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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 21 new columns ({'nr.employed', 'previous', 'cons.price.idx', 'age', 'day_of_week', 'duration', 'contact', 'campaign', 'emp.var.rate', 'y', 'education', 'pdays', 'marital', 'job', 'poutcome', 'cons.conf.idx', 'euribor3m', 'default', 'month', 'loan', 'housing'}) and 6 missing columns ({'industry', 'salary', 'salary_high', 'experience', 'salary_low', 'exams'}).

This happened while the csv dataset builder was generating data using

hf://datasets/supersam7/actuary_salaries/bank_loans.csv (at revision 007a5359af8ffc55b3b387ced445d091f71108de)

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
              age: int64
              job: string
              marital: string
              education: string
              default: string
              housing: string
              loan: string
              contact: string
              month: string
              day_of_week: string
              duration: int64
              campaign: int64
              pdays: int64
              previous: int64
              poutcome: string
              emp.var.rate: double
              cons.price.idx: double
              cons.conf.idx: double
              euribor3m: double
              nr.employed: double
              y: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2673
              to
              {'industry': Value(dtype='string', id=None), 'exams': Value(dtype='string', id=None), 'experience': Value(dtype='int64', id=None), 'salary': Value(dtype='string', id=None), 'salary_low': Value(dtype='int64', id=None), 'salary_high': 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 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 21 new columns ({'nr.employed', 'previous', 'cons.price.idx', 'age', 'day_of_week', 'duration', 'contact', 'campaign', 'emp.var.rate', 'y', 'education', 'pdays', 'marital', 'job', 'poutcome', 'cons.conf.idx', 'euribor3m', 'default', 'month', 'loan', 'housing'}) and 6 missing columns ({'industry', 'salary', 'salary_high', 'experience', 'salary_low', 'exams'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/supersam7/actuary_salaries/bank_loans.csv (at revision 007a5359af8ffc55b3b387ced445d091f71108de)
              
              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.

industry
string
exams
string
experience
int64
salary
string
salary_low
int64
salary_high
int64
Casualty
1 Exam
1
48 - 65
48
65
Casualty
2 Exams
1
50 - 71
50
71
Casualty
3 Exams
1
54 - 77
54
77
Casualty
4 Exams
1
58 - 82
58
82
Casualty
1 Exam
3
54 - 72
54
72
Casualty
2 Exams
3
57 - 81
57
81
Casualty
3 Exams
3
62 - 87
62
87
Casualty
4 Exams
3
63 - 91
63
91
Casualty
5 Exams
3
65 - 95
65
95
Casualty
6 Exams
3
70 - 97
70
97
Casualty
7 Exams
3
72 - 99
72
99
Casualty
ACAS
3
85 - 112
85
112
Casualty
1 Exam
5
55 - 80
55
80
Casualty
2 Exams
5
58 - 83
58
83
Casualty
3 Exams
5
66 - 100
66
100
Casualty
4 Exams
5
71 - 107
71
7
Casualty
5 Exams
5
73 - 111
73
11
Casualty
6 Exams
5
76 - 116
76
16
Casualty
7 Exams
5
85 - 118
85
18
Casualty
ACAS
5
90 - 138
90
38
Casualty
FCAS
5
114 - 166
11
66
Casualty
2 Exams
7
60 - 92
60
92
Casualty
3 Exams
7
79 - 106
79
6
Casualty
4 Exams
7
82 - 109
82
9
Casualty
5 Exams
7
84 - 118
84
18
Casualty
6 Exams
7
88 - 126
88
26
Casualty
7 Exams
7
94 - 135
94
35
Casualty
ACAS
7
98 - 154
98
54
Casualty
FCAS
7
116 - 190
116
190
Casualty
2 Exams
10
60 - 92
60
92
Casualty
3 Exams
10
79 - 106
79
106
Casualty
4 Exams
10
82 - 109
82
109
Casualty
5 Exams
10
84 - 118
84
118
Casualty
6 Exams
10
88 - 126
88
126
Casualty
7 Exams
10
94 - 135
94
135
Casualty
ACAS
10
98 - 154
98
154
Casualty
FCAS
10
116 - 190
116
190
Casualty
3 Exams
15
94 - 141
94
141
Casualty
4 Exams
15
100 - 159
100
159
Casualty
5 Exams
15
102 - 167
102
167
Casualty
6 Exams
15
107 - 172
107
172
Casualty
7 Exams
15
110 - 210
110
210
Casualty
ACAS
15
144 - 369
144
369
Casualty
ACAS
20
124 - 273
124
273
Casualty
FCAS
20
158 - 447
158
447
Health
1
1
49 - 60
49
60
Health
2
1
54 - 66
54
66
Health
3
1
56 - 72
56
72
Health
4
1
58 - 74
58
74
Health
1
3
54 - 69
54
69
Health
2
3
56 - 76
56
76
Health
3
3
57 - 83
57
83
Health
4
3
62 - 89
62
89
Health
5
3
68 - 93
68
93
Health
ASA
3
78 - 120
78
120
Health
1
5
57 - 76
57
76
Health
2
5
62 - 84
62
84
Health
3
5
63 - 90
63
90
Health
4
5
70 - 103
70
103
Health
5
5
72 - 110
72
110
Health
ASA
5
80 - 126
80
126
Health
FSA
5
106 - 165
106
165
Health
2
7
65 - 89
65
89
Health
3
7
67 - 96
67
96
Health
4
7
80 - 107
80
107
Health
5
7
82 - 121
82
121
Health
ASA
7
85 - 134
85
134
Health
FSA
7
112 - 174
112
174
Health
4
10
82 - 115
82
115
Health
5
10
84 - 126
84
126
Health
ASA
10
94 - 150
94
150
Health
FSA
10
121 - 210
121
210
Health
ASA
15
104 - 204
104
204
Health
FSA
15
140 - 273
140
273
Health
ASA
20
133 - 240
133
240
Health
FSA
20
155 - 390
155
390
Life
1
1
51 - 61
51
61
Life
2
1
52 - 64
52
64
Life
3
1
55 - 69
55
69
Life
4
1
57 - 76
57
76
Life
1
3
55 - 70
55
70
Life
2
3
56 - 78
56
78
Life
3
3
58 - 81
58
81
Life
4
3
64 - 92
64
92
Life
5
3
71 - 103
71
103
Life
ASA
3
75 - 117
75
117
Life
1
5
56 - 74
56
74
Life
2
5
60 - 85
60
85
Life
3
5
63 - 94
63
94
Life
4
5
68 - 100
68
100
Life
5
5
72 - 109
72
109
Life
ASA
5
76 - 125
76
125
Life
FSA
5
104 - 156
104
156
Life
2
7
63 - 92
63
92
Life
3
7
69 - 100
69
100
Life
4
7
74 - 104
74
104
Life
5
7
76 - 120
76
120
Life
ASA
7
84 - 147
84
147
Life
FSA
7
122 - 202
122
202
Life
4
10
76 - 117
76
117
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