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MrAlvaroA
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insurance-charge-mlops-logs

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Float value 27.06 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 2013, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp>
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, 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 1802, 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 2116, in cast_array_to_feature
                  return array_cast(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1963, 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 27.06 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 1396, 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 1045, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1029, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1124, 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 1884, 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 2040, 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	25	1	male	yes	southeast	21,353.78411
25	25	0	male	yes	northeast	19,120.433964
52	19	1	female	no	northeast	10,749.357152
25	25	2	female	no	northwest	6,672.529222
25	25	0	male	yes	northeast	19,120.433964
20	33	1	male	no	southwest	3,856.881325
26	27.06	0	male	yes	southeast	19,723.24155
19	30.4	0	male	no	southwest	1,558.698029
35	35.86	2	female	no	southeast	6,503.653788
43	26.7	2	female	yes	southwest	24,600.168204
40	32.775	1	male	yes	northeast	39,947.78888
52	18.335	0	female	no	northwest	10,823.823171
42	30	0	male	yes	southwest	36,291.91418
40	29.3	4	female	no	southwest	7,715.080359
20	33	1	male	no	southwest	3,856.881325
26	27.06	0	male	yes	southeast	19,723.24155
19	30.4	0	male	no	southwest	1,558.698029
35	35.86	2	female	no	southeast	6,503.653788
43	26.7	2	female	yes	southwest	24,600.168204
40	32.775	1	male	yes	northeast	39,947.78888
52	18.335	0	female	no	northwest	10,823.823171
42	30	0	male	yes	southwest	36,291.91418
40	29.3	4	female	no	southwest	7,715.080359
52	26.4	3	male	no	southeast	15,874.709581
43	35.64	1	female	no	southeast	12,792.415999
32	29.8	2	female	no	southwest	6,617.863053
45	25.7	3	female	no	southwest	10,720.927144
29	22.515	3	male	no	northeast	7,547.869931
50	28.12	3	female	no	northwest	11,592.013487
25	22.515	1	female	no	northwest	7,363.863204
57	23.18	0	female	no	northwest	11,942.085005
63	27.74	0	female	yes	northeast	27,906.852246
21	25.7	4	male	yes	southwest	17,640.039595
58	32.395	1	female	no	northeast	13,098.904842
62	38.095	2	female	no	northeast	19,521.850423
49	28.69	3	male	no	northwest	10,872.226983
31	27.645	2	male	no	northeast	5,389.432632
19	24.51	1	female	no	northwest	4,307.293571
18	21.47	0	male	no	northeast	1,707.356344
56	35.8	1	female	no	southwest	12,007.119041
33	28.27	1	female	no	southeast	4,983.803713
21	33.63	2	female	no	northwest	15,697.328104
52	27.36	0	male	yes	northwest	24,001.672361
28	23.845	2	female	no	northwest	6,147.161104
59	27.5	1	male	no	southwest	14,926.912973
25	25.74	0	male	no	southeast	2,527.940727
19	22.515	0	female	no	northwest	2,081.645044
60	18.335	0	female	no	northeast	13,359.893668
34	34.675	0	male	no	northeast	5,464.885474
30	31.57	3	male	no	southeast	5,628.912692
37	30.8	2	female	no	southeast	7,924.582563
54	32.68	0	female	no	northeast	12,046.873903
48	40.15	0	male	no	southeast	10,074.178375
49	29.83	1	male	no	northeast	10,977.702768
43	26.885	0	female	yes	northwest	24,110.033802
20	33	0	female	no	southeast	3,289.187362
23	32.7	3	male	no	southwest	6,392.240935
42	40.37	2	female	yes	southeast	45,054.046187
34	33.7	1	female	no	southwest	6,769.546594
47	26.125	1	female	yes	northeast	30,498.555886
53	36.86	3	female	yes	northwest	52,088.260714
47	38.94	2	male	yes	southeast	45,663.358477
25	32.23	1	female	no	southeast	3,911.425673
63	31.8	0	female	no	southwest	13,800.810431
29	35.5	2	male	yes	southwest	42,111.41183
20	29.6	0	female	no	southwest	2,169.392399
30	19.95	3	female	no	northwest	5,730.976429
19	25.175	0	male	no	northwest	1,638.537113
36	26.885	0	female	no	northwest	5,092.828205
42	37.18	2	male	no	southeast	8,417.028686
19	17.48	0	male	no	northwest	1,839.278246
49	42.68	2	female	no	southeast	9,759.209394
54	47.41	0	female	yes	southeast	46,820.437459
36	29.92	0	female	no	southeast	5,297.48278
30	24.4	3	male	yes	southwest	19,706.11267
43	38.06	2	male	yes	southeast	44,732.138761
19	30.59	0	male	no	northwest	2,280.714362
22	32.11	0	male	no	northwest	2,398.583555
23	27.36	1	male	no	northwest	7,024.299449
22	52.58	1	male	yes	southeast	40,425.754572
61	23.655	0	male	no	northeast	13,495.512731
64	40.48	0	male	no	southeast	14,371.032407
42	34.1	0	male	no	southwest	7,709.25733
46	28.05	1	female	no	southeast	9,022.72994
52	37.525	2	female	no	northwest	16,594.967311
58	27.17	0	female	no	northwest	12,832.161307
39	32.34	2	male	no	southeast	12,633.905155
56	25.65	0	female	no	northwest	12,810.554094
61	21.09	0	female	no	northwest	14,535.452677
50	32.11	2	male	no	northeast	10,552.456267
19	28.9	0	female	no	southwest	1,778.607396
31	36.3	2	male	yes	southwest	46,285.873827
52	24.13	1	female	yes	northwest	23,625.582082
26	33.915	1	male	no	northwest	6,164.779556
53	22.88	1	female	yes	southeast	23,638.468912
25	34.485	0	female	no	northwest	3,752.584159
23	37.1	3	male	no	southwest	5,461.425918
26	35.42	0	male	no	southeast	2,847.758534
41	33.06	2	female	no	northwest	7,695.77104
22	23.18	0	female	no	northeast	3,169.619811

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