Dataset Preview
Duplicate
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 5 new columns ({'sigla_uf_escola', 'id_municipio_residencia', 'id_municipio_escola', 'id_inscricao', 'sigla_uf_residencia'}) and 4 missing columns ({'media', 'nota_media', 'Unnamed: 0', 'nota_media_float'}).

This happened while the csv dataset builder was generating data using

hf://datasets/diegolaterza/enem-2022-survey/enem-2022-survey-raw.csv (at revision 1c053bba7db9e8bf9f96dcbaa5f09acabf4dd74b)

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 1869, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 580, 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 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              id_inscricao: int64
              Q001: string
              Q002: string
              Q003: string
              Q004: string
              Q005: int64
              Q006: string
              Q007: string
              Q008: string
              Q009: string
              Q010: string
              Q011: string
              Q012: string
              Q013: string
              Q014: string
              Q015: string
              Q016: string
              Q017: string
              Q018: string
              Q019: string
              Q020: string
              Q021: string
              Q022: string
              Q023: string
              Q024: string
              Q025: string
              faixa_etaria: double
              sexo: string
              estado_civil: double
              cor_raca: double
              id_municipio_residencia: double
              sigla_uf_residencia: double
              id_municipio_escola: double
              sigla_uf_escola: string
              nota_ciencias_natureza: double
              nota_ciencias_humanas: double
              nota_linguagens_codigos: double
              nota_matematica: double
              nota_redacao: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 4802
              to
              {'Unnamed: 0': Value(dtype='int64', id=None), 'Q001': Value(dtype='int64', id=None), 'Q002': Value(dtype='int64', id=None), 'Q003': Value(dtype='int64', id=None), 'Q004': Value(dtype='int64', id=None), 'Q005': Value(dtype='int64', id=None), 'Q006': Value(dtype='int64', id=None), 'Q007': Value(dtype='int64', id=None), 'Q008': Value(dtype='int64', id=None), 'Q009': Value(dtype='int64', id=None), 'Q010': Value(dtype='int64', id=None), 'Q011': Value(dtype='int64', id=None), 'Q012': Value(dtype='int64', id=None), 'Q013': Value(dtype='int64', id=None), 'Q014': Value(dtype='int64', id=None), 'Q015': Value(dtype='int64', id=None), 'Q016': Value(dtype='int64', id=None), 'Q017': Value(dtype='int64', id=None), 'Q018': Value(dtype='int64', id=None), 'Q019': Value(dtype='int64', id=None), 'Q020': Value(dtype='int64', id=None), 'Q021': Value(dtype='int64', id=None), 'Q022': Value(dtype='int64', id=None), 'Q023': Value(dtype='int64', id=None), 'Q024': Value(dtype='int64', id=None), 'Q025': Value(dtype='int64', id=None), 'faixa_etaria': Value(dtype='int64', id=None), 'sexo': Value(dtype='int64', id=None), 'estado_civil': Value(dtype='int64', id=None), 'cor_raca': Value(dtype='int64', id=None), 'nota_ciencias_natureza': Value(dtype='float64', id=None), 'nota_ciencias_humanas': Value(dtype='float64', id=None), 'nota_linguagens_codigos': Value(dtype='float64', id=None), 'nota_matematica': Value(dtype='float64', id=None), 'nota_redacao': Value(dtype='float64', id=None), 'nota_media_float': Value(dtype='float64', id=None), 'nota_media': Value(dtype='int64', id=None), 'media': 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 1392, 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 1041, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 999, 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 1740, 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 1871, 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 5 new columns ({'sigla_uf_escola', 'id_municipio_residencia', 'id_municipio_escola', 'id_inscricao', 'sigla_uf_residencia'}) and 4 missing columns ({'media', 'nota_media', 'Unnamed: 0', 'nota_media_float'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/diegolaterza/enem-2022-survey/enem-2022-survey-raw.csv (at revision 1c053bba7db9e8bf9f96dcbaa5f09acabf4dd74b)
              
              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
Q001
int64
Q002
int64
Q003
int64
Q004
int64
Q005
int64
Q006
int64
Q007
int64
Q008
int64
Q009
int64
Q010
int64
Q011
int64
Q012
int64
Q013
int64
Q014
int64
Q015
int64
Q016
int64
Q017
int64
Q018
int64
Q019
int64
Q020
int64
Q021
int64
Q022
int64
Q023
int64
Q024
int64
Q025
int64
faixa_etaria
int64
sexo
int64
estado_civil
int64
cor_raca
int64
nota_ciencias_natureza
float64
nota_ciencias_humanas
float64
nota_linguagens_codigos
float64
nota_matematica
float64
nota_redacao
float64
nota_media_float
float64
nota_media
int64
media
float64
0
1
5
3
2
4
1
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
4
1
1
1
9
1
1
3
579.7
580.5
518
619.3
540
567.5
6
1
4
1
2
6
6
4
1
1
2
3
1
1
2
1
1
1
1
1
1
1
1
1
2
1
1
1
4
0
1
3
418
496.1
361.5
397.1
0
334.54
3
0
5
1
2
6
6
2
1
1
2
3
1
1
2
2
2
1
1
1
1
1
1
1
3
1
1
2
3
0
1
1
389.5
408.7
406.4
345
620
433.92
4
0
6
1
1
1
1
6
1
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
2
1
2
1
11
0
1
3
497.4
332.4
428.5
537.9
440
447.24
4
0
8
1
5
1
1
3
1
1
2
3
1
2
2
1
1
1
1
1
1
2
1
1
3
1
1
2
2
1
3
4
419.9
518.5
444.3
448.3
460
458.2
5
0
9
1
2
6
2
6
1
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
4
1
1
2
4
0
1
1
422.1
517.6
472.5
383.5
0
359.14
4
0
11
1
2
2
2
3
2
1
2
3
2
1
2
1
2
1
1
1
1
2
1
1
3
1
1
2
13
1
2
2
450.9
560.6
520.5
344
600
495.2
5
0
12
1
2
1
3
5
2
1
2
2
1
2
2
1
2
1
1
1
1
2
1
1
3
1
1
2
13
1
2
3
425.7
466.2
477.2
566.7
520
491.16
5
0
13
1
1
1
1
1
2
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
2
13
1
1
3
443.8
526.2
453.9
651.4
600
535.06
5
0
14
1
2
1
1
5
2
1
2
2
1
2
2
1
1
1
1
1
1
1
1
1
3
1
1
1
3
1
1
3
580.8
536.3
563.5
449.6
720
570.04
6
1
17
1
4
1
1
3
2
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
2
3
0
1
3
366.3
428.6
363.9
420.7
320
379.9
4
0
21
1
1
6
6
5
2
1
3
4
2
1
2
2
2
2
2
1
1
2
1
1
5
1
3
2
18
1
2
3
492.1
468.3
486.6
434.8
300
436.36
4
0
22
1
4
2
2
4
2
1
2
3
1
1
2
1
1
1
1
1
1
2
2
1
4
1
1
2
5
1
1
2
608.3
570.7
615.4
522
560
575.28
6
1
26
1
1
1
1
3
2
1
2
3
1
2
2
1
1
1
1
1
1
2
1
1
3
1
1
2
9
0
1
3
522.1
538.7
502.9
580.3
600
548.8
5
1
28
1
4
1
2
2
2
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
1
11
0
2
3
396.7
472.5
499.5
421.1
480
453.96
5
0
31
1
1
1
1
4
2
1
3
3
1
1
1
1
1
1
1
1
1
2
1
1
2
1
1
1
13
1
2
5
408
373.5
336.9
407.1
360
377.1
4
0
33
1
1
1
1
5
2
1
2
3
1
2
2
1
1
1
1
1
1
1
1
1
2
1
1
2
3
0
1
3
426.7
532.1
527.4
497.9
640
524.82
5
0
35
1
2
1
1
6
2
1
2
3
1
2
2
1
1
1
1
1
1
2
2
1
2
1
1
2
4
1
1
2
468.9
491.3
500.6
560.8
420
488.32
5
0
36
1
5
1
1
7
2
1
2
3
1
2
2
1
1
1
1
1
1
2
2
1
2
1
1
2
3
0
1
3
535.1
465.1
353
481.6
420
450.96
5
0
37
1
2
1
2
3
2
1
2
4
2
1
2
1
2
1
2
1
2
2
1
1
3
1
2
2
2
1
1
1
648.6
572.8
599
677
700
639.48
6
1
38
1
2
6
2
3
2
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
2
3
1
3
1
495.2
565.6
525
548.7
560
538.9
5
0
39
1
1
1
1
5
2
1
2
3
1
2
2
1
1
1
1
1
1
2
1
1
2
1
1
1
8
1
1
0
481.1
509.3
512.3
373.9
480
471.32
5
0
40
1
1
3
1
4
2
1
2
3
2
1
2
1
1
1
1
1
1
2
1
1
3
1
1
2
14
0
2
2
512.3
545.4
530.5
639.9
540
553.62
6
1
45
1
2
1
1
6
2
1
2
4
1
2
2
1
1
1
1
1
1
1
1
1
3
1
1
2
6
0
1
3
567.8
502.9
527.1
686.8
620
580.92
6
1
47
1
2
3
3
3
3
1
2
3
2
1
2
2
2
1
2
1
1
2
1
1
3
1
2
2
14
1
2
1
417
407.9
305.5
460.2
520
422.12
4
0
52
1
2
3
2
2
3
1
2
3
1
2
2
1
2
1
1
1
1
2
1
1
3
1
1
2
12
1
1
3
384.2
503.9
419.1
406.2
440
430.68
4
0
53
1
3
1
1
4
3
1
2
4
2
1
2
1
1
1
1
1
1
3
2
1
5
1
1
1
3
0
1
3
493.5
523.7
525.4
578.5
520
528.22
5
0
58
1
3
1
1
4
3
1
2
3
2
2
2
2
1
1
1
1
1
2
1
1
3
1
1
2
13
0
2
1
400.6
491.2
383.2
473.8
320
413.76
4
0
61
1
4
2
2
3
4
1
2
3
1
1
2
2
2
1
2
1
1
4
1
1
3
1
3
2
6
1
1
3
554.2
477.2
530.9
680.5
740
596.56
6
1
63
1
2
1
2
4
4
1
2
4
1
2
2
1
1
1
1
1
1
2
1
1
3
1
1
2
10
0
1
1
517.6
338.4
460.5
352.8
640
461.86
5
0
64
1
2
2
2
3
4
1
3
4
2
1
2
2
2
1
1
1
1
2
1
1
4
1
1
2
3
0
1
3
515.8
499.7
457.7
392.5
500
473.14
5
0
66
1
2
3
6
2
6
1
2
2
2
1
2
1
2
1
2
2
2
2
1
1
2
1
2
2
12
1
1
3
476.7
514.3
542
701
420
530.8
5
0
69
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
14
1
1
2
516.1
654.4
611.7
582
680
608.84
6
1
71
2
5
4
2
4
1
1
2
3
1
1
2
1
1
1
2
1
1
2
1
1
3
1
2
2
2
0
1
1
488.5
493.4
550
546.3
660
547.64
5
1
75
2
2
2
2
2
1
1
2
2
1
1
2
2
2
2
2
1
1
2
1
1
3
1
1
2
5
0
1
2
467.4
389.2
408.4
378.2
520
432.64
4
0
76
2
3
6
6
4
1
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
3
1
1
2
1
1
1
3
451.7
414.1
361.9
376.9
760
472.92
5
0
78
2
2
1
1
7
1
1
2
3
2
1
2
1
1
1
2
1
1
2
1
1
5
1
1
2
4
1
1
3
411.2
503.3
446.5
462.4
480
460.68
5
0
79
2
5
3
2
4
1
1
2
3
1
2
2
1
1
1
1
1
1
1
1
1
3
1
1
2
3
0
1
5
393.6
504.5
439.3
553.4
740
526.16
5
0
81
2
8
1
1
5
1
1
2
4
1
1
2
1
1
1
1
1
1
2
1
1
3
1
1
2
4
0
1
2
417.3
433
363.4
408.4
320
388.42
4
0
82
2
1
1
1
2
1
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
1
13
0
2
2
498.7
595.1
571.9
461.8
540
533.5
5
0
83
2
2
1
1
3
1
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
1
10
0
1
3
567.9
632
611.6
645.6
880
667.42
7
1
84
2
2
1
1
5
1
1
1
4
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
1
5
1
1
3
504.2
558.5
552.3
654.2
600
573.84
6
1
85
2
2
1
1
5
1
1
2
4
1
2
2
1
1
1
1
1
1
2
1
1
4
1
1
2
9
0
1
3
425.8
457.5
494.7
568.6
740
537.32
5
0
87
2
2
1
1
1
1
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
2
2
11
1
1
2
458.8
490.1
345.7
422.3
600
463.38
5
0
89
2
3
1
1
3
1
1
2
4
1
2
2
1
1
1
1
1
1
2
1
1
4
1
2
2
6
0
1
3
383.8
428
517.8
439.7
620
477.86
5
0
92
2
3
3
2
4
1
1
2
3
1
2
2
1
1
1
1
1
1
2
2
1
2
1
1
2
3
0
1
3
526.7
513.2
481
449.4
520
498.06
5
0
94
2
5
6
2
5
1
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
5
1
1
2
3
0
1
1
400.7
532.6
509.7
533.9
0
395.38
4
0
96
2
5
1
1
4
1
1
2
3
1
2
2
1
2
1
1
1
1
2
2
1
4
1
1
2
3
0
1
1
393.5
440.7
519.2
541.6
900
559
6
1
98
2
2
1
2
3
1
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
3
1
1
2
10
0
1
3
461.8
512.4
456.4
469
560
491.92
5
0
100
2
5
2
1
4
1
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
3
1
1
2
3
1
1
3
601.6
615.1
585.9
626.7
0
485.86
5
0
101
2
2
1
1
4
1
1
2
3
1
1
1
1
1
1
1
1
1
2
1
1
2
1
1
2
4
0
1
3
464.4
525
466.1
430.7
720
521.24
5
0
102
2
3
2
2
4
2
1
2
3
1
1
2
1
1
1
1
1
1
1
1
1
3
1
2
2
8
0
1
3
469.6
564.2
515.9
472.4
760
556.42
6
1
103
2
2
2
2
4
2
1
2
4
1
2
2
2
2
1
2
1
1
2
1
2
3
1
1
2
5
0
1
3
423
497.9
464.3
408.6
560
470.76
5
0
109
2
3
2
1
4
2
1
2
4
2
1
2
1
2
1
1
1
1
2
1
1
2
1
1
2
11
1
1
5
425.8
505.2
566.4
609.9
560
533.46
5
0
110
2
5
1
1
5
2
1
2
4
1
2
2
1
2
1
1
1
1
2
1
1
4
1
1
2
2
0
1
3
449.1
518.4
382.2
542.1
900
558.36
6
1
112
2
5
3
2
3
2
1
3
4
1
1
2
2
1
1
2
1
1
3
1
1
4
2
2
2
9
0
1
3
483.8
512.2
526.3
504.3
360
477.32
5
0
113
2
2
1
1
3
2
1
3
4
1
1
2
1
1
2
1
1
1
2
1
1
3
1
1
1
3
1
1
3
405
607.6
577.3
479.6
620
537.9
5
0
114
2
3
3
2
5
2
1
2
4
1
1
2
1
1
1
1
1
1
2
1
1
4
1
2
2
5
0
1
1
504.8
483.3
538.2
578.1
700
560.88
6
1
115
2
4
2
2
4
2
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
2
3
0
1
3
395.8
483.1
460
447.3
560
469.24
5
0
116
2
2
1
1
1
2
1
2
2
1
1
2
1
1
1
1
1
1
1
1
1
2
1
1
2
7
0
1
3
504.8
560.3
550.5
394.5
640
530.02
5
0
118
2
3
3
2
2
2
1
2
2
1
1
2
2
2
1
2
1
2
2
2
1
2
2
2
2
3
0
1
3
423.8
579.6
582.6
655.2
780
604.24
6
1
119
2
2
1
2
5
2
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
3
1
1
2
3
0
1
2
414.1
520.9
527.8
376.9
520
471.94
5
0
120
2
4
1
2
4
2
1
2
4
2
1
2
1
1
1
1
1
1
2
1
1
4
1
1
2
3
0
1
1
467.3
504.4
452.4
402.1
300
425.24
4
0
121
2
2
3
2
6
2
1
2
3
1
2
2
1
1
1
1
1
1
2
1
1
3
1
1
1
5
0
1
3
459.1
440.9
400.9
388.6
340
405.9
4
0
122
2
3
3
2
5
2
1
2
4
1
2
2
1
1
1
1
1
1
2
1
1
5
1
1
2
7
1
1
3
393.1
368.4
370.2
479.8
520
426.3
4
0
124
2
5
4
4
3
2
1
2
3
1
1
2
2
2
1
2
1
1
2
1
1
4
2
1
2
3
0
1
3
539.9
521.4
565.6
544.3
860
606.24
6
1
125
2
5
2
6
4
2
1
2
3
1
1
2
1
1
1
1
1
1
2
2
2
3
1
1
2
3
0
1
2
401.9
514.8
499
548.4
480
488.82
5
0
126
2
5
1
2
3
2
1
2
3
1
2
2
1
1
1
1
1
1
2
1
1
3
1
1
2
2
0
1
1
431.9
453.5
466.1
461.3
580
478.56
5
0
127
2
3
6
2
3
2
1
2
2
2
1
2
1
2
2
1
1
1
2
1
1
3
1
1
2
13
1
1
2
518.8
451.8
434.4
402
520
465.4
5
0
128
2
2
2
1
2
2
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
2
2
9
0
1
3
587.2
683.8
620
714.6
900
701.12
7
1
133
2
4
1
2
4
2
1
2
3
1
1
2
1
1
1
1
1
1
1
1
1
2
1
2
2
2
1
1
3
417.7
509.8
489
382.1
560
471.72
5
0
134
2
2
1
1
7
2
1
2
3
1
3
2
1
1
1
1
1
1
2
1
1
5
1
1
2
3
0
1
3
453.2
491.8
437.5
430.4
420
446.58
4
0
138
2
4
1
1
4
2
1
1
3
1
1
2
1
1
1
1
1
1
2
2
1
2
1
1
2
2
0
1
3
512.2
516.7
452.4
580.9
780
568.44
6
1
139
2
4
2
2
3
2
1
2
3
2
1
2
2
2
1
2
1
1
2
2
1
1
1
1
2
3
0
1
1
403
459.2
437.5
438.6
440
435.66
4
0
140
2
5
2
2
4
2
1
3
4
2
2
2
1
1
1
2
1
1
1
1
1
5
1
1
2
5
0
1
3
517.7
498.3
558.2
564.9
660
559.82
6
1
142
2
5
2
2
1
2
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
2
2
11
0
1
3
528.6
547.7
507.7
493
700
555.4
6
1
143
2
2
6
6
2
2
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
3
1
1
1
3
0
1
3
386.1
496.5
407.2
474.7
540
460.9
5
0
144
2
4
3
2
3
2
1
2
3
1
1
2
2
1
1
1
1
1
2
1
1
4
1
1
2
2
0
1
3
507.2
483.9
370.1
444.1
620
485.06
5
0
146
2
3
1
1
9
2
1
2
1
1
1
2
2
2
1
1
1
1
2
1
1
2
1
1
1
6
0
1
2
421.1
404.3
318.6
343.7
500
397.54
4
0
147
2
1
1
1
2
2
1
2
2
1
2
2
2
1
1
1
1
1
2
1
1
3
1
2
2
8
1
1
3
443.2
505
420.2
544.2
460
474.52
5
0
149
2
5
1
1
4
2
1
2
3
1
1
2
1
1
1
1
1
1
1
1
1
3
1
1
2
3
0
1
3
517.5
576.5
546.5
598.8
920
631.86
6
1
154
2
2
2
2
5
2
1
2
4
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
2
12
0
1
3
413.2
416.6
333.4
379.7
0
308.58
3
0
156
2
3
6
6
5
2
1
3
3
1
1
2
1
1
1
1
1
1
3
1
1
4
2
1
2
4
0
1
3
411.9
501.3
553.5
427.3
640
506.8
5
0
158
2
3
1
2
4
2
1
2
3
1
1
2
1
2
1
1
1
1
2
1
1
2
1
1
2
1
0
1
2
424.9
471
488.4
540.5
560
496.96
5
0
160
2
5
6
2
2
2
1
2
3
1
1
2
1
1
1
2
1
1
2
1
2
3
1
1
2
2
0
1
3
424.7
358.3
425.4
489.7
620
463.62
5
0
162
2
2
1
1
3
2
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
3
1
1
2
2
1
1
3
470.1
400.6
470.6
455.3
420
443.32
4
0
164
2
6
3
4
3
2
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
4
1
1
1
5
1
1
3
484.3
520.6
499.6
692.2
520
543.34
5
0
166
2
2
4
1
3
2
1
2
3
1
1
2
2
1
1
1
1
1
2
1
1
3
1
1
2
12
0
2
1
456.5
471.5
402.2
490
520
468.04
5
0
167
2
2
1
1
5
2
1
2
1
1
1
2
1
2
2
1
2
1
1
1
1
4
2
1
2
13
0
0
3
417.4
444.5
386.8
369.3
280
379.6
4
0
168
2
1
2
2
4
2
2
3
2
3
3
3
2
3
2
3
3
1
2
1
1
3
1
2
2
6
1
1
3
421.8
499.5
483.8
422.7
600
485.56
5
0
169
2
2
1
1
4
2
1
2
3
1
1
2
1
1
1
1
1
1
2
1
1
3
1
1
2
2
0
1
3
444.8
451.6
410.5
348.5
340
399.08
4
0
170
2
4
1
1
5
2
1
3
3
2
1
2
2
2
1
1
1
1
2
1
1
3
1
2
2
4
1
1
3
509.8
379.4
331.7
443
0
332.78
3
0
171
2
2
1
1
5
2
1
2
3
1
2
2
1
1
1
1
1
1
1
1
1
3
1
1
2
3
1
1
0
384.1
445.9
353
416.7
420
403.94
4
0
173
2
5
1
2
4
2
1
2
3
1
1
2
1
2
1
2
1
1
2
1
1
4
1
1
2
2
0
1
1
402.5
528.6
521.3
420.2
400
454.52
5
0
177
2
5
3
2
4
2
1
2
4
2
1
2
2
2
1
1
1
1
3
2
1
4
2
2
2
3
0
1
1
463.6
546.7
523.4
544.8
820
579.7
6
1
178
2
2
2
2
3
2
1
2
2
1
1
2
1
1
1
1
1
1
2
1
1
2
1
1
1
4
0
1
3
494.2
460.4
464.3
536.1
560
503
5
0
181
2
1
1
1
7
2
1
2
3
1
4
2
2
2
1
1
1
1
2
1
1
5
1
2
2
3
1
1
1
584.9
575.5
527.8
437.5
580
541.14
5
0
184
2
5
3
2
3
2
1
2
3
1
1
2
2
2
1
1
1
1
2
2
1
4
1
1
2
6
0
1
3
494.5
448.1
463.2
493.4
660
511.84
5
0
186
2
2
1
1
5
2
1
2
4
1
2
2
1
1
1
1
1
1
2
1
1
4
1
1
1
11
0
1
3
491.5
556.6
528.4
468
580
524.9
5
0
188
2
2
1
1
5
2
1
2
3
1
1
2
1
1
1
1
1
1
1
1
1
3
1
1
1
3
0
1
3
441.8
441.7
487.9
384.8
0
351.24
4
0
End of preview.
README.md exists but content is empty.
Downloads last month
4