Datasets:
t4tiana
/
store-sales-time-series-forecasting

Dataset card Viewer Files Community
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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 1 missing columns ({'sales'})

This happened while the csv dataset builder was generating data using

hf://datasets/t4tiana/store-sales-time-series-forecasting/test.csv (at revision 1ac138dfdfafc520bc29831e73373954b1b7bc05)

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 2011, 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 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              id: int64
              date: string
              store_nbr: int64
              family: string
              onpromotion: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 818
              to
              {'id': Value(dtype='int64', id=None), 'date': Value(dtype='string', id=None), 'store_nbr': Value(dtype='int64', id=None), 'family': Value(dtype='string', id=None), 'sales': Value(dtype='float64', id=None), 'onpromotion': 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 1321, 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 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2013, 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 1 missing columns ({'sales'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/t4tiana/store-sales-time-series-forecasting/test.csv (at revision 1ac138dfdfafc520bc29831e73373954b1b7bc05)
              
              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
date
string
store_nbr
int64
family
string
sales
float64
onpromotion
int64
0
2013-01-01
1
AUTOMOTIVE
0
0
1
2013-01-01
1
BABY CARE
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0
2
2013-01-01
1
BEAUTY
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3
2013-01-01
1
BEVERAGES
0
0
4
2013-01-01
1
BOOKS
0
0
5
2013-01-01
1
BREAD/BAKERY
0
0
6
2013-01-01
1
CELEBRATION
0
0
7
2013-01-01
1
CLEANING
0
0
8
2013-01-01
1
DAIRY
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0
9
2013-01-01
1
DELI
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2013-01-01
1
EGGS
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2013-01-01
1
FROZEN FOODS
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0
12
2013-01-01
1
GROCERY I
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0
13
2013-01-01
1
GROCERY II
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2013-01-01
1
HARDWARE
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0
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2013-01-01
1
HOME AND KITCHEN I
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0
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2013-01-01
1
HOME AND KITCHEN II
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2013-01-01
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HOME APPLIANCES
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2013-01-01
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HOME CARE
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2013-01-01
1
LADIESWEAR
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2013-01-01
1
LAWN AND GARDEN
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2013-01-01
1
LINGERIE
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2013-01-01
1
LIQUOR,WINE,BEER
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23
2013-01-01
1
MAGAZINES
0
0
24
2013-01-01
1
MEATS
0
0
25
2013-01-01
1
PERSONAL CARE
0
0
26
2013-01-01
1
PET SUPPLIES
0
0
27
2013-01-01
1
PLAYERS AND ELECTRONICS
0
0
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2013-01-01
1
POULTRY
0
0
29
2013-01-01
1
PREPARED FOODS
0
0
30
2013-01-01
1
PRODUCE
0
0
31
2013-01-01
1
SCHOOL AND OFFICE SUPPLIES
0
0
32
2013-01-01
1
SEAFOOD
0
0
33
2013-01-01
10
AUTOMOTIVE
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0
34
2013-01-01
10
BABY CARE
0
0
35
2013-01-01
10
BEAUTY
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0
36
2013-01-01
10
BEVERAGES
0
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2013-01-01
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BOOKS
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2013-01-01
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BREAD/BAKERY
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2013-01-01
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CELEBRATION
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2013-01-01
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CLEANING
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2013-01-01
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DAIRY
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2013-01-01
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DELI
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2013-01-01
10
EGGS
0
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2013-01-01
10
FROZEN FOODS
0
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45
2013-01-01
10
GROCERY I
0
0
46
2013-01-01
10
GROCERY II
0
0
47
2013-01-01
10
HARDWARE
0
0
48
2013-01-01
10
HOME AND KITCHEN I
0
0
49
2013-01-01
10
HOME AND KITCHEN II
0
0
50
2013-01-01
10
HOME APPLIANCES
0
0
51
2013-01-01
10
HOME CARE
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0
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2013-01-01
10
LADIESWEAR
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0
53
2013-01-01
10
LAWN AND GARDEN
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0
54
2013-01-01
10
LINGERIE
0
0
55
2013-01-01
10
LIQUOR,WINE,BEER
0
0
56
2013-01-01
10
MAGAZINES
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0
57
2013-01-01
10
MEATS
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2013-01-01
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PERSONAL CARE
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2013-01-01
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PET SUPPLIES
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2013-01-01
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PLAYERS AND ELECTRONICS
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2013-01-01
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POULTRY
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2013-01-01
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PREPARED FOODS
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2013-01-01
10
PRODUCE
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0
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2013-01-01
10
SCHOOL AND OFFICE SUPPLIES
0
0
65
2013-01-01
10
SEAFOOD
0
0
66
2013-01-01
11
AUTOMOTIVE
0
0
67
2013-01-01
11
BABY CARE
0
0
68
2013-01-01
11
BEAUTY
0
0
69
2013-01-01
11
BEVERAGES
0
0
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2013-01-01
11
BOOKS
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2013-01-01
11
BREAD/BAKERY
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72
2013-01-01
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CELEBRATION
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73
2013-01-01
11
CLEANING
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0
74
2013-01-01
11
DAIRY
0
0
75
2013-01-01
11
DELI
0
0
76
2013-01-01
11
EGGS
0
0
77
2013-01-01
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FROZEN FOODS
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78
2013-01-01
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GROCERY I
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2013-01-01
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GROCERY II
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80
2013-01-01
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HARDWARE
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2013-01-01
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HOME AND KITCHEN I
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2013-01-01
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HOME AND KITCHEN II
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2013-01-01
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HOME APPLIANCES
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2013-01-01
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HOME CARE
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2013-01-01
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LADIESWEAR
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2013-01-01
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LAWN AND GARDEN
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2013-01-01
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LINGERIE
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2013-01-01
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LIQUOR,WINE,BEER
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2013-01-01
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MAGAZINES
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2013-01-01
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MEATS
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2013-01-01
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PERSONAL CARE
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2013-01-01
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PET SUPPLIES
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PLAYERS AND ELECTRONICS
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2013-01-01
11
POULTRY
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0
95
2013-01-01
11
PREPARED FOODS
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0
96
2013-01-01
11
PRODUCE
0
0
97
2013-01-01
11
SCHOOL AND OFFICE SUPPLIES
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0
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2013-01-01
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SEAFOOD
0
0
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2013-01-01
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AUTOMOTIVE
0
0
End of preview.