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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 3 new columns ({'score_S', 'score_I', 'score_R'}) and 40 missing columns ({'q33', 'q31', 'q36', 'score_N', 'q13', 'q14', 'q49', 'q41', 'q47', 'q44', 'q20', 'q37', 'q34', 'q23', 'q32', 'q18', 'q38', 'q30', 'score_O', 'q48', 'q42', 'q35', 'q40', 'q46', 'q28', 'q19', 'q43', 'q29', 'q50', 'q21', 'q16', 'q25', 'q26', 'q15', 'q45', 'q24', 'q39', 'q27', 'q22', 'q17'}).

This happened while the csv dataset builder was generating data using

hf://datasets/PeterKol/jobcannon-psychometric-responses/career_match.csv (at revision 78f9d88559fbd98a51c729bf07c74fd2e5af73c9), ['hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/big_five.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/career_match.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/dark_triad.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/disc.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/enneagram.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/eq.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/mbti.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/multiple_intelligences.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/riasec.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 1837, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              id: int64
              created_at: string
              locale: string
              duration_seconds: double
              top_result: string
              score_A: int64
              score_C: int64
              score_E: int64
              score_I: int64
              score_R: int64
              score_S: int64
              q1: string
              q2: string
              q3: string
              q4: string
              q5: string
              q6: string
              q7: string
              q8: string
              q9: string
              q10: string
              q11: string
              q12: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2768
              to
              {'id': Value('int64'), 'created_at': Value('string'), 'locale': Value('string'), 'duration_seconds': Value('float64'), 'top_result': Value('string'), 'score_A': Value('int64'), 'score_C': Value('int64'), 'score_E': Value('int64'), 'score_N': Value('int64'), 'score_O': Value('int64'), 'q1': Value('int64'), 'q2': Value('int64'), 'q3': Value('int64'), 'q4': Value('int64'), 'q5': Value('int64'), 'q6': Value('int64'), 'q7': Value('int64'), 'q8': Value('int64'), 'q9': Value('int64'), 'q10': Value('int64'), 'q11': Value('int64'), 'q12': Value('int64'), 'q13': Value('int64'), 'q14': Value('int64'), 'q15': Value('int64'), 'q16': Value('int64'), 'q17': Value('int64'), 'q18': Value('int64'), 'q19': Value('int64'), 'q20': Value('int64'), 'q21': Value('int64'), 'q22': Value('int64'), 'q23': Value('int64'), 'q24': Value('int64'), 'q25': Value('int64'), 'q26': Value('int64'), 'q27': Value('int64'), 'q28': Value('int64'), 'q29': Value('int64'), 'q30': Value('int64'), 'q31': Value('int64'), 'q32': Value('int64'), 'q33': Value('int64'), 'q34': Value('int64'), 'q35': Value('int64'), 'q36': Value('int64'), 'q37': Value('int64'), 'q38': Value('int64'), 'q39': Value('int64'), 'q40': Value('int64'), 'q41': Value('int64'), 'q42': Value('int64'), 'q43': Value('int64'), 'q44': Value('int64'), 'q45': Value('int64'), 'q46': Value('int64'), 'q47': Value('int64'), 'q48': Value('int64'), 'q49': Value('int64'), 'q50': Value('int64')}
              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 1361, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 940, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1683, 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 1839, 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 3 new columns ({'score_S', 'score_I', 'score_R'}) and 40 missing columns ({'q33', 'q31', 'q36', 'score_N', 'q13', 'q14', 'q49', 'q41', 'q47', 'q44', 'q20', 'q37', 'q34', 'q23', 'q32', 'q18', 'q38', 'q30', 'score_O', 'q48', 'q42', 'q35', 'q40', 'q46', 'q28', 'q19', 'q43', 'q29', 'q50', 'q21', 'q16', 'q25', 'q26', 'q15', 'q45', 'q24', 'q39', 'q27', 'q22', 'q17'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/PeterKol/jobcannon-psychometric-responses/career_match.csv (at revision 78f9d88559fbd98a51c729bf07c74fd2e5af73c9), ['hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/big_five.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/career_match.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/dark_triad.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/disc.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/enneagram.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/eq.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/mbti.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/multiple_intelligences.csv', 'hf://datasets/PeterKol/jobcannon-psychometric-responses@78f9d88559fbd98a51c729bf07c74fd2e5af73c9/riasec.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)

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id
int64
created_at
string
locale
null
duration_seconds
float64
top_result
string
score_A
int64
score_C
int64
score_E
int64
score_N
int64
score_O
int64
q1
int64
q2
int64
q3
int64
q4
int64
q5
int64
q6
int64
q7
int64
q8
int64
q9
int64
q10
int64
q11
int64
q12
int64
q13
int64
q14
int64
q15
int64
q16
int64
q17
int64
q18
int64
q19
int64
q20
int64
q21
int64
q22
int64
q23
int64
q24
int64
q25
int64
q26
int64
q27
int64
q28
int64
q29
int64
q30
int64
q31
int64
q32
int64
q33
int64
q34
int64
q35
int64
q36
int64
q37
int64
q38
int64
q39
int64
q40
int64
q41
int64
q42
int64
q43
int64
q44
int64
q45
int64
q46
int64
q47
int64
q48
int64
q49
int64
q50
int64
1
2026-03-10T15:48:45.624832+00:00
null
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2026-03-19T11:41:17.06+00:00
null
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2026-04-06T12:13:07.167535+00:00
null
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C
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60
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53
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2026-04-06T20:34:10.098+00:00
null
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O
57
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70
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2026-04-08T06:19:55.599+00:00
null
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2026-04-08T06:26:23.955+00:00
null
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35
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2026-04-08T07:45:49.299959+00:00
null
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2026-04-08T21:19:35.216+00:00
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9
2026-04-09T07:27:36.107+00:00
null
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O
53
38
10
80
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2
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2
2
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1
10
2026-04-09T19:04:50.72224+00:00
null
null
O
63
38
73
68
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2026-04-10T16:13:39.104+00:00
null
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38
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2026-04-10T21:41:48.198913+00:00
null
null
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13
2026-04-11T00:30:11.119486+00:00
null
null
O
75
60
48
40
78
4
3
3
3
3
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1
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3
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2
1
1
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1
1
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2
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2
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14
2026-04-11T04:48:06.206789+00:00
null
null
O
57
50
13
45
85
3
3
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0
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1
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1
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15
2026-04-11T05:22:56.271+00:00
null
null
C
70
85
78
33
38
1
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1
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2026-04-11T07:45:46.182518+00:00
null
null
O
55
48
45
18
83
3
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3
3
3
4
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0
17
2026-04-11T18:32:48.208429+00:00
null
null
A
83
35
33
73
60
2
3
1
0
4
1
2
1
3
3
4
3
3
4
4
0
4
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1
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1
1
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3
3
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1
3
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1
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3
4
4
4
3
2
1
2
0
0
18
2026-04-11T20:43:03.943172+00:00
null
null
O
63
65
53
38
73
4
3
1
2
3
0
1
0
2
3
1
2
1
2
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3
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4
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3
2
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2
1
2
3
2
3
3
3
2
1
3
2
1
19
2026-04-11T21:20:22.614166+00:00
null
null
C
65
73
50
45
55
3
2
2
2
3
0
3
1
2
4
1
1
2
2
2
1
2
3
2
2
2
2
2
1
2
3
2
1
2
1
4
4
3
2
3
2
2
1
1
1
2
2
3
3
3
2
0
3
1
1
20
2026-04-11T21:52:57.797+00:00
null
null
N
48
45
48
73
60
2
2
2
2
3
0
2
1
3
3
2
3
2
4
4
0
1
2
1
2
2
2
2
2
3
1
3
2
4
2
2
3
2
2
2
4
4
2
1
2
3
3
3
3
3
4
2
2
4
4
21
2026-04-11T23:28:06.940692+00:00
null
null
C
88
98
50
13
73
1
4
1
4
4
2
0
3
4
2
0
0
0
0
0
3
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2
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1
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0
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0
4
4
4
3
3
1
0
2
0
0
22
2026-04-12T00:30:12.418+00:00
null
null
A
93
65
60
28
90
3
3
1
4
4
0
0
1
4
0
2
2
1
1
0
4
2
3
4
2
4
4
4
1
1
2
1
1
3
3
3
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1
3
3
2
2
1
1
1
3
3
4
4
4
1
0
0
0
0
23
2026-04-12T10:58:31.454869+00:00
null
null
O
73
53
75
63
93
4
4
0
4
3
0
0
0
4
2
3
0
2
3
4
0
0
4
1
2
3
2
4
2
3
0
0
2
2
0
1
1
1
3
2
3
3
0
1
0
1
1
3
2
4
1
0
1
0
0
24
2026-04-12T12:01:07.543+00:00
null
null
A
85
55
78
48
78
4
3
0
3
4
4
1
2
4
0
2
2
2
2
1
2
2
2
2
2
4
4
3
3
2
1
2
0
0
2
2
2
2
2
3
3
0
0
4
2
3
3
4
4
4
0
0
2
2
0
25
2026-04-12T15:52:53.723939+00:00
null
null
C
78
95
65
20
80
4
3
1
3
4
0
3
0
4
2
0
0
0
0
0
1
0
4
3
4
4
3
3
0
2
1
1
0
3
1
4
4
4
4
3
0
1
0
0
0
4
3
4
3
3
2
0
1
3
0
26
2026-04-12T16:53:42.893264+00:00
null
null
A
75
57
45
50
70
4
3
1
1
3
0
1
1
4
4
2
2
2
3
1
1
2
3
2
2
3
3
2
1
2
3
3
1
3
3
3
3
3
3
3
3
3
2
2
2
3
3
3
3
3
1
1
2
1
0
27
2026-04-12T19:09:02.073156+00:00
null
null
O
65
65
48
48
70
3
2
2
1
3
0
1
0
4
2
3
0
1
2
3
1
1
3
2
3
3
3
3
2
2
3
3
2
3
3
3
3
3
3
3
0
2
3
2
2
4
2
3
3
3
2
2
3
2
0
28
2026-04-12T20:48:20.283132+00:00
null
null
C
75
90
75
35
88
4
4
0
3
4
0
0
0
4
4
2
0
0
2
1
0
2
4
1
4
4
4
4
4
4
2
2
0
4
2
4
4
2
4
4
0
0
0
2
0
4
0
4
4
4
4
0
2
0
0
29
2026-04-12T21:21:01.737+00:00
null
null
A
73
55
10
38
63
3
3
1
0
3
1
2
1
3
2
1
2
1
1
0
2
1
2
3
2
1
0
0
0
0
4
4
1
4
4
3
2
2
2
2
2
2
3
1
1
3
2
3
4
3
1
1
3
1
0
30
2026-04-13T00:15:11.687+00:00
null
null
A
65
60
28
65
63
3
3
2
1
2
0
2
0
3
3
3
3
2
2
3
2
2
1
1
1
2
0
0
0
2
2
3
2
3
3
2
3
3
3
3
3
2
2
2
1
3
3
3
2
3
1
1
3
2
1
31
2026-04-13T00:46:28.771+00:00
null
null
O
75
45
25
73
83
4
4
2
2
3
0
0
0
4
2
3
4
3
3
3
2
1
1
3
0
2
1
1
0
0
3
3
3
3
2
0
4
2
1
2
3
2
1
2
3
2
3
3
3
2
1
1
0
1
0
32
2026-04-13T02:40:32.193235+00:00
null
null
C
68
88
68
38
85
3
3
1
3
4
0
1
0
4
1
1
1
1
1
2
1
1
3
3
3
4
3
3
2
3
2
1
1
2
2
3
3
4
4
4
0
2
1
0
0
3
3
4
3
4
3
2
2
2
1
33
2026-04-13T03:53:41.342+00:00
null
null
A
70
68
45
43
55
2
2
2
2
3
2
2
1
3
3
1
1
0
2
3
1
2
3
1
3
2
2
2
1
2
2
3
1
2
3
3
3
3
3
3
1
2
1
2
2
2
2
3
3
3
2
0
3
0
0
34
2026-04-13T03:55:20.193+00:00
null
null
C
48
55
38
45
48
1
2
2
2
2
2
1
3
2
2
2
2
2
1
1
2
2
2
2
2
1
2
2
2
2
3
3
2
3
3
2
3
2
2
2
2
2
2
1
2
2
1
2
2
3
2
2
3
3
1
35
2026-04-13T03:58:15.341+00:00
null
null
O
73
35
90
60
90
4
4
0
3
4
0
1
0
4
2
3
1
2
4
4
1
1
4
0
4
4
4
3
4
4
0
0
1
2
0
0
4
0
2
2
3
4
4
1
2
4
4
4
4
4
3
0
4
2
2
36
2026-04-13T05:31:20.323+00:00
null
null
O
45
75
85
15
90
4
4
0
3
4
0
0
0
3
2
0
0
0
0
0
1
3
3
3
4
3
4
4
3
3
0
1
0
1
1
1
3
4
4
3
0
1
1
1
2
1
2
3
3
3
4
4
4
1
1
37
2026-04-13T05:47:17.079+00:00
null
null
E
78
57
85
57
78
4
1
3
2
4
0
0
0
4
1
3
2
2
3
2
2
0
3
2
2
4
4
4
3
2
0
0
0
3
0
1
3
1
3
0
2
1
2
0
0
4
2
4
4
4
4
0
1
2
0
38
2026-04-13T05:53:56.07+00:00
null
null
O
63
63
28
70
75
4
4
4
3
4
0
2
0
3
2
3
4
3
3
1
1
3
1
1
0
1
2
2
0
1
3
4
3
2
3
3
4
3
2
2
2
3
3
0
1
1
1
3
3
3
2
0
4
0
0
39
2026-04-13T06:11:02.67+00:00
null
null
C
68
95
53
68
65
4
3
2
3
3
1
2
2
3
3
3
3
3
3
1
1
1
2
1
1
3
3
1
0
3
1
3
1
3
1
4
4
4
4
4
1
1
0
0
0
1
1
3
1
3
1
0
1
0
0
40
2026-04-13T06:51:42.401+00:00
null
null
O
68
65
38
57
88
4
4
3
4
4
0
0
0
4
2
3
1
2
2
3
2
2
2
1
1
1
2
3
1
3
1
4
2
4
4
2
3
4
4
3
2
2
2
2
2
3
4
4
4
4
4
2
3
2
1
41
2026-04-13T07:47:29.815657+00:00
null
null
O
83
55
73
33
83
3
3
1
4
4
1
0
1
3
1
1
1
1
2
3
4
3
3
2
3
3
4
3
2
3
2
0
1
2
1
1
2
1
3
3
3
2
1
0
2
4
4
3
3
3
1
0
2
1
0
42
2026-04-13T08:54:09.645+00:00
null
null
C
60
75
57
30
68
3
4
1
2
4
2
3
3
4
1
1
0
0
2
1
2
0
4
3
3
4
2
4
3
4
2
2
4
4
2
2
3
4
3
3
1
1
1
1
1
2
4
3
4
2
4
2
4
0
1
43
2026-04-13T11:01:13.19781+00:00
null
null
C
48
65
53
50
40
3
1
3
3
2
3
1
3
0
3
2
4
1
2
3
3
0
3
3
3
4
1
3
2
1
3
2
4
0
1
3
3
3
2
4
1
1
2
2
3
3
4
1
2
3
4
4
2
2
2
44
2026-04-13T11:11:42.642576+00:00
null
20
A
65
63
43
60
43
1
1
1
1
1
1
1
1
1
2
1
1
1
2
1
1
3
1
0
3
2
2
3
2
2
2
2
2
3
3
2
3
1
1
1
4
4
1
2
1
1
4
4
4
3
2
3
4
2
4
45
2026-04-13T11:49:05.479+00:00
null
null
O
73
40
15
73
75
4
4
2
2
3
0
1
0
3
3
4
4
4
4
4
3
3
3
1
1
1
0
0
0
0
3
3
3
3
3
2
2
2
2
3
3
3
3
3
3
3
3
3
3
2
1
0
2
1
1
46
2026-04-13T13:02:41.848+00:00
null
null
C
73
78
50
50
57
2
3
1
2
3
2
2
3
3
2
2
2
2
1
3
2
2
3
1
2
2
2
2
1
3
2
2
1
3
2
3
4
2
3
3
2
1
0
1
0
3
2
3
3
3
0
0
3
1
1
47
2026-04-13T15:49:00.842+00:00
null
null
O
68
73
30
38
93
4
4
0
3
4
0
0
0
4
2
3
2
1
3
1
1
3
4
3
4
1
1
0
0
1
1
3
0
4
3
3
3
3
4
4
2
1
3
1
1
3
1
3
3
3
2
1
3
0
0
48
2026-04-13T17:05:19.583966+00:00
null
null
O
68
60
70
30
80
4
3
1
3
4
0
1
1
3
2
1
0
0
1
1
1
3
3
2
2
3
3
3
3
2
1
1
1
2
1
2
4
3
2
1
2
3
1
1
1
3
3
3
3
3
3
1
2
1
1
49
2026-04-13T21:14:43.630222+00:00
null
null
O
83
78
70
25
88
4
3
1
3
4
0
1
0
4
1
1
0
0
2
2
2
3
4
2
4
3
3
4
2
3
1
2
0
3
1
3
4
2
3
2
1
1
0
1
0
3
2
4
3
4
2
0
1
0
0
50
2026-04-13T22:52:03.12+00:00
null
null
A
70
53
5
68
40
3
1
3
0
2
2
3
3
4
3
3
4
3
2
2
3
1
0
2
1
0
0
0
0
0
4
4
3
4
3
3
2
2
2
2
2
2
2
2
2
3
3
3
3
3
2
1
2
1
1
51
2026-04-13T22:53:31.817936+00:00
null
null
N
68
53
13
73
48
2
1
1
0
2
2
1
2
3
3
3
4
3
2
2
2
1
0
2
0
0
0
0
0
0
3
3
3
3
3
2
2
2
2
2
2
2
2
2
1
2
3
3
3
2
1
1
2
1
1
52
2026-04-13T23:29:22.255777+00:00
null
null
E
83
63
95
13
60
2
2
1
3
3
2
1
4
3
1
0
0
0
1
0
2
3
4
3
4
4
4
4
4
3
0
0
0
0
1
3
2
2
3
3
1
2
1
2
2
3
3
3
4
4
2
0
0
0
2
53
2026-04-14T07:24:06.058+00:00
null
null
N
75
63
20
80
48
3
1
3
2
3
3
2
2
3
3
4
4
3
3
3
3
0
0
1
1
3
1
1
0
0
3
3
3
4
4
2
4
4
3
3
4
3
2
2
0
4
4
3
3
3
3
1
1
1
1
54
2026-04-14T12:33:13.058085+00:00
null
null
A
70
45
50
5
63
3
3
1
1
3
1
2
3
3
1
0
0
0
0
0
4
4
3
4
3
2
2
3
2
1
3
1
0
3
3
1
2
1
2
1
2
1
1
3
2
2
3
3
3
3
1
0
3
0
2
55
2026-04-14T15:11:31.946734+00:00
null
null
A
93
75
68
48
78
4
2
1
3
4
0
2
0
4
3
3
1
2
1
1
1
3
2
1
2
3
3
3
2
1
1
0
0
3
1
4
4
3
3
3
3
3
1
0
0
3
3
4
3
4
0
0
0
0
0
56
2026-04-14T15:18:32.750432+00:00
null
null
O
68
60
85
40
85
4
3
0
4
4
0
0
3
4
2
1
0
0
3
1
1
1
3
1
3
3
3
4
3
2
1
0
0
0
0
3
3
0
3
4
4
3
0
1
1
3
1
3
3
3
2
0
4
0
0
57
2026-04-14T18:17:44.396+00:00
null
null
A
85
80
63
33
83
3
2
1
2
3
0
0
0
4
0
0
0
0
2
1
2
2
2
2
2
2
3
2
1
2
1
1
1
1
1
3
4
3
3
3
0
1
2
0
1
4
2
3
4
3
1
0
1
0
0
58
2026-04-14T19:09:01.408+00:00
null
null
C
65
100
83
3
78
4
4
0
3
3
0
1
2
3
3
0
0
0
0
0
4
4
4
3
4
3
3
3
2
3
0
0
0
1
0
4
4
4
4
4
0
0
0
0
0
2
3
3
3
3
1
1
3
1
2
59
2026-04-15T15:25:16.895391+00:00
null
null
O
78
33
48
63
80
4
4
0
3
3
0
0
2
2
2
2
2
4
2
1
1
1
1
1
2
1
3
2
0
2
0
3
3
2
1
3
4
0
0
0
4
4
3
1
2
3
1
4
3
4
1
1
2
0
0
60
2026-04-15T18:01:42.008411+00:00
null
null
O
57
38
33
45
75
3
3
2
3
4
0
1
0
3
3
1
2
1
0
3
2
2
2
2
1
1
1
1
0
2
2
3
3
3
1
2
3
1
1
2
3
3
3
3
2
2
1
3
3
3
2
1
3
2
1
61
2026-04-15T23:01:31.319+00:00
null
null
A
98
83
88
10
93
4
4
0
4
4
0
0
1
4
2
0
0
1
1
0
3
3
4
4
4
4
4
4
4
4
1
2
0
1
1
4
4
4
4
3
1
1
1
2
1
4
4
4
4
4
0
0
1
0
0
62
2026-04-16T03:47:18.139258+00:00
null
null
O
83
65
90
57
93
4
4
2
3
4
0
0
0
4
0
3
3
3
4
3
3
0
3
3
4
4
4
4
4
4
0
0
0
4
0
4
4
2
3
2
3
3
3
0
0
4
4
4
4
4
4
0
3
0
0
63
2026-04-16T05:37:26.838+00:00
null
null
E
73
83
98
35
70
2
3
0
2
4
2
2
2
3
0
2
0
1
2
0
2
2
2
3
2
4
4
4
3
4
0
0
0
0
0
3
2
2
4
4
1
0
0
1
0
2
1
4
4
4
2
0
2
2
0
64
2026-04-16T13:02:32.576+00:00
null
null
O
63
50
73
55
80
4
4
2
4
4
0
1
2
2
1
2
0
1
3
2
1
2
1
1
1
3
4
4
0
3
2
2
1
0
0
1
4
1
1
2
3
2
3
0
1
3
3
3
3
4
3
2
4
1
1
65
2026-04-16T16:18:47.727698+00:00
null
193
O
80
63
88
53
90
4
4
0
4
4
0
0
1
4
3
3
4
4
2
4
4
3
3
4
2
3
4
3
4
4
2
0
0
1
0
3
3
0
3
3
3
2
1
0
1
4
2
4
4
4
2
0
4
0
0
66
2026-04-16T18:02:59.552+00:00
null
null
O
75
83
48
18
83
4
4
1
4
4
0
2
0
1
1
0
0
0
0
2
1
4
4
4
2
0
0
1
0
0
0
1
0
1
0
0
2
4
4
4
1
0
0
0
0
3
2
3
4
3
3
0
1
1
0
67
2026-04-16T23:26:06.283+00:00
null
null
O
90
40
90
18
95
4
3
0
4
4
1
0
0
4
0
1
0
1
0
0
1
4
4
3
3
4
4
4
3
3
0
0
0
1
1
0
0
1
0
1
3
1
1
1
0
3
3
4
4
4
1
0
1
0
0
68
2026-04-17T00:15:34.736004+00:00
null
194
A
85
57
38
60
78
3
3
1
3
3
0
0
1
3
2
2
2
2
3
2
2
2
1
1
1
1
1
2
1
0
1
3
2
3
1
2
4
3
3
2
3
2
2
2
2
3
3
4
3
3
1
0
1
0
0
69
2026-04-17T01:24:56.291+00:00
null
null
A
78
45
5
60
53
4
4
2
0
2
0
4
4
3
2
3
2
2
1
4
1
2
3
0
2
0
0
0
0
0
4
4
2
4
4
3
3
1
2
1
4
4
0
2
2
1
2
4
4
4
0
1
1
0
2
70
2026-04-17T03:22:28.264+00:00
null
null
O
70
8
85
70
85
4
4
2
4
4
0
1
0
3
2
4
2
4
4
4
3
0
3
2
2
3
3
1
4
4
0
1
0
0
0
0
1
0
0
0
4
4
3
4
3
4
3
3
4
4
4
3
2
1
0
71
2026-04-17T08:31:57.932+00:00
null
null
O
43
68
68
65
75
3
2
1
3
3
1
0
1
3
1
3
2
3
3
2
1
1
2
2
1
3
3
3
2
2
1
1
1
1
2
3
3
3
3
3
2
2
1
2
1
1
2
3
2
3
3
2
3
3
3
72
2026-04-17T13:02:16.756+00:00
null
null
O
83
38
85
40
93
4
4
0
4
4
0
1
0
4
2
2
1
0
3
1
3
1
3
1
3
3
4
4
4
3
0
1
0
2
1
1
3
0
2
2
3
4
3
0
3
3
4
4
4
3
2
0
3
0
0
73
2026-04-17T20:11:53.76298+00:00
null
227
O
73
30
45
45
100
4
4
0
4
4
0
0
0
4
0
3
2
3
2
0
1
3
4
3
1
3
3
3
1
1
2
3
1
4
3
1
4
3
1
1
4
4
4
3
3
3
3
3
4
4
3
0
0
3
2
74
2026-04-17T21:20:29.900946+00:00
null
565
A
68
40
3
63
38
0
0
3
0
3
3
0
2
3
3
3
4
4
4
0
1
1
4
4
0
1
0
0
0
0
4
4
4
4
4
3
1
1
0
1
0
4
3
3
0
3
2
3
4
0
1
0
4
0
0
75
2026-04-18T11:03:53.088+00:00
null
null
O
57
57
50
25
78
3
4
2
4
4
2
2
0
3
1
1
0
0
2
1
1
2
4
3
4
3
2
2
0
3
3
3
2
1
1
3
3
1
4
2
4
3
2
0
1
4
2
3
3
4
4
2
3
3
1
76
2026-04-18T15:04:15.758155+00:00
null
270
E
70
80
88
18
60
0
2
1
1
0
0
1
0
4
1
2
0
0
0
0
2
1
4
4
4
2
4
4
4
4
0
1
0
2
0
3
4
4
4
4
0
3
3
1
0
3
4
4
4
4
4
0
3
4
0
77
2026-04-19T02:54:56.455+00:00
null
null
C
35
85
35
33
63
1
3
1
4
4
4
0
3
2
1
2
0
2
2
2
1
2
4
4
4
2
2
3
0
2
1
4
2
4
4
4
4
1
4
3
1
1
0
0
0
2
0
2
1
2
3
3
4
2
1
78
2026-04-19T17:03:43.57+00:00
null
null
O
73
35
30
63
75
4
3
1
1
2
0
0
1
3
1
3
4
2
2
2
3
2
0
3
0
1
2
0
2
1
4
3
1
3
3
3
1
0
1
1
4
3
1
2
2
3
2
3
3
3
0
0
2
1
2
79
2026-04-19T21:26:17.96+00:00
null
null
N
38
53
40
55
40
3
1
2
1
0
1
3
4
3
2
3
3
1
2
4
3
1
1
3
3
1
1
1
2
1
2
3
1
3
1
1
3
3
1
0
1
3
0
3
0
2
4
1
0
3
4
3
3
4
1
80
2026-04-19T22:17:18.037+00:00
null
null
E
45
57
63
60
55
3
1
0
3
4
3
2
1
0
3
4
2
3
1
3
4
3
1
0
1
3
3
0
4
3
1
1
3
3
0
3
4
3
1
0
1
2
4
1
0
1
3
4
1
0
4
4
1
0
2
81
2026-04-20T18:30:35.06284+00:00
null
152
C
65
70
65
23
63
1
3
2
3
4
1
2
1
3
3
2
0
1
1
1
2
3
4
3
4
3
3
3
2
2
2
1
1
2
1
2
3
2
3
3
0
0
2
2
1
3
3
4
4
4
3
2
2
3
2
82
2026-04-21T00:03:45.517908+00:00
null
154
O
60
25
50
75
80
3
4
1
3
4
0
0
2
3
2
3
2
3
3
3
0
1
1
1
1
0
3
3
1
3
1
3
0
3
3
1
1
0
1
1
3
3
3
3
2
3
2
4
3
3
3
2
2
3
1
83
2026-04-21T16:52:23.988867+00:00
null
174
C
78
78
73
33
57
0
3
1
3
3
4
0
2
3
2
1
1
0
0
2
1
3
3
1
3
3
3
3
1
3
1
1
0
1
1
3
4
2
3
3
1
2
1
0
0
4
3
3
3
3
2
0
1
0
2
84
2026-04-21T20:13:43.650936+00:00
null
168
O
50
43
55
63
80
4
3
3
2
3
0
1
0
4
0
3
2
1
4
3
1
2
3
0
2
2
3
3
2
2
3
2
2
2
1
2
2
0
2
3
3
3
1
3
2
1
3
3
3
3
3
3
1
3
3
85
2026-04-22T09:13:00.537074+00:00
null
342
A
80
53
43
25
43
0
2
3
2
3
3
3
3
3
1
1
1
1
1
1
3
3
3
3
3
2
2
2
1
1
2
3
1
2
3
3
2
3
3
2
2
3
3
3
1
3
3
4
3
3
1
0
1
1
1
86
2026-04-22T11:40:12.451558+00:00
null
334
A
88
80
38
20
73
3
3
1
2
4
0
4
0
4
2
1
0
0
0
0
4
3
3
1
2
3
2
2
2
1
2
4
4
3
2
3
3
3
3
4
2
0
0
2
0
3
4
4
4
2
0
0
2
0
0
87
2026-04-22T13:24:00.754+00:00
null
null
C
85
95
45
28
78
2
2
1
3
4
1
0
0
4
2
0
0
0
0
2
0
4
3
1
3
1
3
2
0
2
1
1
0
4
4
3
4
4
4
3
0
0
0
0
0
4
4
4
4
4
0
0
4
2
0
88
2026-04-22T13:41:18.147+00:00
null
null
E
65
60
70
33
57
2
3
3
4
3
3
1
4
3
1
2
0
3
1
1
3
2
4
1
4
3
3
4
2
3
1
1
1
3
1
3
3
3
3
3
3
3
4
0
1
4
4
4
3
4
4
3
3
1
2
89
2026-04-22T15:13:43.302546+00:00
null
134
O
78
55
48
45
80
4
3
3
3
3
1
0
0
4
1
3
3
1
3
3
3
1
4
3
4
1
3
3
2
2
2
3
3
3
1
3
4
1
3
1
1
1
3
2
3
4
4
4
4
4
3
0
1
4
1
90
2026-04-22T15:48:52.588588+00:00
null
165
A
78
75
57
8
60
2
3
1
2
3
2
2
1
1
1
0
0
0
0
0
4
4
3
3
3
3
3
3
2
2
2
2
2
2
2
3
3
3
3
3
1
1
1
1
1
1
3
4
4
3
2
1
1
0
0
91
2026-04-22T18:42:20.047+00:00
null
null
O
70
55
15
40
80
3
2
1
3
3
0
0
0
3
1
3
1
1
2
3
3
1
4
3
3
1
1
0
0
1
3
4
2
4
4
3
3
3
2
2
3
3
2
1
2
4
2
3
3
3
1
0
3
2
1
92
2026-04-22T18:47:16.832521+00:00
null
294
O
75
57
40
80
90
4
4
0
4
4
0
0
0
3
3
4
3
3
2
2
0
1
0
0
1
0
3
3
1
3
2
3
3
4
2
2
3
1
3
3
3
3
1
1
1
3
2
4
3
3
2
0
3
0
0
93
2026-04-22T19:42:19.682887+00:00
null
266
A
93
85
85
0
88
4
4
0
4
4
0
2
1
4
2
0
0
0
0
0
4
4
4
4
4
4
4
4
2
3
1
1
0
1
0
3
4
3
4
4
0
4
0
0
0
3
2
4
4
4
0
0
0
0
0
94
2026-04-22T23:43:20.418198+00:00
null
247
C
73
75
63
53
68
2
3
3
3
4
2
1
1
3
1
2
1
3
3
3
1
1
3
3
3
3
4
3
3
3
1
3
3
3
1
3
4
3
3
4
3
1
1
1
1
3
3
3
4
4
3
0
1
3
1
95
2026-04-23T01:13:08.134157+00:00
null
160
O
55
23
68
38
70
2
4
1
4
2
2
0
2
1
0
2
1
1
3
0
3
1
3
3
2
3
3
3
0
4
1
2
1
1
1
0
0
0
0
0
2
3
3
1
2
2
1
2
2
3
3
2
2
1
0
96
2026-04-23T02:06:07.367695+00:00
null
235
O
78
65
57
88
90
4
3
1
3
4
0
0
0
4
1
4
4
4
3
2
1
0
1
0
0
1
2
3
2
4
1
2
2
3
1
3
4
2
3
3
3
3
1
1
1
2
3
3
3
3
1
0
2
0
0
97
2026-04-23T09:32:34.247364+00:00
null
227
N
50
35
53
75
70
4
3
1
3
3
1
3
1
3
2
4
3
3
2
4
2
0
1
1
2
3
3
3
0
1
1
2
3
1
2
1
3
1
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
98
2026-04-23T17:02:50.395435+00:00
null
260
O
75
83
75
3
88
3
3
0
3
4
1
0
0
4
1
0
0
0
0
0
4
3
4
4
4
4
3
3
1
4
0
1
1
2
1
3
3
3
3
3
2
0
0
0
0
3
3
4
4
4
2
1
2
3
0
99
2026-04-24T00:43:30.846285+00:00
null
277
E
75
70
78
18
75
3
4
2
3
3
1
0
2
4
2
2
0
0
0
0
2
3
4
3
3
4
4
3
3
3
1
1
1
2
1
3
4
2
3
3
2
2
1
1
1
3
2
3
3
3
2
0
2
0
0
100
2026-04-24T02:21:43.411+00:00
null
null
C
78
90
88
48
68
3
1
0
3
4
1
1
4
3
1
0
0
0
0
0
0
0
1
0
0
4
4
4
3
4
0
0
1
3
0
4
3
1
4
4
0
0
0
0
0
3
4
4
4
4
3
0
3
2
0
End of preview.

JobCannon Psychometric Response Dataset

Anonymized, item-level responses to nine open-domain psychometric instruments, collected from real test-takers on JobCannon. Each row is one completed assessment: the raw per-item answers, the computed dimensional scores, and the dominant result type.

This is a first-party dataset — these are our own users' responses, not a re-publication of someone else's data. Released for research, education, and benchmarking in the spirit of the OpenPsychometrics archive.

Mirrors & DOI

The same dataset is published openly across several platforms:

What's inside

File Instrument N Items Score dimensions
career_match.csv Mini-RIASEC (forced-choice career interest) 2,005 12 6 (R I A S E C)
riasec.csv RIASEC / Holland Codes (full) 1,455 60 6 + percentile
mbti.csv 16-type indicator (E/I, S/N, T/F, J/P + A/T) 1,762 60 7
big_five.csv Big Five / OCEAN 880 50 5
disc.csv DISC behavioral style 888 12 4 (D I S C)
enneagram.csv Enneagram (9 types) 487 36 9
multiple_intelligences.csv Gardner's Multiple Intelligences 498 40 8
eq.csv Emotional intelligence (short) 264 10 4
dark_triad.csv Dark Triad (SD3-style) 155 18 3

_NORMS.md contains the per-test result distributions and dimensional means.

Column schema

Every CSV shares the same leading columns, then per-instrument score and item columns:

Column Meaning
id Anonymous sequential index within the file. Not a database identifier.
created_at UTC timestamp of completion
locale UI language at time of taking (may be blank)
duration_seconds Time to complete (may be blank)
top_result Dominant result type for this instrument
score_<dim> Computed score per dimension
q1 … qN Raw per-item answer values (instrument-specific scale)

Only canonical-length submissions are included: each instrument was filtered to its current item count, dropping incomplete and legacy-version rows so every q1…qN block is consistent within a file.

Privacy

No personal data is present. The build pipeline never selects user id, anonymous id, name, email, IP/host, referrer, or UTM parameters. The only identifier is an anonymous sequential id generated at export time; the underlying database row identifiers are not emitted.

Instruments & licensing

All instruments are open-domain or public-domain measures (RIASEC/Holland, IPIP Big Five, DISC, Enneagram, MMI, Dark Triad SD3 family). They are screening and self-discovery tools, not clinical diagnostics.

Citation

@dataset{jobcannon_psychometric_2026,
  title  = {JobCannon Psychometric Response Dataset},
  author = {JobCannon},
  year   = {2026},
  url    = {https://jobcannon.io}
}

License: CC-BY-4.0 — free to use with attribution.

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