 | 2 row 18 : 18 | belgium (bel) | 0 | 0 | 1 | 1 row 19 : 18 | spain (esp) | 0 | 0 | 1 | 1 row 20 : total | total | 13 | 13 | 13 | 39 | col : rank row 1 : 2 row 2 : 8 row 3 : 8 row 4 : 17 row 5 : 18 row 6 : 18 | select rank where silver = 0 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & soviet union (urs) & 4 & 1 & 6 & 11 \\
1 & 2 & yugoslavia (yug) & 2 & 0 & 1 & 3 \\
2 & 3 & west germany (frg) & 1 & 1 & 1 & 3 \\
3 & 4 & bulgaria (bul) & 1 & 1 & 0 & 2 \\
4 & 4 & czechoslovakia (tch) & 1 & 1 & 0 & 2 \\
5 & 4 & east germany (gdr) & 1 & 1 & 0 & 2 \\
6 & 4 & great britain (gbr) & 1 & 1 & 0 & 2 \\
7 & 8 & norway (nor) & 1 & 0 & 0 & 1 \\
8 & 8 & romania (rou) & 1 & 0 & 0 & 1 \\
9 & 10 & china (chn) & 0 & 1 & 1 & 2 \\
10 & 11 & chile (chi) & 0 & 1 & 0 & 1 \\
11 & 11 & france (fra) & 0 & 1 & 0 & 1 \\
12 & 11 & japan (jpn) & 0 & 1 & 0 & 1 \\
13 & 11 & south korea (kor) & 0 & 1 & 0 & 1 \\
14 & 11 & sweden (swe) & 0 & 1 & 0 & 1 \\
15 & 11 & united states (usa) & 0 & 1 & 0 & 1 \\
16 & 17 & hungary (hun) & 0 & 0 & 2 & 2 \\
17 & 18 & belgium (bel) & 0 & 0 & 1 & 1 \\
18 & 18 & spain (esp) & 0 & 0 & 1 & 1 \\
19 & total & total & 13 & 13 & 13 & 39 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& rank \\
\midrule
0 & 2 \\
1 & 8 \\
2 & 8 \\
3 & 17 \\
4 & 18 \\
5 & 18 \\
\bottomrule
\end{tabular}
| select rank where silver = 0 <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 (urs)</td>
<td>4</td>
<td>1</td>
<td>6</td>
<td>11</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>yugoslavia (yug)</td>
<td>2</td>
<td>0</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>west germany (frg)</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>bulgaria (bul)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>czechoslovakia (tch)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>east germany (gdr)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>4</td>
<td>great britain (gbr)</td>
<td>1</td>
<td>1</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>norway (nor)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>romania (rou)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>china (chn)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>chile (chi)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>france (fra)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>11</td>
<td>japan (jpn)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>11</td>
<td>south korea (kor)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>11</td>
<td>sweden (swe)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>11</td>
<td>united states (usa)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>hungary (hun)</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>belgium (bel)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>18</td>
<td>spain (esp)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>19</th>
<td>total</td>
<td>total</td>
<td>13</td>
<td>13</td>
<td>13</td>
<td>39</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>2</td>
</tr>
<tr>
<th>1</th>
<td>8</td>
</tr>
<tr>
<th>2</th>
<td>8</td>
</tr>
<tr>
<th>3</th>
<td>17</td>
</tr>
<tr>
<th>4</th>
<td>18</td>
</tr>
<tr>
<th>5</th>
<td>18</td>
</tr>
</tbody>
</table> | select rank where silver = 0 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | soviet union (urs) | 4 | 1 | 6 | 11 |
| 1 | 2 | yugoslavia (yug) | 2 | 0 | 1 | 3 |
| 2 | 3 | west germany (frg) | 1 | 1 | 1 | 3 |
| 3 | 4 | bulgaria (bul) | 1 | 1 | 0 | 2 |
| 4 | 4 | czechoslovakia (tch) | 1 | 1 | 0 | 2 |
| 5 | 4 | east germany (gdr) | 1 | 1 | 0 | 2 |
| 6 | 4 | great britain (gbr) | 1 | 1 | 0 | 2 |
| 7 | 8 | norway (nor) | 1 | 0 | 0 | 1 |
| 8 | 8 | romania (rou) | 1 | 0 | 0 | 1 |
| 9 | 10 | china (chn) | 0 | 1 | 1 | 2 |
| 10 | 11 | chile (chi) | 0 | 1 | 0 | 1 |
| 11 | 11 | france (fra) | 0 | 1 | 0 | 1 |
| 12 | 11 | japan (jpn) | 0 | 1 | 0 | 1 |
| 13 | 11 | south korea (kor) | 0 | 1 | 0 | 1 |
| 14 | 11 | sweden (swe) | 0 | 1 | 0 | 1 |
| 15 | 11 | united states (usa) | 0 | 1 | 0 | 1 |
| 16 | 17 | hungary (hun) | 0 | 0 | 2 | 2 |
| 17 | 18 | belgium (bel) | 0 | 0 | 1 | 1 |
| 18 | 18 | spain (esp) | 0 | 0 | 1 | 1 |
| 19 | total | total | 13 | 13 | 13 | 39 | | | | rank |
|---:|-------:|
| 0 | 2 |
| 1 | 8 |
| 2 | 8 |
| 3 | 17 |
| 4 | 18 |
| 5 | 18 | | [
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] |
select count ( * ) where occupation = 'private chef/model' col : name | age | hometown | occupation | culinary p.o.v. | eliminated row 1 : damaris phillips | 31 | louisville, ky | culinary teacher | "modern southern food" | winner row 2 : rodney henry | 47 | baltimore, md | pie shop owner | "pie style" | second place row 3 : russell jackson | 49 | san francisco, ca | underground chef | "seven culinary sins" | third place row 4 : stacey poon-kinney | 34 | san diego, ca | restaurant owner | "vintage with a modern twist" | week 10 row 5 : nikki dinki | 29 | new york, ny | food blogger/online host | "semi-vegetarian" / "meat on the side" | week 9 row 6 : chad rosenthal | 37 | ambler, pa | restaurant owner | "jewish bbq guy" | week 7 row 7 : chris hodgson | 26 | cleveland, oh | chef/restaurateur | "compassion for food" | week 6 row 8 : viet pham | 33 | salt lake city, ut | chef/restaurant owner | "the american dream" | week 5 row 9 : connie "lovely" jackson | 27 | los angeles, ca | caterer | "party on a plate" | week 4 & week 8(winner of star salvation) row 10 : danushka lysek | 37 | new york, ny | private chef/model | "your private chef" | week 3 row 11 : andres guillama | 26 | waynesville, nc | childhood obesity prevention coach | "teaching men to cook" | week 2 row 12 : daniela perez-reyes | 28 | haleiwa, hi | bartender/caterer | "peruvian princess" | week 1 | col : count ( "*" ) row 1 : 1 | select count ( * ) where occupation = 'private chef/model' <table_name> : table \begin{tabular}{lllllll}
\toprule
& name & age & hometown & occupation & culinary p.o.v. & eliminated \\
\midrule
0 & damaris phillips & 31 & louisville, ky & culinary teacher & "modern southern food" & winner \\
1 & rodney henry & 47 & baltimore, md & pie shop owner & "pie style" & second place \\
2 & russell jackson & 49 & san francisco, ca & underground chef & "seven culinary sins" & third place \\
3 & stacey poon-kinney & 34 & san diego, ca & restaurant owner & "vintage with a modern twist" & week 10 \\
4 & nikki dinki & 29 & new york, ny & food blogger/online host & "semi-vegetarian" / "meat on the side" & week 9 \\
5 & chad rosenthal & 37 & ambler, pa & restaurant owner & "jewish bbq guy" & week 7 \\
6 & chris hodgson & 26 & cleveland, oh & chef/restaurateur & "compassion for food" & week 6 \\
7 & viet pham & 33 & salt lake city, ut & chef/restaurant owner & "the american dream" & week 5 \\
8 & connie "lovely" jackson & 27 & los angeles, ca & caterer & "party on a plate" & week 4 & week 8(winner of star salvation) \\
9 & danushka lysek & 37 & new york, ny & private chef/model & "your private chef" & week 3 \\
10 & andres guillama & 26 & waynesville, nc & childhood obesity prevention coach & "teaching men to cook" & week 2 \\
11 & daniela perez-reyes & 28 & haleiwa, hi & bartender/caterer & "peruvian princess" & week 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where occupation = 'private chef/model' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>age</th>
<th>hometown</th>
<th>occupation</th>
<th>culinary p.o.v.</th>
<th>eliminated</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>damaris phillips</td>
<td>31</td>
<td>louisville, ky</td>
<td>culinary teacher</td>
<td>"modern southern food"</td>
<td>winner</td>
</tr>
<tr>
<th>1</th>
<td>rodney henry</td>
<td>47</td>
<td>baltimore, md</td>
<td>pie shop owner</td>
<td>"pie style"</td>
<td>second place</td>
</tr>
<tr>
<th>2</th>
<td>russell jackson</td>
<td>49</td>
<td>san francisco, ca</td>
<td>underground chef</td>
<td>"seven culinary sins"</td>
<td>third place</td>
</tr>
<tr>
<th>3</th>
<td>stacey poon-kinney</td>
<td>34</td>
<td>san diego, ca</td>
<td>restaurant owner</td>
<td>"vintage with a modern twist"</td>
<td>week 10</td>
</tr>
<tr>
<th>4</th>
<td>nikki dinki</td>
<td>29</td>
<td>new york, ny</td>
<td>food blogger/online host</td>
<td>"semi-vegetarian" / "meat on the side"</td>
<td>week 9</td>
</tr>
<tr>
<th>5</th>
<td>chad rosenthal</td>
<td>37</td>
<td>ambler, pa</td>
<td>restaurant owner</td>
<td>"jewish bbq guy"</td>
<td>week 7</td>
</tr>
<tr>
<th>6</th>
<td>chris hodgson</td>
<td>26</td>
<td>cleveland, oh</td>
<td>chef/restaurateur</td>
<td>"compassion for food"</td>
<td>week 6</td>
</tr>
<tr>
<th>7</th>
<td>viet pham</td>
<td>33</td>
<td>salt lake city, ut</td>
<td>chef/restaurant owner</td>
<td>"the american dream"</td>
<td>week 5</td>
</tr>
<tr>
<th>8</th>
<td>connie "lovely" jackson</td>
<td>27</td>
<td>los angeles, ca</td>
<td>caterer</td>
<td>"party on a plate"</td>
<td>week 4 & week 8(winner of star salvation)</td>
</tr>
<tr>
<th>9</th>
<td>danushka lysek</td>
<td>37</td>
<td>new york, ny</td>
<td>private chef/model</td>
<td>"your private chef"</td>
<td>week 3</td>
</tr>
<tr>
<th>10</th>
<td>andres guillama</td>
<td>26</td>
<td>waynesville, nc</td>
<td>childhood obesity prevention coach</td>
<td>"teaching men to cook"</td>
<td>week 2</td>
</tr>
<tr>
<th>11</th>
<td>daniela perez-reyes</td>
<td>28</td>
<td>haleiwa, hi</td>
<td>bartender/caterer</td>
<td>"peruvian princess"</td>
<td>week 1</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 occupation = 'private chef/model' <table_name> : table | | name | age | hometown | occupation | culinary p.o.v. | eliminated |
|---:|:------------------------|------:|:-------------------|:-----------------------------------|:---------------------------------------|:------------------------------------------|
| 0 | damaris phillips | 31 | louisville, ky | culinary teacher | "modern southern food" | winner |
| 1 | rodney henry | 47 | baltimore, md | pie shop owner | "pie style" | second place |
| 2 | russell jackson | 49 | san francisco, ca | underground chef | "seven culinary sins" | third place |
| 3 | stacey poon-kinney | 34 | san diego, ca | restaurant owner | "vintage with a modern twist" | week 10 |
| 4 | nikki dinki | 29 | new york, ny | food blogger/online host | "semi-vegetarian" / "meat on the side" | week 9 |
| 5 | chad rosenthal | 37 | ambler, pa | restaurant owner | "jewish bbq guy" | week 7 |
| 6 | chris hodgson | 26 | cleveland, oh | chef/restaurateur | "compassion for food" | week 6 |
| 7 | viet pham | 33 | salt lake city, ut | chef/restaurant owner | "the american dream" | week 5 |
| 8 | connie "lovely" jackson | 27 | los angeles, ca | caterer | "party on a plate" | week 4 & week 8(winner of star salvation) |
| 9 | danushka lysek | 37 | new york, ny | private chef/model | "your private chef" | week 3 |
| 10 | andres guillama | 26 | waynesville, nc | childhood obesity prevention coach | "teaching men to cook" | week 2 |
| 11 | daniela perez-reyes | 28 | haleiwa, hi | bartender/caterer | "peruvian princess" | week 1 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( single ) where album = 'marcher dans le sable' col : year | single | charts fr | charts bel wa | charts swi | certification | album row 1 : 1997 | "sur la route" | 14 | none | none | | la derniere annee row 2 : 2000 | "j'en reve encore" | 7 | 4 | none | | marcher dans le sable row 3 : 2001 | "une seule vie (marcher dans le sable)" | 30 | none | none | | marcher dans le sable row 4 : 2001 | "tomber" | 35 | none | none | | marcher dans le sable row 5 : 2004 | "elle s'ennuie" | 35 | none | 73 | | none row 6 : 2004 | "elle danse seule" | 22 | none | 46 | | un homme sans racines row 7 : 2011 | "l'etranger" | 59 | none | none | | sur ma route row 8 : 2013 | "je me souviens de tout" | 130 | none | none | | da palmas | col : count ( "single" ) row 1 : 3 | select count ( single ) where album = 'marcher dans le sable' <table_name> : table \begin{tabular}{llllllll}
\toprule
& year & single & charts fr & charts bel wa & charts swi & certification & album \\
\midrule
0 & 1997 & "sur la route" & 14 & none & none & & la derniere annee \\
1 & 2000 & "j'en reve encore" & 7 & 4 & none & & marcher dans le sable \\
2 & 2001 & "une seule vie (marcher dans le sable)" & 30 & none & none & & marcher dans le sable \\
3 & 2001 & "tomber" & 35 & none & none & & marcher dans le sable \\
4 & 2004 & "elle s'ennuie" & 35 & none & 73 & & none \\
5 & 2004 & "elle danse seule" & 22 & none & 46 & & un homme sans racines \\
6 & 2011 & "l'etranger" & 59 & none & none & & sur ma route \\
7 & 2013 & "je me souviens de tout" & 130 & none & none & & da palmas \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "single" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( single ) where album = 'marcher dans le sable' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>single</th>
<th>charts fr</th>
<th>charts bel wa</th>
<th>charts swi</th>
<th>certification</th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1997</td>
<td>"sur la route"</td>
<td>14</td>
<td>none</td>
<td>none</td>
<td></td>
<td>la derniere annee</td>
</tr>
<tr>
<th>1</th>
<td>2000</td>
<td>"j'en reve encore"</td>
<td>7</td>
<td>4</td>
<td>none</td>
<td></td>
<td>marcher dans le sable</td>
</tr>
<tr>
<th>2</th>
<td>2001</td>
<td>"une seule vie (marcher dans le sable)"</td>
<td>30</td>
<td>none</td>
<td>none</td>
<td></td>
<td>marcher dans le sable</td>
</tr>
<tr>
<th>3</th>
<td>2001</td>
<td>"tomber"</td>
<td>35</td>
<td>none</td>
<td>none</td>
<td></td>
<td>marcher dans le sable</td>
</tr>
<tr>
<th>4</th>
<td>2004</td>
<td>"elle s'ennuie"</td>
<td>35</td>
<td>none</td>
<td>73</td>
<td></td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2004</td>
<td>"elle danse seule"</td>
<td>22</td>
<td>none</td>
<td>46</td>
<td></td>
<td>un homme sans racines</td>
</tr>
<tr>
<th>6</th>
<td>2011</td>
<td>"l'etranger"</td>
<td>59</td>
<td>none</td>
<td>none</td>
<td></td>
<td>sur ma route</td>
</tr>
<tr>
<th>7</th>
<td>2013</td>
<td>"je me souviens de tout"</td>
<td>130</td>
<td>none</td>
<td>none</td>
<td></td>
<td>da palmas</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "single" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( single ) where album = 'marcher dans le sable' <table_name> : table | | year | single | charts fr | charts bel wa | charts swi | certification | album |
|---:|-------:|:----------------------------------------|------------:|:----------------|:-------------|:----------------|:----------------------|
| 0 | 1997 | "sur la route" | 14 | none | none | | la derniere annee |
| 1 | 2000 | "j'en reve encore" | 7 | 4 | none | | marcher dans le sable |
| 2 | 2001 | "une seule vie (marcher dans le sable)" | 30 | none | none | | marcher dans le sable |
| 3 | 2001 | "tomber" | 35 | none | none | | marcher dans le sable |
| 4 | 2004 | "elle s'ennuie" | 35 | none | 73 | | none |
| 5 | 2004 | "elle danse seule" | 22 | none | 46 | | un homme sans racines |
| 6 | 2011 | "l'etranger" | 59 | none | none | | sur ma route |
| 7 | 2013 | "je me souviens de tout" | 130 | none | none | | da palmas | | | | count ( "single" ) |
|---:|---------------------:|
| 0 | 3 | | [
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