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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Float value 30.4 was truncated converting to int64
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2245, in cast_table_to_schema
                  arrays = [
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2246, in <listcomp>
                  cast_array_to_feature(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2102, in cast_array_to_feature
                  return array_cast(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1949, in array_cast
                  return array.cast(pa_type)
                File "pyarrow/array.pxi", line 996, in pyarrow.lib.Array.cast
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/compute.py", line 404, in cast
                  return call_function("cast", [arr], options, memory_pool)
                File "pyarrow/_compute.pyx", line 590, in pyarrow._compute.call_function
                File "pyarrow/_compute.pyx", line 385, in pyarrow._compute.Function.call
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Float value 30.4 was truncated converting to int64
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1897, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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age
int64
bmi
float64
children
int64
sex
string
smoker
string
region
string
prediction
float64
40
0
2
female
no
southeast
-1,459.497547
46
2
2
male
no
northwest
1,025.137071
49
22
1
male
no
northeast
8,483.31377
39
24
2
male
no
northeast
7,013.020599
25
29
2
female
no
northeast
5,119.415169
25
29
2
female
yes
northeast
28,770.544025
25
29
2
female
no
northeast
5,119.415169
25
29
2
female
no
southwest
4,309.615815
25
29
2
female
no
northwest
4,748.737843
25
29
2
female
no
northeast
5,119.415169
20
19
11
female
yes
northwest
27,571.571702
23
19
11
female
yes
northwest
28,342.498819
26
19
11
female
yes
northwest
29,113.425937
31
19
11
female
yes
northwest
30,398.304466
39
19
11
female
yes
northwest
32,454.110112
39
21
11
female
yes
northwest
33,128.295216
39
21
7
female
yes
northwest
31,427.180082
39
21
7
male
no
northwest
7,757.459535
39
21
7
male
no
southeast
7,470.272564
39
21
7
male
no
southeast
7,470.272564
39
21
7
male
no
southwest
7,318.337507
39
21
7
male
no
northwest
7,757.459535
30
25
2
male
no
southeast
4,379.467502
27
30.4
3
female
no
northwest
6,159.897611
23
32.7
3
male
no
southwest
5,449.593937
22
33.77
0
male
no
southeast
4,429.405969
45
39.805
0
male
no
northeast
13,032.065051
52
18.335
0
female
no
northwest
7,241.432267
26
29.92
1
female
no
southeast
4,603.372943
61
36.1
3
male
no
southwest
16,360.785435
47
19.57
1
male
no
northwest
6,779.550131
51
36.385
3
female
no
northwest
14,344.813474
35
35.86
2
female
no
southeast
9,343.762837
22
52.58
1
male
yes
southeast
34,846.524511
26
31.065
0
male
no
northwest
4,832.66041
19
24.51
1
female
no
northwest
1,268.059266
18
26.125
0
male
no
northeast
1,482.294883
42
37.18
2
male
no
southeast
11,568.963255
47
26.6
2
female
no
northeast
9,963.858573
64
37.905
0
male
no
northwest
16,903.450287
30
27.7
0
female
no
southwest
4,305.716459
42
24.985
2
female
no
northwest
7,763.898246
47
25.41
1
male
yes
southeast
32,112.11252
43
32.6
2
male
no
southwest
10,130.120015
21
36.85
0
male
no
southeast
5,210.675323
43
26.885
0
female
yes
northwest
31,461.921089
32
28.93
1
male
yes
southeast
29,444.042715
22
27.1
0
female
no
southwest
2,047.655282
44
38.06
1
male
no
southeast
11,954.277329
31
25.935
1
male
no
northwest
4,813.532931
21
16.815
1
female
no
northeast
-441.239183
62
38.095
2
female
no
northeast
17,693.373045
59
27.83
3
female
no
southeast
13,229.605368
37
30.78
0
female
yes
northeast
31,603.71967
60
40.92
0
male
yes
southeast
40,255.823393
30
28.405
1
female
no
northwest
5,407.76752
26
33.915
1
male
no
northwest
6,218.652966
50
31.825
0
male
yes
northeast
35,278.073871
41
33.06
2
female
no
northwest
10,228.944897
30
19.95
3
female
no
northwest
3,408.20756
33
35.75
2
male
no
southeast
8,774.139553
48
33.33
0
female
no
southeast
10,981.045289
55
27.645
0
male
no
northwest
11,132.099351
64
26.885
0
female
yes
northwest
36,858.410912
19
22.515
0
female
no
northwest
170.280841
19
25.745
1
female
no
northwest
1,684.368568
50
32.11
2
male
no
northeast
12,573.57396
23
36.67
2
female
yes
northeast
30,842.092487
24
35.86
0
male
no
southeast
5,647.880814
30
23.655
3
female
yes
northwest
28,308.264321
26
30
1
male
no
southwest
4,459.813597
19
30.59
0
male
no
northwest
2,873.711507
28
33
2
female
no
southeast
6,580.848198
50
25.6
0
female
no
southwest
8,737.336217
25
20.8
1
female
no
southwest
1,120.178105
54
32.68
0
female
no
northeast
12,961.653662
25
34.485
0
female
no
northwest
5,747.132923
41
34.2
2
male
no
northwest
10,594.638715
20
29.6
0
female
no
southwest
2,376.43525
36
35.2
1
male
yes
southeast
32,585.515839
30
27.93
0
female
no
northeast
5,193.047101
19
17.48
0
male
no
northwest
-1,545.571849
23
28.12
0
female
no
northwest
3,087.587418
62
32.11
0
male
no
northeast
14,806.724863
27
24.75
0
female
yes
southeast
26,343.430227
51
18.05
0
female
no
northwest
6,888.385184
56
34.43
0
male
no
southeast
13,389.061052
49
25.6
2
male
yes
southwest
32,963.455242
35
23.465
2
female
no
northeast
5,823.364952
56
35.8
1
female
no
southwest
14,142.813265
19
28.6
5
female
no
southwest
3,908.76091
43
26.7
2
female
yes
southwest
31,810.994506
53
36.6
3
male
no
southwest
14,473.526065
40
41.42
1
female
no
northwest
12,364.784142
20
33
0
female
no
southeast
3,674.484984
28
17.29
0
female
no
northeast
1,092.430936
58
33.1
0
female
no
southwest
13,321.336003
42
40.37
2
female
yes
southeast
36,314.009043
52
26.4
3
male
no
southeast
10,930.141387
37
46.53
3
male
no
southeast
13,861.17887
End of preview.

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