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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 2 new columns ({'Sales', '#Order'})

This happened while the csv dataset builder was generating data using

hf://datasets/SURESHBEEKHANI/SalesForecastingWOMartStore/TRAIN.csv (at revision 9fad683234cd403a8e67482eb8250e9c4957f28c)

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 1869, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 580, 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 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              ID: string
              Store_id: int64
              Store_Type: string
              Location_Type: string
              Region_Code: string
              Date: string
              Holiday: int64
              Discount: string
              #Order: int64
              Sales: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1403
              to
              {'ID': Value(dtype='string', id=None), 'Store_id': Value(dtype='int64', id=None), 'Store_Type': Value(dtype='string', id=None), 'Location_Type': Value(dtype='string', id=None), 'Region_Code': Value(dtype='string', id=None), 'Date': Value(dtype='string', id=None), 'Holiday': Value(dtype='int64', id=None), 'Discount': 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 1392, 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 1041, 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 999, 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 1740, 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 1871, 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 2 new columns ({'Sales', '#Order'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/SURESHBEEKHANI/SalesForecastingWOMartStore/TRAIN.csv (at revision 9fad683234cd403a8e67482eb8250e9c4957f28c)
              
              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.

ID
string
Store_id
int64
Store_Type
string
Location_Type
string
Region_Code
string
Date
string
Holiday
int64
Discount
string
T1188341
171
S4
L2
R3
2019-06-01
0
No
T1188342
172
S1
L1
R1
2019-06-01
0
No
T1188343
173
S4
L2
R1
2019-06-01
0
No
T1188344
174
S1
L1
R4
2019-06-01
0
No
T1188345
170
S1
L1
R2
2019-06-01
0
No
T1188346
175
S4
L2
R1
2019-06-01
0
No
T1188347
176
S4
L2
R3
2019-06-01
0
No
T1188348
169
S1
L2
R4
2019-06-01
0
No
T1188349
14
S3
L2
R4
2019-06-01
0
No
T1188350
177
S2
L1
R4
2019-06-01
0
No
T1188351
178
S3
L2
R3
2019-06-01
0
No
T1188352
179
S1
L1
R2
2019-06-01
0
No
T1188353
185
S1
L1
R3
2019-06-01
0
No
T1188354
181
S3
L1
R3
2019-06-01
0
No
T1188355
182
S3
L1
R1
2019-06-01
0
No
T1188356
183
S1
L3
R1
2019-06-01
0
No
T1188357
184
S1
L2
R2
2019-06-01
0
No
T1188358
186
S2
L5
R2
2019-06-01
0
No
T1188359
187
S1
L1
R1
2019-06-01
0
No
T1188360
188
S3
L2
R1
2019-06-01
0
No
T1188361
189
S2
L3
R3
2019-06-01
0
No
T1188362
190
S3
L3
R1
2019-06-01
0
No
T1188363
191
S3
L1
R1
2019-06-01
0
No
T1188364
168
S2
L3
R3
2019-06-01
0
No
T1188365
13
S3
L3
R1
2019-06-01
0
No
T1188366
180
S1
L3
R2
2019-06-01
0
No
T1188367
167
S1
L1
R2
2019-06-01
0
No
T1188368
142
S2
L1
R3
2019-06-01
0
No
T1188369
165
S1
L1
R2
2019-06-01
0
No
T1188370
140
S4
L1
R1
2019-06-01
0
No
T1188371
141
S1
L1
R2
2019-06-01
0
No
T1188372
143
S3
L2
R3
2019-06-01
0
No
T1188373
144
S1
L3
R3
2019-06-01
0
No
T1188374
145
S1
L3
R1
2019-06-01
0
No
T1188375
146
S4
L2
R1
2019-06-01
0
No
T1188376
147
S4
L2
R4
2019-06-01
0
No
T1188377
16
S1
L3
R1
2019-06-01
0
No
T1188378
148
S1
L1
R2
2019-06-01
0
No
T1188379
149
S2
L3
R2
2019-06-01
0
No
T1188380
150
S4
L2
R1
2019-06-01
0
No
T1188381
151
S1
L3
R2
2019-06-01
0
No
T1188382
166
S1
L1
R2
2019-06-01
0
No
T1188383
152
S2
L1
R1
2019-06-01
0
No
T1188384
154
S1
L3
R2
2019-06-01
0
No
T1188385
155
S3
L1
R2
2019-06-01
0
No
T1188386
156
S1
L1
R3
2019-06-01
0
No
T1188387
157
S4
L2
R1
2019-06-01
0
No
T1188388
158
S4
L2
R2
2019-06-01
0
No
T1188389
159
S2
L1
R3
2019-06-01
0
No
T1188390
160
S4
L2
R1
2019-06-01
0
Yes
T1188391
161
S1
L1
R3
2019-06-01
0
No
T1188392
162
S4
L1
R2
2019-06-01
0
No
T1188393
15
S4
L2
R1
2019-06-01
0
No
T1188394
163
S1
L2
R3
2019-06-01
0
No
T1188395
164
S1
L1
R3
2019-06-01
0
No
T1188396
153
S4
L2
R1
2019-06-01
0
No
T1188397
192
S1
L1
R3
2019-06-01
0
No
T1188398
246
S3
L1
R3
2019-06-01
0
No
T1188399
194
S1
L1
R2
2019-06-01
0
No
T1188400
224
S1
L2
R2
2019-06-01
0
No
T1188401
225
S1
L1
R1
2019-06-01
0
No
T1188402
226
S2
L5
R4
2019-06-01
0
No
T1188403
227
S4
L2
R1
2019-06-01
0
No
T1188404
228
S1
L1
R1
2019-06-01
0
No
T1188405
229
S1
L1
R2
2019-06-01
0
No
T1188406
230
S2
L4
R4
2019-06-01
0
No
T1188407
231
S4
L2
R3
2019-06-01
0
No
T1188408
232
S1
L1
R4
2019-06-01
0
No
T1188409
233
S1
L3
R3
2019-06-01
0
Yes
T1188410
234
S2
L4
R2
2019-06-01
0
No
T1188411
10
S4
L2
R3
2019-06-01
0
No
T1188412
223
S2
L5
R2
2019-06-01
0
No
T1188413
235
S1
L1
R3
2019-06-01
0
No
T1188414
237
S2
L3
R3
2019-06-01
0
No
T1188415
238
S1
L1
R2
2019-06-01
0
No
T1188416
239
S3
L1
R3
2019-06-01
0
No
T1188417
240
S3
L2
R3
2019-06-01
0
No
T1188418
241
S1
L1
R4
2019-06-01
0
No
T1188419
242
S4
L1
R1
2019-06-01
0
No
T1188420
243
S4
L2
R2
2019-06-01
0
No
T1188421
244
S2
L5
R4
2019-06-01
0
No
T1188422
245
S4
L1
R2
2019-06-01
0
No
T1188423
139
S4
L2
R2
2019-06-01
0
No
T1188424
247
S1
L1
R3
2019-06-01
0
No
T1188425
248
S1
L1
R2
2019-06-01
0
No
T1188426
236
S1
L1
R3
2019-06-01
0
No
T1188427
222
S4
L2
R2
2019-06-01
0
No
T1188428
221
S1
L1
R2
2019-06-01
0
No
T1188429
11
S4
L2
R1
2019-06-01
0
No
T1188430
195
S4
L1
R1
2019-06-01
0
No
T1188431
196
S1
L1
R3
2019-06-01
0
No
T1188432
197
S2
L5
R1
2019-06-01
0
No
T1188433
198
S4
L2
R3
2019-06-01
0
No
T1188434
199
S1
L1
R4
2019-06-01
0
No
T1188435
200
S2
L1
R2
2019-06-01
0
No
T1188436
201
S4
L1
R1
2019-06-01
0
No
T1188437
202
S4
L2
R2
2019-06-01
0
No
T1188438
203
S2
L4
R2
2019-06-01
0
No
T1188439
204
S4
L1
R3
2019-06-01
0
No
T1188440
205
S1
L1
R2
2019-06-01
0
No
End of preview.
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