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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 6 new columns ({'Subsample', 'Fruit diameter to length ratio', 'Caylx to fruit area ratio', 'Fruit exterior NDAI', 'Fruit interior NDAI', 'Fruit firmness (N)'}) and 3 missing columns ({'TA (g/L)', 'Brix (%)', 'Brix to TA ratio'}).

This happened while the csv dataset builder was generating data using

hf://datasets/koidra/VF_Strawberry/VF_Strawberry/OSU_IndoorStrawKubota/Indoor strawberry phenotyping fruit morphology & firmness data.csv (at revision 1d602a6b3a1b68217904ac863f466244db14b317)

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 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, 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 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Cultivar name: string
              Cultivar ID: string
              Replicate: int64
              Subsample: int64
              Caylx to fruit area ratio: double
              Fruit diameter to length ratio: double
              Fruit interior NDAI: double
              Fruit exterior NDAI: double
              Fruit firmness (N): double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1466
              to
              {'Cultivar name': Value('string'), 'Cultivar ID': Value('string'), 'Replicate': Value('int64'), 'Brix (%)': Value('float64'), 'TA (g/L)': Value('float64'), 'Brix to TA ratio': Value('float64')}
              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 1456, 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 1055, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, 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 1702, 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 1833, 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 6 new columns ({'Subsample', 'Fruit diameter to length ratio', 'Caylx to fruit area ratio', 'Fruit exterior NDAI', 'Fruit interior NDAI', 'Fruit firmness (N)'}) and 3 missing columns ({'TA (g/L)', 'Brix (%)', 'Brix to TA ratio'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/koidra/VF_Strawberry/VF_Strawberry/OSU_IndoorStrawKubota/Indoor strawberry phenotyping fruit morphology & firmness data.csv (at revision 1d602a6b3a1b68217904ac863f466244db14b317)
              
              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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Cultivar name
string
Cultivar ID
string
Replicate
int64
Brix (%)
float64
TA (g/L)
float64
Brix to TA ratio
float64
Benton
K14
1
10.3
9.16
1.12
Benton
K14
2
9.9
9.86
1
Benton
K14
3
9.3
10.25
0.91
Bountiful
K01
1
7.5
13.9
0.54
Bountiful
K01
2
8.1
13.58
0.6
Bountiful
K01
3
7.1
11.53
0.62
Chandler
K09
1
7.5
9.99
0.75
Chandler
K09
2
7.7
9.99
0.77
Chandler
K09
3
7.3
9.99
0.73
Dover
K06
1
6.4
7.88
0.81
Dover
K06
2
6.8
8.2
0.83
Dover
K06
3
7.2
9.54
0.75
Earliglow
K10
1
9.6
9.99
0.96
Earliglow
K10
2
9.4
11.01
0.85
Earliglow
K10
3
9.9
10.25
0.97
Elsanta
K32
1
8.8
10.18
0.86
Elsanta
K32
2
7.1
9.41
0.75
Elsanta
K32
3
8.5
9.48
0.9
Honeoye
K27
1
8.1
10.05
0.81
Honeoye
K27
2
9.3
10.25
0.91
Honeoye
K27
3
7.4
10.05
0.74
Hood
K13
1
10.9
10.37
1.05
Hood
K13
2
10.9
9.67
1.13
Hood
K13
3
11.2
10.69
1.05
Mara des Bois
K08
1
8.1
8.2
0.99
Mara des Bois
K08
2
8
8.07
0.99
Mara des Bois
K08
3
7.8
7.24
1.08
Marshall
K33
1
8.6
10.05
0.86
Marshall
K33
2
9.7
10.69
0.91
Marshall
K33
3
9.9
10.76
0.92
Melody
K02
1
6.5
7.36
0.88
Melody
K02
2
6.3
7.43
0.85
Melody
K02
3
6.4
7.43
0.86
Miyazaki
K29
1
9.8
10.69
0.92
Miyazaki
K29
2
9.1
10.44
0.87
Miyazaki
K29
3
8.9
10.89
0.82
NW 90054-37
K21
1
11.8
12.23
0.96
NW 90054-37
K21
2
11.3
12.36
0.91
NW 90054-37
K21
3
12.5
11.66
1.07
Nyohou
K30
1
9.7
11.4
0.85
Nyohou
K30
2
10.5
10.63
0.99
Nyohou
K30
3
10.3
10.76
0.96
ORUS 1267-236
K31
1
7.4
10.44
0.71
ORUS 1267-236
K31
2
7.6
10.12
0.75
ORUS 1267-236
K31
3
8.8
10.63
0.83
ORUS 740-7
K20
1
9.3
10.44
0.89
ORUS 740-7
K20
2
8.8
9.86
0.89
ORUS 740-7
K20
3
9.7
10.18
0.95
Perle de Prague
K11
1
9.2
11.72
0.79
Perle de Prague
K11
2
9.7
12.49
0.78
Perle de Prague
K11
3
9
12.42
0.72
Puget Beauty
K17
1
8.5
8.33
1.02
Puget Beauty
K17
2
9.4
9.03
1.04
Puget Beauty
K17
3
8.2
8.45
0.97
Redchief
K25
1
9.2
11.21
0.82
Redchief
K25
2
9.1
11.01
0.83
Redchief
K25
3
9
11.08
0.81
Shuksan
K12
1
9.6
11.34
0.85
Shuksan
K12
2
9.8
11.85
0.83
Shuksan
K12
3
9
11.21
0.8
Sweet Sunrise
K15
1
8.5
10.31
0.82
Sweet Sunrise
K15
2
8.5
10.05
0.85
Sweet Sunrise
K15
3
8.7
9.99
0.87
Tamella
K22
1
4.4
5.96
0.74
Tamella
K22
2
4.8
5.96
0.81
Tamella
K22
3
5
6.15
0.81
Tangi
K04
1
9.7
12.68
0.76
Tangi
K04
2
9.5
13.45
0.71
Tangi
K04
3
9.9
13.45
0.74
Benton
K14
1
null
null
null
Benton
K14
1
null
null
null
Benton
K14
1
null
null
null
Benton
K14
2
null
null
null
Benton
K14
2
null
null
null
Benton
K14
2
null
null
null
Benton
K14
3
null
null
null
Benton
K14
3
null
null
null
Benton
K14
3
null
null
null
Bountiful
K01
1
null
null
null
Bountiful
K01
1
null
null
null
Bountiful
K01
1
null
null
null
Bountiful
K01
2
null
null
null
Bountiful
K01
2
null
null
null
Bountiful
K01
2
null
null
null
Bountiful
K01
3
null
null
null
Bountiful
K01
3
null
null
null
Bountiful
K01
3
null
null
null
Chandler
K09
1
null
null
null
Chandler
K09
1
null
null
null
Chandler
K09
1
null
null
null
Chandler
K09
2
null
null
null
Chandler
K09
2
null
null
null
Chandler
K09
2
null
null
null
Chandler
K09
3
null
null
null
Chandler
K09
3
null
null
null
Chandler
K09
3
null
null
null
Dover
K06
1
null
null
null
Dover
K06
1
null
null
null
Dover
K06
1
null
null
null
Dover
K06
2
null
null
null
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