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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 11 new columns ({'First author', 'Published year', 'Study type', 'Country', 'Number of patients', 'Chemotherapy regimen', 'Hazard Ratio Estimation Method', 'Outcomes', 'Follow-up period (median) (year)', 'Pathological complete response rate', 'Clinical stage'}) and 6 missing columns ({'Antibody Immunotherapy Agents', 'Univariate or Multivariate Model', 'retrospective or prospective cohort', 'Total Numebr of Participants', 'Cancer Type', 'immune-related adverse event grades'}).
This happened while the csv dataset builder was generating data using
hf://datasets/zifeng-ai/TrialReviewBench/TrialReviewBench-data-extraction/32539858.csv (at revision 6dfc322004341212eb905a6874ccfae416b9f9f5)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 643, 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 2293, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
First author: string
Published year: int64
Country: string
Study type: string
Number of patients: string
Clinical stage: string
Chemotherapy regimen: string
Pathological complete response rate: string
Follow-up period (median) (year): double
Hazard Ratio Estimation Method: string
Outcomes: string
PMID: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1866
to
{'PMID': Value(dtype='int64', id=None), 'Cancer Type': Value(dtype='string', id=None), 'Antibody Immunotherapy Agents': Value(dtype='string', id=None), 'Total Numebr of Participants': Value(dtype='int64', id=None), 'immune-related adverse event grades': Value(dtype='string', id=None), 'Univariate or Multivariate Model': Value(dtype='string', id=None), 'retrospective or prospective cohort': Value(dtype='string', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1433, 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 1050, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, 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 1742, 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 1873, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 11 new columns ({'First author', 'Published year', 'Study type', 'Country', 'Number of patients', 'Chemotherapy regimen', 'Hazard Ratio Estimation Method', 'Outcomes', 'Follow-up period (median) (year)', 'Pathological complete response rate', 'Clinical stage'}) and 6 missing columns ({'Antibody Immunotherapy Agents', 'Univariate or Multivariate Model', 'retrospective or prospective cohort', 'Total Numebr of Participants', 'Cancer Type', 'immune-related adverse event grades'}).
This happened while the csv dataset builder was generating data using
hf://datasets/zifeng-ai/TrialReviewBench/TrialReviewBench-data-extraction/32539858.csv (at revision 6dfc322004341212eb905a6874ccfae416b9f9f5)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PMID
int64 | Cancer Type
string | Antibody Immunotherapy Agents
string | Total Numebr of Participants
int64 | immune-related adverse event grades
string | Univariate or Multivariate Model
string | retrospective or prospective cohort
string |
|---|---|---|---|---|---|---|
26,222,619
|
multiple cancer types
|
pembrolizumab
| 83
|
1–3
|
multivariate
|
retrospective cohort
|
26,446,948
|
Melanoma
|
nivolumab
| 143
|
1–3
|
multivariate
|
retrospective cohort
|
28,975,219
|
non-small-cell lung carcinoma
|
nivolumab
| 130
|
1–4
|
multivariate
|
retrospective cohort
|
29,296,533
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab
| 58
|
1–2
|
multivariate
|
retrospective cohort
|
28,652,280
|
multiple cancer types
|
nivolumab/pembrolizumab
| 173
|
1–2
|
multivariate
|
retrospective cohort
|
27,998,967
|
non-small-cell lung carcinoma
|
pembrolizumab
| 48
|
1–3
|
univariate
|
prospective cohort
|
27,510,892
|
Melanoma
|
nivolumab
| 35
|
1–2
|
univariate
|
retrospective cohort
|
30,442,524
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab
| 270
|
1–4
|
univariate
|
retrospective cohort
|
30,589,930
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab
| 137
|
1–4
|
univariate
|
retrospective cohort
|
29,290,265
|
non-small-cell lung carcinoma
|
nivolumab
| 18
|
1–4
|
univariate
|
retrospective cohort
|
30,682,533
|
multiple cancer types
|
nivolumab/pembrolizumab
| 106
|
1–4
|
multivariate
|
retrospective cohort
|
30,506,406
|
non-small-cell lung carcinoma
|
nivolumab
| 195
|
1–4
|
multivariate
|
retrospective cohort
|
30,506,406
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab
| 246
|
1–2
|
multivariate
|
retrospective cohort
|
29,975,414
|
Melanoma
|
ipilimumab
| 281
|
N.A.
|
univariate
|
retrospective cohort
|
30,539,281
|
Melanoma
|
nivolumab/pembrolizumab
| 173
|
1–5
|
multivariate
|
retrospective cohort
|
30,311,424
|
non-small-cell lung carcinoma
|
nivolumab
| 104
|
1–4
|
multivariate
|
retrospective cohort
|
30,197,259
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab/atezolizumab
| 91
|
1–4
|
univariate
|
retrospective cohort
|
29,382,669
|
non-small-cell lung carcinoma
|
pembrolizumab
| 97
|
1–4
|
multivariate
|
retrospective cohort
|
29,656,747
|
non-small-cell lung carcinoma
|
nivolumab
| 613
|
≥3
|
multivariate
|
retrospective cohort
|
30,528,047
|
Melanoma
|
nivolumab
| 15
|
1–2
|
multivariate
|
retrospective cohort
|
30,782,080
|
multiple cancer types
|
nivolumab/pembrolizumab
| 103
|
1–4
|
univariate
|
retrospective cohort
|
30,885,550
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab
| 559
|
1–4
|
multivariate
|
retrospective cohort
|
30,911,841
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab
| 133
|
1–4
|
multivariate
|
retrospective cohort
|
31,021,392
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab
| 83
|
N.A.
|
univariate
|
prospective cohort
|
30,944,023
|
renal cell carcinoma
|
nivolumab
| 389
|
1–4
|
multivariate
|
retrospective cohort
|
31,086,392
|
multiple cancer types
|
nivolumab
| 191
|
N.A.
|
univariate
|
retrospective cohort
|
31,081,424
|
non-small-cell lung carcinoma
|
nivolumab/pembrolizumab
| 112
|
3–4
|
univariate
|
retrospective cohort
|
30,935,847
|
renal cell carcinoma
|
nivolumab
| 47
|
1–4
|
multivariate
|
retrospective cohort
|
30,425,107
|
Melanoma
|
ipilimumab
| 133
|
1–4
|
univariate
|
retrospective cohort
|
31,088,239
|
Melanoma
|
ipilimumab
| 100
|
1–3
|
univariate
|
retrospective cohort
|
29,470,805
| null | null | null | null | null | null |
21,725,686
| null | null | null | null | null | null |
20,599,225
| null | null | null | null | null | null |
null | null | null | null | null | null | null |
null | null | null | null | null | null | null |
30,290,661
| null | null | null | null | null | null |
29,348,858
| null | null | null | null | null | null |
31,536,530
| null | null | null | null | null | null |
31,280,213
| null | null | null | null | null | null |
31,700,918
| null | null | null | null | null | null |
31,205,914
| null | null | null | null | null | null |
30,181,755
| null | null | null | null | null | null |
30,043,207
| null | null | null | null | null | null |
29,230,663
| null | null | null | null | null | null |
27,709,313
| null | null | null | null | null | null |
25,820,754
| null | null | null | null | null | null |
23,677,653
| null | null | null | null | null | null |
11,821,454
| null | null | null | null | null | null |
29,718,092
| null | null | null | null | null | null |
29,860,922
| null | null | null | null | null | null |
29,804,902
| null | null | null | null | null | null |
31,563,959
| null | null | null | null | null | null |
30,675,515
| null | null | null | null | null | null |
25,524,798
| null | null | null | null | null | null |
30,632,023
| null | null | null | null | null | null |
26,947,331
| null | null | null | null | null | null |
16,140,090
| null | null | null | null | null | null |
20,078,235
| null | null | null | null | null | null |
19,913,249
| null | null | null | null | null | null |
17,081,323
| null | null | null | null | null | null |
17,070,244
| null | null | null | null | null | null |
15,890,586
| null | null | null | null | null | null |
27,637,505
| null | null | null | null | null | null |
7,850,294
| null | null | null | null | null | null |
7,526,002
| null | null | null | null | null | null |
19,076,132
| null | null | null | null | null | null |
3,917,295
| null | null | null | null | null | null |
1,523,739
| null | null | null | null | null | null |
3,411,670
| null | null | null | null | null | null |
19,453,762
| null | null | null | null | null | null |
9,827,721
| null | null | null | null | null | null |
9,697,786
| null | null | null | null | null | null |
24,008,772
| null | null | null | null | null | null |
15,758,726
| null | null | null | null | null | null |
9,474,190
| null | null | null | null | null | null |
28,761,588
| null | null | null | null | null | null |
27,347,619
| null | null | null | null | null | null |
27,347,619
| null | null | null | null | null | null |
19,653,872
| null | null | null | null | null | null |
11,061,900
| null | null | null | null | null | null |
30,385,835
| null | null | null | null | null | null |
31,075,058
| null | null | null | null | null | null |
16,815,663
| null | null | null | null | null | null |
30,006,908
| null | null | null | null | null | null |
21,420,229
| null | null | null | null | null | null |
30,126,045
| null | null | null | null | null | null |
19,303,197
| null | null | null | null | null | null |
30,790,014
| null | null | null | null | null | null |
1,873,780
| null | null | null | null | null | null |
14,532,787
| null | null | null | null | null | null |
28,396,223
| null | null | null | null | null | null |
24,314,031
| null | null | null | null | null | null |
18,639,970
| null | null | null | null | null | null |
16,140,090
| null | null | null | null | null | null |
20,078,235
| null | null | null | null | null | null |
19,913,249
| null | null | null | null | null | null |
17,081,323
| null | null | null | null | null | null |
17,070,244
| null | null | null | null | null | null |
15,890,586
| null | null | null | null | null | null |
27,637,505
| null | null | null | null | null | null |
End of preview.
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