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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 10 new columns ({'wides', 'conceded', 'overs', 'maidens', 'wickets', 'bowler id', 'noballs', 'dots', 'opposition', 'economy'}) and 7 missing columns ({'strikeRate', 'fielders', 'wicketType', 'isOut', 'batsman', 'runs', 'bowler'}).

This happened while the csv dataset builder was generating data using

hf://datasets/bhuvaneshprasad/odi-cricket-dataset-1971-2014/odi_Bowling_Card.csv (at revision dbe8f34ce6e781fd52c0ae8ddd5807a539646047)

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 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Match ID: int64
              innings: int64
              team: string
              opposition: string
              bowler id: double
              overs: double
              balls: double
              maidens: double
              conceded: double
              wickets: double
              economy: double
              dots: double
              fours: double
              sixes: double
              wides: double
              noballs: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2075
              to
              {'Match ID': Value(dtype='int64', id=None), 'innings': Value(dtype='int64', id=None), 'team': Value(dtype='string', id=None), 'batsman': Value(dtype='float64', id=None), 'runs': Value(dtype='float64', id=None), 'balls': Value(dtype='float64', id=None), 'fours': Value(dtype='float64', id=None), 'sixes': Value(dtype='float64', id=None), 'strikeRate': Value(dtype='float64', id=None), 'isOut': Value(dtype='bool', id=None), 'wicketType': Value(dtype='string', id=None), 'fielders': Value(dtype='string', id=None), 'bowler': 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 1321, 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 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2013, 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 10 new columns ({'wides', 'conceded', 'overs', 'maidens', 'wickets', 'bowler id', 'noballs', 'dots', 'opposition', 'economy'}) and 7 missing columns ({'strikeRate', 'fielders', 'wicketType', 'isOut', 'batsman', 'runs', 'bowler'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/bhuvaneshprasad/odi-cricket-dataset-1971-2014/odi_Bowling_Card.csv (at revision dbe8f34ce6e781fd52c0ae8ddd5807a539646047)
              
              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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Match ID
int64
innings
int64
team
string
batsman
float64
runs
float64
balls
float64
fours
float64
sixes
float64
strikeRate
float64
isOut
bool
wicketType
string
fielders
string
bowler
null
64,381
1
Sri Lanka
1,810
5
17
0
0
29.41
true
lbw
null
null
64,357
1
Pakistan
1,981
35
48
2
0
72.91
true
caught
['1977']
null
65,455
1
Australia
1,922
16
30
1
0
53.33
true
caught
['1945']
null
64,381
1
Sri Lanka
1,987
6
46
0
0
13.04
true
caught
['1980']
null
64,357
1
Pakistan
1,750
114
123
14
0
92.68
true
run out
null
null
251,495
1
Australia
2,119
24
36
5
0
66.66
true
caught
['4380']
null
65,455
1
Australia
1,793
9
25
1
0
36
true
caught
['1945']
null
64,555
1
India
1,934
1
11
0
0
9.09
true
caught
['1982']
null
64,381
1
Sri Lanka
1,789
37
56
3
0
66.07
true
caught
['1383']
null
64,357
1
Pakistan
1,672
65
68
5
0
95.58
false
not out
['-']
null
65,826
1
India
2,060
25
37
2
0
67.56
true
caught
['2147']
null
251,495
1
Australia
10,538
3
16
0
0
18.75
true
caught
['2121']
null
65,878
1
West Indies
2,023
8
22
1
0
36.36
true
caught
['2024']
null
65,455
1
Australia
1,754
69
98
2
0
70.4
true
run out
null
null
64,555
1
India
2,024
4
5
1
0
80
true
bowled
null
null
64,566
1
New Zealand
2,235
33
37
7
0
89.18
true
caught
['2107']
null
64,381
1
Sri Lanka
1,762
19
37
0
0
51.35
true
caught
['1775']
null
64,357
1
Pakistan
1,978
5
2
1
0
250
false
not out
['-']
null
64,471
1
Pakistan
1,981
0
2
0
0
0
true
caught
['1998']
null
66,276
2
Australia
2,101
null
null
null
null
null
false
DNB
null
null
433,579
1
England
7,023
0
3
0
0
0
true
caught
['46533']
null
433,579
1
England
8,107
2
3
0
0
66.66
true
caught
['2232']
null
433,579
1
England
10,407
52
94
3
0
55.31
true
caught
['19422']
null
433,579
1
England
7,822
5
7
1
0
71.42
true
caught
['9492']
null
433,579
1
England
44,691
60
98
3
1
61.22
true
lbw
null
null
433,579
1
England
11,120
10
19
1
0
52.63
true
caught
['6354']
null
433,579
1
England
8,307
3
17
0
0
17.64
true
caught
['9492']
null
433,579
1
England
34,739
1
4
0
0
25
true
lbw
null
null
473,926
1
New Zealand
48,927
21
17
3
1
123.52
true
caught
['10439']
null
433,579
1
England
7,013
16
20
3
0
80
true
caught
['45222']
null
473,926
1
New Zealand
10,381
13
29
2
0
44.82
true
caught
['53546']
null
433,579
1
England
48,440
0
3
0
0
0
true
lbw
null
null
473,926
1
New Zealand
44,930
4
5
1
0
80
true
caught
['10439']
null
433,579
1
England
10,829
2
6
0
0
33.33
false
not out
['-']
null
473,926
1
New Zealand
9,570
11
28
2
0
39.28
true
run out
['44908', '19647']
null
433,579
2
South Africa
9,952
42
51
2
0
82.35
true
bowled
null
null
473,926
1
New Zealand
51,088
15
36
1
0
41.66
true
caught
['10439']
null
433,579
2
South Africa
10,406
22
41
2
0
53.65
true
caught
['11120']
null
473,926
1
New Zealand
9,639
62
75
7
0
82.66
true
caught
['24723']
null
433,579
2
South Africa
2,232
15
20
3
0
75
true
caught
['11120']
null
473,926
1
New Zealand
10,384
37
39
3
0
94.87
true
caught
['9257']
null
433,579
2
South Africa
46,533
25
44
0
0
56.81
true
bowled
null
null
473,926
1
New Zealand
10,386
53
58
5
1
91.37
false
not out
['-']
null
433,579
2
South Africa
46,933
17
38
2
0
44.73
true
run out
['7822', '11120']
null
473,926
1
New Zealand
4,380
13
15
1
0
86.66
false
not out
['-']
null
433,579
2
South Africa
45,222
0
4
0
0
0
true
bowled
null
null
473,926
1
New Zealand
49,108
null
null
null
null
null
false
DNB
null
null
433,605
1
India
7,781
38
25
9
0
152
true
lbw
null
null
433,579
2
South Africa
6,354
13
37
0
0
35.13
true
bowled
null
null
473,926
1
New Zealand
48,928
null
null
null
null
null
false
DNB
null
null
433,605
1
India
1,934
85
115
11
0
73.91
true
caught
['4169']
null
433,579
2
South Africa
9,492
3
16
0
0
18.75
true
caught
['11120']
null
473,926
2
Pakistan
19,647
12
23
2
0
52.17
true
caught
['44930']
null
433,605
1
India
7,773
27
32
2
0
84.37
true
stumping
['9257']
null
433,579
2
South Africa
47,154
20
31
3
0
64.51
true
lbw
null
null
433,605
1
India
49,752
9
21
0
0
42.85
true
caught
['53546']
null
433,579
2
South Africa
47,289
1
3
0
0
33.33
true
caught
['11120']
null
473,926
2
Pakistan
49,899
42
42
6
1
100
true
caught
['44930']
null
489,214
1
West Indies
45,256
51
48
4
2
106.25
true
caught
['53546']
null
433,579
2
South Africa
19,422
1
1
0
0
100
false
not out
['-']
null
433,605
1
India
7,716
0
1
0
0
0
true
bowled
null
null
518,203
1
Afghanistan
52,976
1
2
0
0
50
true
caught
['52871']
null
489,214
1
West Indies
10,494
16
21
1
1
76.19
true
lbw
null
null
473,926
2
Pakistan
9,257
20
30
2
0
66.66
true
caught
['44930']
null
433,605
1
India
7,593
25
42
2
0
59.52
true
lbw
null
null
518,203
1
Afghanistan
53,767
34
23
4
1
147.82
true
lbw
null
null
489,214
1
West Indies
51,054
12
18
2
0
66.66
true
caught
['19596']
null
473,926
2
Pakistan
10,439
42
63
1
0
66.66
true
run out
['10386', '10384']
null
433,605
1
India
15,716
36
39
3
0
92.3
false
not out
['-']
null
433,599
1
India
7,773
22
26
4
0
84.61
true
caught
['51012']
null
518,203
1
Afghanistan
60,436
8
10
1
0
80
true
caught
['60142']
null
489,214
1
West Indies
10,238
29
74
2
0
39.18
true
bowled
null
null
473,926
2
Pakistan
19,596
93
91
7
1
102.19
false
not out
['-']
null
433,566
1
Bangladesh
48,391
44
43
7
0
102.32
true
caught
['47403']
null
433,605
1
India
7,139
12
15
2
0
80
true
stumping
['9257']
null
433,584
1
West Indies
10,494
107
133
11
1
80.45
true
bowled
null
null
433,599
1
India
1,934
2
4
0
0
50
true
caught
['49521']
null
518,203
1
Afghanistan
53,602
14
6
3
0
233.33
true
bowled
null
null
489,214
1
West Indies
47,110
4
12
0
0
33.33
true
bowled
null
null
473,926
2
Pakistan
53,546
10
17
1
0
58.82
true
caught
['10386']
null
433,566
1
Bangladesh
51,239
12
12
2
0
100
true
stumping
['10351']
null
446,965
1
England
7,023
8
10
1
0
80
true
caught
['6426']
null
433,605
1
India
7,678
9
10
1
0
90
true
caught
['9257']
null
433,584
1
West Indies
2,120
35
62
3
0
56.45
true
caught
['47403']
null
433,599
1
India
49,752
59
76
5
0
77.63
true
bowled
null
null
518,203
1
Afghanistan
46,888
47
31
1
4
151.61
true
caught
['48506']
null
489,214
1
West Indies
45,257
18
24
1
0
75
true
caught
['19596']
null
473,926
2
Pakistan
4,169
4
2
1
0
200
true
lbw
null
null
433,566
1
Bangladesh
47,218
3
8
0
0
37.5
true
run out
['7233']
null
446,965
1
England
11,120
67
58
8
1
115.51
true
caught
['12912']
null
433,605
1
India
7,804
1
2
0
0
50
true
run out
['24723', '9257']
null
433,584
1
West Indies
51,054
0
3
0
0
0
true
bowled
null
null
433,599
1
India
7,716
113
123
10
2
91.86
true
caught
['49040']
null
518,203
1
Afghanistan
53,809
15
18
0
1
83.33
true
caught
['10334']
null
489,214
1
West Indies
17,838
15
22
1
0
68.18
true
lbw
null
null
473,926
2
Pakistan
4,178
23
18
1
1
127.77
true
caught
['4380']
null
433,566
1
Bangladesh
47,986
36
66
2
0
54.54
true
caught
['10342']
null
446,965
1
England
10,407
102
126
6
0
80.95
true
bowled
null
null
433,605
1
India
47,100
0
0
0
0
0
false
not out
['-']
null
433,584
1
West Indies
6,405
10
19
1
0
52.63
true
caught
['10345']
null
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