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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 ({'employee_name', 'type', 'amount', 'employee_id'}) and 4 missing columns ({'hour_amount', 'name', 'day_amount', 'unit_cost'}).

This happened while the csv dataset builder was generating data using

hf://datasets/theethawats98/tdce-example-extended-random/before/generated_employee_usage.csv (at revision 9becd0d2c66f08ad515ad3f70ad21a5cc51174ba)

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 643, 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
              Unnamed: 0: int64
              _id: string
              employee_id: string
              process_id: int64
              employee_name: string
              amount: int64
              duration: double
              type: string
              cost: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1288
              to
              {'Unnamed: 0': Value(dtype='int64', id=None), '_id': Value(dtype='string', id=None), 'process_id': Value(dtype='int64', id=None), 'name': Value(dtype='string', id=None), 'cost': Value(dtype='int64', id=None), 'day_amount': Value(dtype='float64', id=None), 'hour_amount': Value(dtype='int64', id=None), 'unit_cost': Value(dtype='float64', id=None), 'duration': Value(dtype='float64', 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 1436, 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 1053, 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 ({'employee_name', 'type', 'amount', 'employee_id'}) and 4 missing columns ({'hour_amount', 'name', 'day_amount', 'unit_cost'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/theethawats98/tdce-example-extended-random/before/generated_employee_usage.csv (at revision 9becd0d2c66f08ad515ad3f70ad21a5cc51174ba)
              
              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.

Unnamed: 0
int64
_id
string
process_id
int64
name
string
cost
int64
day_amount
float64
hour_amount
int64
unit_cost
float64
duration
float64
1
electric
68,200,213
electric
400,000
24
8
34.722222
9.25
2
water_supply
68,200,213
water_supply
3,000
24
8
0.260417
9.25
4
electric
68,200,212
electric
400,000
24
8
34.722222
49.95
5
water_supply
68,200,212
water_supply
3,000
24
8
0.260417
49.95
7
electric
68,200,211
electric
400,000
24
8
34.722222
11.1
8
water_supply
68,200,211
water_supply
3,000
24
8
0.260417
11.1
10
electric
68,200,210
electric
400,000
24
8
34.722222
48.1
11
water_supply
68,200,210
water_supply
3,000
24
8
0.260417
48.1
13
electric
68,200,209
electric
400,000
24
8
34.722222
46.25
14
water_supply
68,200,209
water_supply
3,000
24
8
0.260417
46.25
17
electric
68,200,208
electric
400,000
24
8
34.722222
44.4
18
electric
68,200,208
electric
400,000
24
8
34.722222
86.95
19
water_supply
68,200,208
water_supply
3,000
24
8
0.260417
44.4
20
water_supply
68,200,208
water_supply
3,000
24
8
0.260417
86.95
22
electric
68,200,207
electric
400,000
24
8
34.722222
86.95
23
water_supply
68,200,207
water_supply
3,000
24
8
0.260417
86.95
26
electric
68,200,206
electric
400,000
24
8
34.722222
118.4
27
electric
68,200,206
electric
400,000
24
8
34.722222
49.95
28
water_supply
68,200,206
water_supply
3,000
24
8
0.260417
118.4
29
water_supply
68,200,206
water_supply
3,000
24
8
0.260417
49.95
32
electric
68,200,205
electric
400,000
24
8
34.722222
118.4
33
electric
68,200,205
electric
400,000
24
8
34.722222
20.35
34
water_supply
68,200,205
water_supply
3,000
24
8
0.260417
118.4
35
water_supply
68,200,205
water_supply
3,000
24
8
0.260417
20.35
37
electric
68,200,204
electric
400,000
24
8
34.722222
118.4
38
water_supply
68,200,204
water_supply
3,000
24
8
0.260417
118.4
40
electric
68,200,203
electric
400,000
24
8
34.722222
118.4
41
water_supply
68,200,203
water_supply
3,000
24
8
0.260417
118.4
43
electric
68,200,202
electric
400,000
24
8
34.722222
1.85
44
water_supply
68,200,202
water_supply
3,000
24
8
0.260417
1.85
46
electric
68,200,189
electric
400,000
24
8
34.722222
24.05
47
water_supply
68,200,189
water_supply
3,000
24
8
0.260417
24.05
49
electric
68,200,188
electric
400,000
24
8
34.722222
11.1
50
water_supply
68,200,188
water_supply
3,000
24
8
0.260417
11.1
52
electric
68,200,187
electric
400,000
24
8
34.722222
48.1
53
water_supply
68,200,187
water_supply
3,000
24
8
0.260417
48.1
55
electric
68,200,186
electric
400,000
24
8
34.722222
44.4
56
water_supply
68,200,186
water_supply
3,000
24
8
0.260417
44.4
59
electric
68,200,185
electric
400,000
24
8
34.722222
53.65
60
electric
68,200,185
electric
400,000
24
8
34.722222
92.5
61
water_supply
68,200,185
water_supply
3,000
24
8
0.260417
53.65
62
water_supply
68,200,185
water_supply
3,000
24
8
0.260417
92.5
64
electric
68,200,184
electric
400,000
24
8
34.722222
92.5
65
water_supply
68,200,184
water_supply
3,000
24
8
0.260417
92.5
67
electric
68,200,183
electric
400,000
24
8
34.722222
5.55
68
water_supply
68,200,183
water_supply
3,000
24
8
0.260417
5.55
70
electric
68,200,182
electric
400,000
24
8
34.722222
18.5
71
water_supply
68,200,182
water_supply
3,000
24
8
0.260417
18.5
73
electric
68,200,181
electric
400,000
24
8
34.722222
149.85
74
water_supply
68,200,181
water_supply
3,000
24
8
0.260417
149.85
77
electric
68,200,180
electric
400,000
24
8
34.722222
38.85
78
electric
68,200,180
electric
400,000
24
8
34.722222
149.85
79
water_supply
68,200,180
water_supply
3,000
24
8
0.260417
38.85
80
water_supply
68,200,180
water_supply
3,000
24
8
0.260417
149.85
82
electric
68,200,167
electric
400,000
24
8
34.722222
173.9
83
water_supply
68,200,167
water_supply
3,000
24
8
0.260417
173.9
85
electric
68,200,166
electric
400,000
24
8
34.722222
377.4
86
water_supply
68,200,166
water_supply
3,000
24
8
0.260417
377.4
88
electric
68,200,165
electric
400,000
24
8
34.722222
90.65
89
water_supply
68,200,165
water_supply
3,000
24
8
0.260417
90.65
91
electric
68,200,164
electric
400,000
24
8
34.722222
323.75
92
water_supply
68,200,164
water_supply
3,000
24
8
0.260417
323.75
94
electric
68,200,163
electric
400,000
24
8
34.722222
401.45
95
water_supply
68,200,163
water_supply
3,000
24
8
0.260417
401.45
99
electric
68,200,162
electric
400,000
24
8
34.722222
225.7
100
electric
68,200,162
electric
400,000
24
8
34.722222
451.4
101
electric
68,200,162
electric
400,000
24
8
34.722222
323.75
102
water_supply
68,200,162
water_supply
3,000
24
8
0.260417
225.7
103
water_supply
68,200,162
water_supply
3,000
24
8
0.260417
451.4
104
water_supply
68,200,162
water_supply
3,000
24
8
0.260417
323.75
106
electric
68,200,161
electric
400,000
24
8
34.722222
323.75
107
water_supply
68,200,161
water_supply
3,000
24
8
0.260417
323.75
109
electric
68,200,160
electric
400,000
24
8
34.722222
451.4
110
water_supply
68,200,160
water_supply
3,000
24
8
0.260417
451.4
112
electric
68,200,159
electric
400,000
24
8
34.722222
59.2
113
water_supply
68,200,159
water_supply
3,000
24
8
0.260417
59.2
115
electric
68,200,158
electric
400,000
24
8
34.722222
40.7
116
water_supply
68,200,158
water_supply
3,000
24
8
0.260417
40.7
118
electric
68,200,156
electric
400,000
24
8
34.722222
1,011.95
119
water_supply
68,200,156
water_supply
3,000
24
8
0.260417
1,011.95
121
electric
68,200,155
electric
400,000
24
8
34.722222
1,011.95
122
water_supply
68,200,155
water_supply
3,000
24
8
0.260417
1,011.95
124
electric
68,200,154
electric
400,000
24
8
34.722222
98.05
125
water_supply
68,200,154
water_supply
3,000
24
8
0.260417
98.05
127
electric
68,200,140
electric
400,000
24
8
34.722222
3.7
128
water_supply
68,200,140
water_supply
3,000
24
8
0.260417
3.7
130
electric
68,200,139
electric
400,000
24
8
34.722222
38.85
131
water_supply
68,200,139
water_supply
3,000
24
8
0.260417
38.85
133
electric
68,200,138
electric
400,000
24
8
34.722222
9.25
134
water_supply
68,200,138
water_supply
3,000
24
8
0.260417
9.25
136
electric
68,200,137
electric
400,000
24
8
34.722222
44.4
137
water_supply
68,200,137
water_supply
3,000
24
8
0.260417
44.4
139
electric
68,200,136
electric
400,000
24
8
34.722222
35.15
140
water_supply
68,200,136
water_supply
3,000
24
8
0.260417
35.15
143
electric
68,200,135
electric
400,000
24
8
34.722222
49.95
144
electric
68,200,135
electric
400,000
24
8
34.722222
96.2
145
water_supply
68,200,135
water_supply
3,000
24
8
0.260417
49.95
146
water_supply
68,200,135
water_supply
3,000
24
8
0.260417
96.2
148
electric
68,200,134
electric
400,000
24
8
34.722222
96.2
149
water_supply
68,200,134
water_supply
3,000
24
8
0.260417
96.2
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