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Datasets:
jason1966
/
akashdeepkuila_bakery

Tags:
kaggle
business
marketing
data visualization
data analytics
optimization
License:
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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 5 new columns ({'date_time', 'weekday_weekend', 'Item', 'period_day', 'Transaction'}) and 5 missing columns ({'DayType', 'DateTime', 'TransactionNo', 'Daypart', 'Items'}).

This happened while the csv dataset builder was generating data using

hf://datasets/jason1966/akashdeepkuila_bakery/bakery_sales_revised.csv (at revision 8a2840c3f5490755a1686e4e747c94f92ac15405), [/tmp/hf-datasets-cache/medium/datasets/32240447257559-config-parquet-and-info-jason1966-akashdeepkuila_-45730cc6/hub/datasets--jason1966--akashdeepkuila_bakery/snapshots/8a2840c3f5490755a1686e4e747c94f92ac15405/Bakery.csv (origin=hf://datasets/jason1966/akashdeepkuila_bakery@8a2840c3f5490755a1686e4e747c94f92ac15405/Bakery.csv), /tmp/hf-datasets-cache/medium/datasets/32240447257559-config-parquet-and-info-jason1966-akashdeepkuila_-45730cc6/hub/datasets--jason1966--akashdeepkuila_bakery/snapshots/8a2840c3f5490755a1686e4e747c94f92ac15405/bakery_sales_revised.csv (origin=hf://datasets/jason1966/akashdeepkuila_bakery@8a2840c3f5490755a1686e4e747c94f92ac15405/bakery_sales_revised.csv)]

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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1890, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 760, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Transaction: int64
              Item: string
              date_time: string
              period_day: string
              weekday_weekend: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 858
              to
              {'TransactionNo': Value('int64'), 'Items': Value('string'), 'DateTime': Value('string'), 'Daypart': Value('string'), 'DayType': Value('string')}
              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 1347, 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 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1892, 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 5 new columns ({'date_time', 'weekday_weekend', 'Item', 'period_day', 'Transaction'}) and 5 missing columns ({'DayType', 'DateTime', 'TransactionNo', 'Daypart', 'Items'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/jason1966/akashdeepkuila_bakery/bakery_sales_revised.csv (at revision 8a2840c3f5490755a1686e4e747c94f92ac15405), [/tmp/hf-datasets-cache/medium/datasets/32240447257559-config-parquet-and-info-jason1966-akashdeepkuila_-45730cc6/hub/datasets--jason1966--akashdeepkuila_bakery/snapshots/8a2840c3f5490755a1686e4e747c94f92ac15405/Bakery.csv (origin=hf://datasets/jason1966/akashdeepkuila_bakery@8a2840c3f5490755a1686e4e747c94f92ac15405/Bakery.csv), /tmp/hf-datasets-cache/medium/datasets/32240447257559-config-parquet-and-info-jason1966-akashdeepkuila_-45730cc6/hub/datasets--jason1966--akashdeepkuila_bakery/snapshots/8a2840c3f5490755a1686e4e747c94f92ac15405/bakery_sales_revised.csv (origin=hf://datasets/jason1966/akashdeepkuila_bakery@8a2840c3f5490755a1686e4e747c94f92ac15405/bakery_sales_revised.csv)]
              
              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.

TransactionNo
int64
Items
string
DateTime
string
Daypart
string
DayType
string
1
Bread
2016-10-30 09:58:11
Morning
Weekend
2
Scandinavian
2016-10-30 10:05:34
Morning
Weekend
2
Scandinavian
2016-10-30 10:05:34
Morning
Weekend
3
Hot chocolate
2016-10-30 10:07:57
Morning
Weekend
3
Jam
2016-10-30 10:07:57
Morning
Weekend
3
Cookies
2016-10-30 10:07:57
Morning
Weekend
4
Muffin
2016-10-30 10:08:41
Morning
Weekend
5
Coffee
2016-10-30 10:13:03
Morning
Weekend
5
Pastry
2016-10-30 10:13:03
Morning
Weekend
5
Bread
2016-10-30 10:13:03
Morning
Weekend
6
Medialuna
2016-10-30 10:16:55
Morning
Weekend
6
Pastry
2016-10-30 10:16:55
Morning
Weekend
6
Muffin
2016-10-30 10:16:55
Morning
Weekend
7
Medialuna
2016-10-30 10:19:12
Morning
Weekend
7
Pastry
2016-10-30 10:19:12
Morning
Weekend
7
Coffee
2016-10-30 10:19:12
Morning
Weekend
7
Tea
2016-10-30 10:19:12
Morning
Weekend
8
Pastry
2016-10-30 10:20:51
Morning
Weekend
8
Bread
2016-10-30 10:20:51
Morning
Weekend
9
Bread
2016-10-30 10:21:59
Morning
Weekend
9
Muffin
2016-10-30 10:21:59
Morning
Weekend
10
Scandinavian
2016-10-30 10:25:58
Morning
Weekend
10
Medialuna
2016-10-30 10:25:58
Morning
Weekend
11
Bread
2016-10-30 10:27:21
Morning
Weekend
11
Medialuna
2016-10-30 10:27:21
Morning
Weekend
11
Bread
2016-10-30 10:27:21
Morning
Weekend
12
Jam
2016-10-30 10:30:14
Morning
Weekend
12
Coffee
2016-10-30 10:30:14
Morning
Weekend
12
Tartine
2016-10-30 10:30:14
Morning
Weekend
12
Pastry
2016-10-30 10:30:14
Morning
Weekend
12
Tea
2016-10-30 10:30:14
Morning
Weekend
13
Basket
2016-10-30 10:31:24
Morning
Weekend
13
Bread
2016-10-30 10:31:24
Morning
Weekend
13
Coffee
2016-10-30 10:31:24
Morning
Weekend
14
Bread
2016-10-30 10:32:46
Morning
Weekend
14
Medialuna
2016-10-30 10:32:46
Morning
Weekend
14
Pastry
2016-10-30 10:32:46
Morning
Weekend
15
Mineral water
2016-10-30 10:34:36
Morning
Weekend
15
Scandinavian
2016-10-30 10:34:36
Morning
Weekend
16
Bread
2016-10-30 10:37:08
Morning
Weekend
16
Medialuna
2016-10-30 10:37:08
Morning
Weekend
16
Coffee
2016-10-30 10:37:08
Morning
Weekend
17
Hot chocolate
2016-10-30 10:38:04
Morning
Weekend
18
Farm House
2016-10-30 10:41:56
Morning
Weekend
19
Farm House
2016-10-30 10:43:08
Morning
Weekend
19
Bread
2016-10-30 10:43:08
Morning
Weekend
20
Bread
2016-10-30 10:45:22
Morning
Weekend
20
Medialuna
2016-10-30 10:45:22
Morning
Weekend
21
Coffee
2016-10-30 10:49:29
Morning
Weekend
21
Coffee
2016-10-30 10:49:29
Morning
Weekend
21
Medialuna
2016-10-30 10:49:29
Morning
Weekend
21
Bread
2016-10-30 10:49:29
Morning
Weekend
22
Jam
2016-10-30 10:52:15
Morning
Weekend
23
Scandinavian
2016-10-30 10:53:49
Morning
Weekend
23
Muffin
2016-10-30 10:53:49
Morning
Weekend
24
Bread
2016-10-30 10:54:33
Morning
Weekend
25
Scandinavian
2016-10-30 10:55:22
Morning
Weekend
26
Fudge
2016-10-30 10:56:08
Morning
Weekend
27
Scandinavian
2016-10-30 11:02:19
Morning
Weekend
28
Coffee
2016-10-30 11:03:24
Morning
Weekend
28
Bread
2016-10-30 11:03:24
Morning
Weekend
29
Bread
2016-10-30 11:05:30
Morning
Weekend
29
Jam
2016-10-30 11:05:30
Morning
Weekend
30
Bread
2016-10-30 11:07:19
Morning
Weekend
31
Basket
2016-10-30 11:12:56
Morning
Weekend
32
Scandinavian
2016-10-30 11:16:15
Morning
Weekend
32
Muffin
2016-10-30 11:16:15
Morning
Weekend
33
Coffee
2016-10-30 11:22:49
Morning
Weekend
34
Coffee
2016-10-30 11:25:45
Morning
Weekend
34
Muffin
2016-10-30 11:25:45
Morning
Weekend
35
Muffin
2016-10-30 11:27:34
Morning
Weekend
35
Scandinavian
2016-10-30 11:27:34
Morning
Weekend
36
Tea
2016-10-30 11:33:08
Morning
Weekend
36
Bread
2016-10-30 11:33:08
Morning
Weekend
37
Coffee
2016-10-30 11:37:10
Morning
Weekend
37
Bread
2016-10-30 11:37:10
Morning
Weekend
38
Bread
2016-10-30 11:42:40
Morning
Weekend
38
Tea
2016-10-30 11:42:40
Morning
Weekend
39
Scandinavian
2016-10-30 11:44:31
Morning
Weekend
40
Juice
2016-10-30 11:55:51
Morning
Weekend
40
Tartine
2016-10-30 11:55:51
Morning
Weekend
40
Coffee
2016-10-30 11:55:51
Morning
Weekend
40
Muffin
2016-10-30 11:55:51
Morning
Weekend
41
Scandinavian
2016-10-30 11:57:06
Morning
Weekend
42
Bread
2016-10-30 11:57:45
Morning
Weekend
42
Tea
2016-10-30 11:57:45
Morning
Weekend
43
Scandinavian
2016-10-30 12:00:22
Afternoon
Weekend
43
Fudge
2016-10-30 12:00:22
Afternoon
Weekend
44
Coffee
2016-10-30 12:05:47
Afternoon
Weekend
44
Medialuna
2016-10-30 12:05:47
Afternoon
Weekend
45
Coffee
2016-10-30 12:08:36
Afternoon
Weekend
45
Hot chocolate
2016-10-30 12:08:36
Afternoon
Weekend
45
Medialuna
2016-10-30 12:08:36
Afternoon
Weekend
46
Coffee
2016-10-30 12:09:04
Afternoon
Weekend
47
Ella's Kitchen Pouches
2016-10-30 12:15:29
Afternoon
Weekend
47
Juice
2016-10-30 12:15:29
Afternoon
Weekend
47
Bread
2016-10-30 12:15:29
Afternoon
Weekend
47
Muffin
2016-10-30 12:15:29
Afternoon
Weekend
47
Jam
2016-10-30 12:15:29
Afternoon
Weekend
48
Coffee
2016-10-30 12:17:02
Afternoon
Weekend
End of preview.

Bakery Sales Dataset

Market Basket Analysis : Association Rule Mining

Dataset Info

  • Source: Kaggle
  • Original Size: 0.21 MB
  • Kaggle Downloads: 24,562
  • Files: 2

Files

  • Bakery.csv
  • bakery_sales_revised.csv

Mirrored from Kaggle
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