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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 4 new columns ({'cds', 'users_id', 'date', 'amt'}) and 6 missing columns ({'age', 'gender', 'zone', 'age_category', 'state', 'id'}). This happened while the csv dataset builder was generating data using hf://datasets/ZennyKenny/CDNOW/purchases.csv (at revision 3400bd38e52a012e691bcddd168504187edbfa55) 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 623, 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 users_id: int64 date: string cds: int64 amt: double -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 694 to {'id': Value(dtype='int64', id=None), 'zone': Value(dtype='string', id=None), 'state': Value(dtype='string', id=None), 'gender': Value(dtype='string', id=None), 'age_category': Value(dtype='string', id=None), 'age': Value(dtype='int64', 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 1438, 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 4 new columns ({'cds', 'users_id', 'date', 'amt'}) and 6 missing columns ({'age', 'gender', 'zone', 'age_category', 'state', 'id'}). This happened while the csv dataset builder was generating data using hf://datasets/ZennyKenny/CDNOW/purchases.csv (at revision 3400bd38e52a012e691bcddd168504187edbfa55) 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)
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id
int64 | zone
string | state
string | gender
string | age_category
string | age
int64 |
---|---|---|---|---|---|
1 | Pacific | Oregon | M | young | 26 |
2 | Eastern | New Jersey | M | medium | 36 |
3 | Central | Minnesota | M | young | 17 |
4 | Eastern | Michigan | M | medium | 56 |
5 | Eastern | New Jersey | M | medium | 46 |
6 | Mountain | New Mexico | M | medium | 35 |
7 | Central | Nebraska | F | null | 30 |
8 | Eastern | Indiana | M | young | 20 |
9 | Mountain | Colorado | M | medium | 45 |
10 | Eastern | Ohio | F | medium | 40 |
11 | Eastern | New York | F | medium | 40 |
12 | Eastern | North Carolina | F | medium | 51 |
13 | Eastern | North Carolina | M | young | 28 |
14 | Pacific | California | F | medium | 55 |
15 | Central | Louisiana | M | young | 22 |
16 | Mountain | New Mexico | F | null | 30 |
17 | Eastern | Kentucky | F | medium | 37 |
18 | Central | Louisiana | F | young | 24 |
19 | Central | Texas | M | medium | 53 |
20 | Eastern | Maryland | M | young | 17 |
21 | Central | Illinois | F | medium | 43 |
22 | Central | Louisiana | F | medium | 38 |
23 | Central | North Dakota | F | young | 25 |
24 | Central | Illinois | M | medium | 37 |
25 | Central | Alabama | F | young | 20 |
26 | Eastern | Maryland | F | medium | 41 |
27 | Eastern | Florida | M | medium | 36 |
28 | Eastern | Massachusetts | F | young | 28 |
29 | Central | Texas | F | medium | 44 |
30 | Mountain | New Mexico | F | young | 21 |
31 | Mountain | Arizona | F | young | 21 |
32 | Eastern | Massachusetts | M | young | 28 |
33 | Central | Iowa | F | young | 29 |
34 | Eastern | New York | F | medium | 48 |
35 | Central | Missouri | M | medium | 56 |
36 | Central | Oklahoma | M | medium | 40 |
37 | Central | Oklahoma | F | medium | 46 |
38 | Eastern | Ohio | M | medium | 46 |
39 | Central | Alabama | F | young | 21 |
40 | Eastern | Pennsylvania | F | medium | 57 |
41 | Eastern | North Carolina | M | medium | 42 |
42 | Central | Illinois | F | young | 19 |
43 | Eastern | Michigan | F | medium | 49 |
44 | Eastern | Indiana | M | null | 30 |
45 | Mountain | Arizona | F | medium | 34 |
46 | Mountain | Arizona | F | medium | 35 |
47 | Eastern | New York | M | young | 28 |
48 | Mountain | Colorado | M | medium | 34 |
49 | Mountain | Colorado | F | null | 30 |
50 | Central | Illinois | M | old | 62 |
51 | Central | Illinois | M | null | 30 |
52 | Eastern | North Carolina | M | medium | 39 |
53 | Central | Arkansas | M | null | 30 |
54 | Pacific | Oregon | F | young | 25 |
55 | Central | Iowa | M | medium | 31 |
56 | Mountain | Arizona | F | medium | 40 |
57 | Mountain | Arizona | F | medium | 35 |
58 | Mountain | New Mexico | M | medium | 56 |
59 | Central | Tennessee | F | young | 24 |
60 | Eastern | New Jersey | F | medium | 50 |
61 | Eastern | New York | M | medium | 53 |
62 | Central | Minnesota | M | old | 63 |
63 | Eastern | New York | F | young | 24 |
64 | Central | Louisiana | F | old | 76 |
65 | Eastern | New Jersey | F | old | 67 |
66 | Pacific | Oregon | M | medium | 31 |
67 | Eastern | Delaware | M | medium | 35 |
68 | Eastern | Florida | F | young | 26 |
69 | Central | Tennessee | M | medium | 52 |
70 | Central | Wisconsin | F | medium | 42 |
71 | Central | Texas | M | young | 23 |
72 | Pacific | California | F | young | 29 |
73 | Eastern | New Jersey | M | medium | 57 |
74 | Eastern | New Jersey | F | medium | 41 |
75 | Pacific | California | M | medium | 45 |
76 | Eastern | Pennsylvania | M | young | 18 |
77 | Eastern | Indiana | F | medium | 56 |
78 | Central | Minnesota | F | medium | 48 |
79 | Eastern | Michigan | F | medium | 34 |
80 | Mountain | Idaho | M | medium | 37 |
81 | Central | Texas | F | old | 61 |
82 | Central | Missouri | F | young | 19 |
83 | Central | Texas | F | medium | 44 |
84 | Eastern | New York | F | young | 20 |
85 | Eastern | Pennsylvania | F | medium | 50 |
86 | Pacific | Nevada | F | young | 25 |
87 | Central | Oklahoma | M | young | 18 |
88 | Central | Minnesota | M | medium | 59 |
89 | Mountain | Colorado | M | medium | 38 |
90 | Central | Illinois | M | medium | 41 |
91 | Mountain | Colorado | M | medium | 36 |
92 | Eastern | Massachusetts | M | medium | 46 |
93 | Mountain | Idaho | F | medium | 40 |
94 | Mountain | Colorado | F | medium | 46 |
95 | Eastern | New York | M | medium | 33 |
96 | Mountain | Colorado | M | medium | 47 |
97 | Eastern | Pennsylvania | F | medium | 50 |
98 | Eastern | Kentucky | M | medium | 31 |
99 | Eastern | North Carolina | M | medium | 37 |
100 | Mountain | Arizona | F | young | 25 |
End of preview.
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