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arcinstitute
/
Replogle-Nadig-Models

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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 1 new columns ({'perturbation'}) and 1 missing columns ({'statistic'}).

This happened while the csv dataset builder was generating data using

hf://datasets/arcinstitute/Replogle-Nadig-Models/hepg2/eval_train_last.ckpt/hepg2_hepg2_results.csv (at revision a2e587fa9493c9501efc21361dbd92efe2268fa5)

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 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, 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 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              perturbation: string
              overlap_at_N: double
              overlap_at_50: double
              overlap_at_100: double
              overlap_at_200: double
              overlap_at_500: double
              precision_at_N: double
              precision_at_50: double
              precision_at_100: double
              precision_at_200: double
              precision_at_500: double
              de_spearman_sig: double
              de_direction_match: double
              de_spearman_lfc_sig: double
              de_sig_genes_recall: double
              de_nsig_counts_real: double
              de_nsig_counts_pred: double
              pr_auc: double
              roc_auc: double
              pearson_delta: double
              mse: double
              mae: double
              mse_delta: double
              mae_delta: double
              discrimination_score_l1: double
              discrimination_score_l2: double
              discrimination_score_cosine: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3763
              to
              {'statistic': Value('string'), 'overlap_at_N': Value('float64'), 'overlap_at_50': Value('float64'), 'overlap_at_100': Value('float64'), 'overlap_at_200': Value('float64'), 'overlap_at_500': Value('float64'), 'precision_at_N': Value('float64'), 'precision_at_50': Value('float64'), 'precision_at_100': Value('float64'), 'precision_at_200': Value('float64'), 'precision_at_500': Value('float64'), 'de_spearman_sig': Value('float64'), 'de_direction_match': Value('float64'), 'de_spearman_lfc_sig': Value('float64'), 'de_sig_genes_recall': Value('float64'), 'de_nsig_counts_real': Value('float64'), 'de_nsig_counts_pred': Value('float64'), 'pr_auc': Value('float64'), 'roc_auc': Value('float64'), 'pearson_delta': Value('float64'), 'mse': Value('float64'), 'mae': Value('float64'), 'mse_delta': Value('float64'), 'mae_delta': Value('float64'), 'discrimination_score_l1': Value('float64'), 'discrimination_score_l2': Value('float64'), 'discrimination_score_cosine': Value('float64')}
              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 1451, 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 994, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, 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 1833, 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 1 new columns ({'perturbation'}) and 1 missing columns ({'statistic'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/arcinstitute/Replogle-Nadig-Models/hepg2/eval_train_last.ckpt/hepg2_hepg2_results.csv (at revision a2e587fa9493c9501efc21361dbd92efe2268fa5)
              
              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.

statistic
string
overlap_at_N
float64
overlap_at_50
float64
overlap_at_100
float64
overlap_at_200
float64
overlap_at_500
float64
precision_at_N
float64
precision_at_50
float64
precision_at_100
float64
precision_at_200
float64
precision_at_500
float64
de_spearman_sig
float64
de_direction_match
float64
de_spearman_lfc_sig
float64
de_sig_genes_recall
float64
de_nsig_counts_real
float64
de_nsig_counts_pred
float64
pr_auc
float64
roc_auc
float64
pearson_delta
float64
mse
float64
mae
float64
mse_delta
float64
mae_delta
float64
discrimination_score_l1
float64
discrimination_score_l2
float64
discrimination_score_cosine
float64
count
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
900
null_count
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
mean
0.224822
0.141667
0.20547
0.241825
0.229196
0.224801
0.140239
0.204808
0.243328
0.232813
0.921741
0.849295
null
0.260926
208.566667
209.814444
0.670491
0.88541
0.560888
0.004848
0.048883
0.004781
0.0486
0.807267
0.826607
0.741384
std
0.278093
0.170921
0.255253
0.306625
0.28584
0.276533
0.174222
0.258123
0.309531
0.290126
0
0.156213
null
0.331164
249.513785
326.608946
0
0
0.292454
0.002402
0.010871
0.002402
0.010981
0.196278
0.188344
0.283119
min
0
0
0
0
0
0
0
0
0
0
0.921741
0.272727
-0.7
0
1
0
0.670491
0.88541
-0.197115
0.000379
0.012613
0.000329
0.011554
0.135556
0.161111
0.002222
25%
0
0
0
0
0
0
0
0
0
0
0.921741
0.762712
0.428571
0
23
0
0.670491
0.88541
0.309092
0.003257
0.041269
0.003204
0.040922
0.667778
0.702222
0.546667
50%
0.019802
0.02
0.02
0.019802
0.019802
0
0
0
0
0
0.921741
0.910256
0.754622
0.019802
82
4
0.670491
0.88541
0.574482
0.004528
0.049304
0.00444
0.04895
0.87
0.893333
0.871111
75%
0.501754
0.3
0.42
0.515
0.501754
0.521311
0.3
0.44
0.515
0.52
0.921741
0.974453
0.884929
0.583333
350
355
0.670491
0.88541
0.842031
0.005812
0.054513
0.005743
0.054284
0.987778
0.99
0.987778
max
0.848315
0.58
0.81
0.915
0.874
0.819558
0.58
0.81
0.915
0.874
0.921741
1
1
0.941704
1,424
1,585
0.670491
0.88541
0.986927
0.020723
0.096392
0.020715
0.096667
1
1
1
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.615385
-0.076923
0
13
0
0.670491
0.88541
0.306234
0.004441
0.050579
0.004374
0.050339
0.696667
0.743333
0.625556
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.666667
0.34965
0
12
0
0.670491
0.88541
0.115202
0.004787
0.053663
0.004721
0.053413
0.682222
0.756667
0.502222
null
0.615538
0.36
0.53
0.625
0.616
0.605307
0.36
0.53
0.625
0.616
0.921741
0.966135
0.931549
0.727092
502
603
0.670491
0.88541
0.88782
0.007824
0.059788
0.007782
0.059962
0.984444
0.985556
0.982222
null
0.611628
0.2
0.52
0.74
0.611628
0.614695
0.2
0.52
0.74
0.602
0.921741
0.988372
0.903448
0.797674
430
558
0.670491
0.88541
0.924875
0.004462
0.05036
0.004461
0.050523
0.981111
0.988889
0.985556
null
0.593496
0.42
0.56
0.675
0.593496
0.59761
0.42
0.56
0.675
0.596
0.921741
0.99729
0.928549
0.813008
369
502
0.670491
0.88541
0.923511
0.001898
0.032537
0.001851
0.032218
1
1
0.978889
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.814815
0.693529
0
27
1
0.670491
0.88541
0.511644
0.004391
0.04811
0.004519
0.048927
0.682222
0.678889
0.992222
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.5
-0.362637
0
14
0
0.670491
0.88541
0.283651
0.002312
0.036607
0.002218
0.035854
0.945556
0.961111
0.407778
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.911765
0.683208
0
68
0
0.670491
0.88541
0.483375
0.005828
0.05383
0.005813
0.053886
0.557778
0.528889
0.816667
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.666667
0.185519
0
48
0
0.670491
0.88541
0.259018
0.004797
0.051779
0.00474
0.052
0.614444
0.666667
0.536667
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.533333
0.321429
0
15
1
0.670491
0.88541
0.048644
0.004306
0.049544
0.0043
0.049659
0.761111
0.806667
0.731111
null
0.020202
0.02
0.020202
0.020202
0.020202
0
0
0
0
0
0.921741
0.959596
0.837712
0.020202
99
3
0.670491
0.88541
0.720761
0.006265
0.059412
0.006352
0.05976
0.368889
0.437778
0.965556
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.972222
0.811769
0
108
3
0.670491
0.88541
0.677018
0.004451
0.049079
0.004556
0.049603
0.613333
0.623333
0.951111
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.7
0.479699
0
20
0
0.670491
0.88541
0.311357
0.001832
0.032126
0.001837
0.03237
0.972222
0.977778
0.741111
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.571429
0.163636
0
21
0
0.670491
0.88541
0.308379
0.006294
0.060212
0.006239
0.059789
0.494444
0.537778
0.616667
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.982759
0.821711
0
58
1
0.670491
0.88541
0.567534
0.004755
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0.004823
0.052146
0.647778
0.727778
0.944444
null
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0
0
0
0
0
0
0
0
0
0.921741
0.6
0.054545
0
10
0
0.670491
0.88541
0.33536
0.002087
0.035331
0.002074
0.035062
0.957778
0.973333
0.72
null
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0
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0
0
0
0
0
0
0.921741
0.5
0.221978
0
14
0
0.670491
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0.033904
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0.033397
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0.475556
null
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0
0
0
0
0
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0
0.921741
0.8125
0.05
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16
0
0.670491
0.88541
0.157324
0.002501
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0.923333
0.016667
null
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0
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0
0
0
0.921741
0.8
0.442857
0
15
0
0.670491
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0.005285
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null
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0.921741
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13
0
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0.91
0.933333
0.332222
null
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0
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0
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null
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31
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null
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0
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null
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0
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0.7
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null
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0.42
0.49
0.465
0.452722
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0.42
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0.465
0.444724
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0.670491
0.88541
0.714146
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null
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0.35
0.29
0.247934
0.356436
0.18
0.35
0.356436
0.356436
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0.913223
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242
101
0.670491
0.88541
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0.005135
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0.050857
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0.612222
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null
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0
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0
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0.038481
0.893333
0.898889
0.954444
null
0.473684
0.44
0.57
0.473684
0.473684
0.585714
0.44
0.57
0.585714
0.585714
0.921741
0.989474
0.922165
0.473684
190
140
0.670491
0.88541
0.833715
0.004833
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0.004865
0.052179
0.974444
0.992222
0.988889
null
0.219008
0.14
0.25
0.245
0.219008
0.185714
0.14
0.185714
0.185714
0.185714
0.921741
0.958678
0.831115
0.219008
242
70
0.670491
0.88541
0.827061
0.00492
0.050551
0.005047
0.05125
0.533333
0.617778
0.98
null
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0.4
0.59
0.675
0.659259
0.662679
0.4
0.59
0.675
0.662679
0.921741
0.97284
0.93706
0.683951
405
418
0.670491
0.88541
0.918116
0.00443
0.04754
0.004504
0.048124
0.995556
0.995556
1
null
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0.1
0.21
0.295
0.36
0.347328
0.1
0.21
0.295
0.347328
0.921741
0.961183
0.883127
0.345656
541
262
0.670491
0.88541
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0.012395
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0.012166
0.07603
0.167778
0.188889
1
null
0.631579
0.26
0.4
0.545
0.634
0.6298
0.26
0.4
0.545
0.634
0.921741
0.979626
0.910908
0.696095
589
651
0.670491
0.88541
0.922755
0.003841
0.043547
0.003615
0.042656
1
0.998889
1
null
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0.12
0.11
0.1
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0.151515
0.151515
0.151515
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0.95
0.905067
0.1
240
33
0.670491
0.88541
0.817356
0.007563
0.060586
0.007383
0.060277
0.335556
0.354444
0.993333
null
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0.22
0.28
0.44
0.442971
0.476351
0.22
0.28
0.44
0.476351
0.921741
0.944297
0.823488
0.442971
377
296
0.670491
0.88541
0.854222
0.008235
0.064348
0.008071
0.063711
0.747778
0.864444
0.995556
null
0
0
0
0
0
0
0
0
0
0
0.921741
0.619048
0.344156
0
21
1
0.670491
0.88541
0.520125
0.003697
0.045813
0.003531
0.044758
0.84
0.892222
0.778889
null
0.554502
0.24
0.51
0.62
0.554502
0.540643
0.24
0.51
0.62
0.542
0.921741
0.983412
0.932719
0.677725
422
529
0.670491
0.88541
0.889687
0.00853
0.066451
0.008217
0.065575
0.996667
0.996667
0.997778
null
0.445578
0.2
0.36
0.485
0.445578
0.478632
0.2
0.36
0.485
0.478632
0.921741
0.979592
0.876591
0.445578
294
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