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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Float value 25.7 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 25.7 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
int64
children
int64
sex
string
smoker
string
region
string
prediction
float64
40
37
2
female
no
southwest
7,359.319926
40
37
2
female
yes
southwest
43,032.575997
40
37
2
male
yes
southwest
42,426.646516
34
3
1
male
no
northwest
7,824.32104
34
3
1
male
no
northwest
7,824.32104
34
3
1
male
no
northwest
7,824.32104
34
3
1
male
no
northwest
7,824.32104
34
3
1
male
yes
northwest
16,773.531475
34
3
1
male
yes
northwest
16,773.531475
34
3
1
male
yes
northwest
16,773.531475
33
117
1
male
no
northeast
8,168.662122
33
51
1
male
no
northeast
8,168.662122
33
161
1
male
no
northeast
8,168.662122
33
161
3
male
no
northeast
9,770.511679
33
161
3
male
no
southeast
7,026.814738
33
161
3
male
no
southwest
7,104.121182
33
161
3
male
no
northeast
9,770.511679
33
161
3
male
no
northwest
7,471.283578
33
161
3
male
yes
northwest
47,479.38227
33
161
3
male
no
northwest
7,471.283578
33
161
3
male
yes
northwest
47,479.38227
33
161
3
male
no
northwest
7,471.283578
41
86
2
male
no
southeast
8,845.522532
41
86
2
male
no
southeast
8,845.522532
41
86
2
male
yes
southeast
43,995.607406
45
33
1
male
no
southeast
8,395.185167
45
33
1
male
yes
southeast
42,322.717899
19
79
1
male
yes
southeast
39,256.806569
35
83
1
male
yes
southeast
44,146.601789
35
83
1
male
no
southeast
7,415.229663
30
70
5
male
no
southwest
7,180.808139
30
70
5
male
yes
southwest
43,751.113128
36
0
1
male
no
southeast
7,426.367354
23
70
0
female
yes
southeast
39,343.784165
23
70
0
female
no
southeast
5,940.411886
36
54
2
female
yes
northeast
45,374.823615
30
80
2
female
no
southeast
6,754.224766
30
80
2
female
yes
southeast
43,789.698711
17
150
0
male
no
northwest
2,855.636313
45
25.7
3
female
no
southwest
9,975.453542
19
30.59
0
male
no
northwest
3,093.041322
39
32.8
0
female
no
southwest
6,183.392482
18
30.14
0
male
no
southeast
4,472.059219
45
38.285
0
female
no
northeast
11,888.941538
40
24.97
2
male
no
southeast
8,445.92038
47
19.57
1
male
no
northwest
9,804.189541
21
36.85
0
male
no
southeast
2,893.756152
31
25.935
1
male
no
northwest
5,055.123119
43
38.06
2
male
yes
southeast
44,383.556197
59
37.1
1
male
no
southwest
20,813.086292
40
41.42
1
female
no
northwest
7,111.140683
58
27.17
0
female
no
northwest
13,073.332296
46
48.07
2
female
no
northeast
11,040.859798
29
29.64
1
male
no
northeast
5,085.090895
42
37.18
2
male
no
southeast
8,691.872044
27
32.585
3
male
no
northeast
7,964.43015
61
21.09
0
female
no
northwest
15,719.921192
60
18.335
0
female
no
northeast
15,143.63757
26
31.065
0
male
no
northwest
3,597.931183
22
52.58
1
male
yes
southeast
39,256.806569
23
41.91
0
male
no
southeast
4,790.834146
22
39.805
0
female
no
northeast
3,746.225954
18
29.165
0
female
no
northeast
3,559.51485
62
32.11
0
male
no
northeast
13,506.264752
21
26.4
1
female
no
southwest
2,610.618663
62
21.4
0
male
no
southwest
15,314.334706
21
25.7
4
male
yes
southwest
18,451.187378
25
23.9
5
male
no
southwest
6,253.80115
32
33.63
1
male
yes
northeast
42,006.185584
52
46.75
5
female
no
southeast
14,379.356648
51
36.385
3
female
no
northwest
12,600.835905
33
28.27
1
female
no
southeast
5,123.180574
60
35.1
0
female
no
southwest
13,306.365696
18
41.14
0
male
no
southeast
2,538.730157
34
33.25
1
female
no
northeast
7,350.27974
43
35.97
3
male
yes
southeast
42,372.502835
37
30.8
2
female
no
southeast
7,446.633665
22
32.11
0
male
no
northwest
2,309.759849
57
23.18
0
female
no
northwest
11,940.406599
33
35.75
1
male
yes
southeast
44,213.416145
42
30
0
male
yes
southwest
36,157.175321
52
26.4
3
male
no
southeast
13,949.845152
52
30.875
0
female
no
northeast
11,790.61702
53
36.86
3
female
yes
northwest
48,985.701856
23
24.51
0
male
no
northeast
5,217.211503
36
29.92
0
female
no
southeast
5,061.039801
49
28.69
3
male
no
northwest
11,213.008458
21
35.72
0
female
no
northwest
2,589.487115
28
33
2
female
no
southeast
4,898.811795
49
36.85
0
male
no
southeast
9,950.166112
58
32.395
1
female
no
northeast
12,738.152567
32
28.93
1
male
yes
southeast
20,585.856353
19
22.515
0
female
no
northwest
2,058.847125
39
32.5
1
female
no
southwest
6,735.792071
24
35.86
0
male
no
southeast
2,695.861878
50
28.12
3
female
no
northwest
12,306.200526
63
37.7
0
female
yes
southwest
47,894.153383
32
31.5
1
male
no
southwest
4,749.520027
58
31.825
2
female
no
northeast
14,072.493162
35
23.465
2
female
no
northeast
8,934.909283
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