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 8 new columns ({'year', 'Log GDP per capita', 'Healthy life expectancy at birth', 'Negative affect', 'Happiness score', 'Iso alpha', 'Country name', 'Positive affect'}) and 5 missing columns ({'Country or region', 'Healthy life expectancy', 'GDP per capita', 'Overall rank', 'Score'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Slapping/Happiness/WHR-1.csv (at revision b9481601cc4678da83c0032b0a38c826f9312104)
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
Country name: string
Iso alpha: string
year: int64
Happiness score: double
Log GDP per capita: double
Social support: double
Healthy life expectancy at birth: double
Freedom to make life choices: double
Generosity: double
Perceptions of corruption: double
Positive affect: double
Negative affect: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1862
to
{'Overall rank': Value(dtype='int64', id=None), 'Country or region': Value(dtype='string', id=None), 'Score': Value(dtype='float64', id=None), 'GDP per capita': Value(dtype='float64', id=None), 'Social support': Value(dtype='float64', id=None), 'Healthy life expectancy': Value(dtype='float64', id=None), 'Freedom to make life choices': Value(dtype='float64', id=None), 'Generosity': Value(dtype='float64', id=None), 'Perceptions of corruption': 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 8 new columns ({'year', 'Log GDP per capita', 'Healthy life expectancy at birth', 'Negative affect', 'Happiness score', 'Iso alpha', 'Country name', 'Positive affect'}) and 5 missing columns ({'Country or region', 'Healthy life expectancy', 'GDP per capita', 'Overall rank', 'Score'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Slapping/Happiness/WHR-1.csv (at revision b9481601cc4678da83c0032b0a38c826f9312104)
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.
Overall rank
int64 | Country or region
string | Score
float64 | GDP per capita
float64 | Social support
float64 | Healthy life expectancy
float64 | Freedom to make life choices
float64 | Generosity
float64 | Perceptions of corruption
float64 |
|---|---|---|---|---|---|---|---|---|
1
|
Finland
| 7.769
| 1.34
| 1.587
| 0.986
| 0.596
| 0.153
| 0.393
|
2
|
Denmark
| 7.6
| 1.383
| 1.573
| 0.996
| 0.592
| 0.252
| 0.41
|
3
|
Norway
| 7.554
| 1.488
| 1.582
| 1.028
| 0.603
| 0.271
| 0.341
|
4
|
Iceland
| 7.494
| 1.38
| 1.624
| 1.026
| 0.591
| 0.354
| 0.118
|
5
|
Netherlands
| 7.488
| 1.396
| 1.522
| 0.999
| 0.557
| 0.322
| 0.298
|
6
|
Switzerland
| 7.48
| 1.452
| 1.526
| 1.052
| 0.572
| 0.263
| 0.343
|
7
|
Sweden
| 7.343
| 1.387
| 1.487
| 1.009
| 0.574
| 0.267
| 0.373
|
8
|
New Zealand
| 7.307
| 1.303
| 1.557
| 1.026
| 0.585
| 0.33
| 0.38
|
9
|
Canada
| 7.278
| 1.365
| 1.505
| 1.039
| 0.584
| 0.285
| 0.308
|
10
|
Austria
| 7.246
| 1.376
| 1.475
| 1.016
| 0.532
| 0.244
| 0.226
|
11
|
Australia
| 7.228
| 1.372
| 1.548
| 1.036
| 0.557
| 0.332
| 0.29
|
12
|
Costa Rica
| 7.167
| 1.034
| 1.441
| 0.963
| 0.558
| 0.144
| 0.093
|
13
|
Israel
| 7.139
| 1.276
| 1.455
| 1.029
| 0.371
| 0.261
| 0.082
|
14
|
Luxembourg
| 7.09
| 1.609
| 1.479
| 1.012
| 0.526
| 0.194
| 0.316
|
15
|
United Kingdom
| 7.054
| 1.333
| 1.538
| 0.996
| 0.45
| 0.348
| 0.278
|
16
|
Ireland
| 7.021
| 1.499
| 1.553
| 0.999
| 0.516
| 0.298
| 0.31
|
17
|
Germany
| 6.985
| 1.373
| 1.454
| 0.987
| 0.495
| 0.261
| 0.265
|
18
|
Belgium
| 6.923
| 1.356
| 1.504
| 0.986
| 0.473
| 0.16
| 0.21
|
19
|
United States
| 6.892
| 1.433
| 1.457
| 0.874
| 0.454
| 0.28
| 0.128
|
20
|
Czech Republic
| 6.852
| 1.269
| 1.487
| 0.92
| 0.457
| 0.046
| 0.036
|
21
|
United Arab Emirates
| 6.825
| 1.503
| 1.31
| 0.825
| 0.598
| 0.262
| 0.182
|
22
|
Malta
| 6.726
| 1.3
| 1.52
| 0.999
| 0.564
| 0.375
| 0.151
|
23
|
Mexico
| 6.595
| 1.07
| 1.323
| 0.861
| 0.433
| 0.074
| 0.073
|
24
|
France
| 6.592
| 1.324
| 1.472
| 1.045
| 0.436
| 0.111
| 0.183
|
25
|
Taiwan
| 6.446
| 1.368
| 1.43
| 0.914
| 0.351
| 0.242
| 0.097
|
26
|
Chile
| 6.444
| 1.159
| 1.369
| 0.92
| 0.357
| 0.187
| 0.056
|
27
|
Guatemala
| 6.436
| 0.8
| 1.269
| 0.746
| 0.535
| 0.175
| 0.078
|
28
|
Saudi Arabia
| 6.375
| 1.403
| 1.357
| 0.795
| 0.439
| 0.08
| 0.132
|
29
|
Qatar
| 6.374
| 1.684
| 1.313
| 0.871
| 0.555
| 0.22
| 0.167
|
30
|
Spain
| 6.354
| 1.286
| 1.484
| 1.062
| 0.362
| 0.153
| 0.079
|
31
|
Panama
| 6.321
| 1.149
| 1.442
| 0.91
| 0.516
| 0.109
| 0.054
|
32
|
Brazil
| 6.3
| 1.004
| 1.439
| 0.802
| 0.39
| 0.099
| 0.086
|
33
|
Uruguay
| 6.293
| 1.124
| 1.465
| 0.891
| 0.523
| 0.127
| 0.15
|
34
|
Singapore
| 6.262
| 1.572
| 1.463
| 1.141
| 0.556
| 0.271
| 0.453
|
35
|
El Salvador
| 6.253
| 0.794
| 1.242
| 0.789
| 0.43
| 0.093
| 0.074
|
36
|
Italy
| 6.223
| 1.294
| 1.488
| 1.039
| 0.231
| 0.158
| 0.03
|
37
|
Bahrain
| 6.199
| 1.362
| 1.368
| 0.871
| 0.536
| 0.255
| 0.11
|
38
|
Slovakia
| 6.198
| 1.246
| 1.504
| 0.881
| 0.334
| 0.121
| 0.014
|
39
|
Trinidad & Tobago
| 6.192
| 1.231
| 1.477
| 0.713
| 0.489
| 0.185
| 0.016
|
40
|
Poland
| 6.182
| 1.206
| 1.438
| 0.884
| 0.483
| 0.117
| 0.05
|
41
|
Uzbekistan
| 6.174
| 0.745
| 1.529
| 0.756
| 0.631
| 0.322
| 0.24
|
42
|
Lithuania
| 6.149
| 1.238
| 1.515
| 0.818
| 0.291
| 0.043
| 0.042
|
43
|
Colombia
| 6.125
| 0.985
| 1.41
| 0.841
| 0.47
| 0.099
| 0.034
|
44
|
Slovenia
| 6.118
| 1.258
| 1.523
| 0.953
| 0.564
| 0.144
| 0.057
|
45
|
Nicaragua
| 6.105
| 0.694
| 1.325
| 0.835
| 0.435
| 0.2
| 0.127
|
46
|
Kosovo
| 6.1
| 0.882
| 1.232
| 0.758
| 0.489
| 0.262
| 0.006
|
47
|
Argentina
| 6.086
| 1.092
| 1.432
| 0.881
| 0.471
| 0.066
| 0.05
|
48
|
Romania
| 6.07
| 1.162
| 1.232
| 0.825
| 0.462
| 0.083
| 0.005
|
49
|
Cyprus
| 6.046
| 1.263
| 1.223
| 1.042
| 0.406
| 0.19
| 0.041
|
50
|
Ecuador
| 6.028
| 0.912
| 1.312
| 0.868
| 0.498
| 0.126
| 0.087
|
51
|
Kuwait
| 6.021
| 1.5
| 1.319
| 0.808
| 0.493
| 0.142
| 0.097
|
52
|
Thailand
| 6.008
| 1.05
| 1.409
| 0.828
| 0.557
| 0.359
| 0.028
|
53
|
Latvia
| 5.94
| 1.187
| 1.465
| 0.812
| 0.264
| 0.075
| 0.064
|
54
|
South Korea
| 5.895
| 1.301
| 1.219
| 1.036
| 0.159
| 0.175
| 0.056
|
55
|
Estonia
| 5.893
| 1.237
| 1.528
| 0.874
| 0.495
| 0.103
| 0.161
|
56
|
Jamaica
| 5.89
| 0.831
| 1.478
| 0.831
| 0.49
| 0.107
| 0.028
|
57
|
Mauritius
| 5.888
| 1.12
| 1.402
| 0.798
| 0.498
| 0.215
| 0.06
|
58
|
Japan
| 5.886
| 1.327
| 1.419
| 1.088
| 0.445
| 0.069
| 0.14
|
59
|
Honduras
| 5.86
| 0.642
| 1.236
| 0.828
| 0.507
| 0.246
| 0.078
|
60
|
Kazakhstan
| 5.809
| 1.173
| 1.508
| 0.729
| 0.41
| 0.146
| 0.096
|
61
|
Bolivia
| 5.779
| 0.776
| 1.209
| 0.706
| 0.511
| 0.137
| 0.064
|
62
|
Hungary
| 5.758
| 1.201
| 1.41
| 0.828
| 0.199
| 0.081
| 0.02
|
63
|
Paraguay
| 5.743
| 0.855
| 1.475
| 0.777
| 0.514
| 0.184
| 0.08
|
64
|
Northern Cyprus
| 5.718
| 1.263
| 1.252
| 1.042
| 0.417
| 0.191
| 0.162
|
65
|
Peru
| 5.697
| 0.96
| 1.274
| 0.854
| 0.455
| 0.083
| 0.027
|
66
|
Portugal
| 5.693
| 1.221
| 1.431
| 0.999
| 0.508
| 0.047
| 0.025
|
67
|
Pakistan
| 5.653
| 0.677
| 0.886
| 0.535
| 0.313
| 0.22
| 0.098
|
68
|
Russia
| 5.648
| 1.183
| 1.452
| 0.726
| 0.334
| 0.082
| 0.031
|
69
|
Philippines
| 5.631
| 0.807
| 1.293
| 0.657
| 0.558
| 0.117
| 0.107
|
70
|
Serbia
| 5.603
| 1.004
| 1.383
| 0.854
| 0.282
| 0.137
| 0.039
|
71
|
Moldova
| 5.529
| 0.685
| 1.328
| 0.739
| 0.245
| 0.181
| 0
|
72
|
Libya
| 5.525
| 1.044
| 1.303
| 0.673
| 0.416
| 0.133
| 0.152
|
73
|
Montenegro
| 5.523
| 1.051
| 1.361
| 0.871
| 0.197
| 0.142
| 0.08
|
74
|
Tajikistan
| 5.467
| 0.493
| 1.098
| 0.718
| 0.389
| 0.23
| 0.144
|
75
|
Croatia
| 5.432
| 1.155
| 1.266
| 0.914
| 0.296
| 0.119
| 0.022
|
76
|
Hong Kong
| 5.43
| 1.438
| 1.277
| 1.122
| 0.44
| 0.258
| 0.287
|
77
|
Dominican Republic
| 5.425
| 1.015
| 1.401
| 0.779
| 0.497
| 0.113
| 0.101
|
78
|
Bosnia and Herzegovina
| 5.386
| 0.945
| 1.212
| 0.845
| 0.212
| 0.263
| 0.006
|
79
|
Turkey
| 5.373
| 1.183
| 1.36
| 0.808
| 0.195
| 0.083
| 0.106
|
80
|
Malaysia
| 5.339
| 1.221
| 1.171
| 0.828
| 0.508
| 0.26
| 0.024
|
81
|
Belarus
| 5.323
| 1.067
| 1.465
| 0.789
| 0.235
| 0.094
| 0.142
|
82
|
Greece
| 5.287
| 1.181
| 1.156
| 0.999
| 0.067
| 0
| 0.034
|
83
|
Mongolia
| 5.285
| 0.948
| 1.531
| 0.667
| 0.317
| 0.235
| 0.038
|
84
|
North Macedonia
| 5.274
| 0.983
| 1.294
| 0.838
| 0.345
| 0.185
| 0.034
|
85
|
Nigeria
| 5.265
| 0.696
| 1.111
| 0.245
| 0.426
| 0.215
| 0.041
|
86
|
Kyrgyzstan
| 5.261
| 0.551
| 1.438
| 0.723
| 0.508
| 0.3
| 0.023
|
87
|
Turkmenistan
| 5.247
| 1.052
| 1.538
| 0.657
| 0.394
| 0.244
| 0.028
|
88
|
Algeria
| 5.211
| 1.002
| 1.16
| 0.785
| 0.086
| 0.073
| 0.114
|
89
|
Morocco
| 5.208
| 0.801
| 0.782
| 0.782
| 0.418
| 0.036
| 0.076
|
90
|
Azerbaijan
| 5.208
| 1.043
| 1.147
| 0.769
| 0.351
| 0.035
| 0.182
|
91
|
Lebanon
| 5.197
| 0.987
| 1.224
| 0.815
| 0.216
| 0.166
| 0.027
|
92
|
Indonesia
| 5.192
| 0.931
| 1.203
| 0.66
| 0.491
| 0.498
| 0.028
|
93
|
China
| 5.191
| 1.029
| 1.125
| 0.893
| 0.521
| 0.058
| 0.1
|
94
|
Vietnam
| 5.175
| 0.741
| 1.346
| 0.851
| 0.543
| 0.147
| 0.073
|
95
|
Bhutan
| 5.082
| 0.813
| 1.321
| 0.604
| 0.457
| 0.37
| 0.167
|
96
|
Cameroon
| 5.044
| 0.549
| 0.91
| 0.331
| 0.381
| 0.187
| 0.037
|
97
|
Bulgaria
| 5.011
| 1.092
| 1.513
| 0.815
| 0.311
| 0.081
| 0.004
|
98
|
Ghana
| 4.996
| 0.611
| 0.868
| 0.486
| 0.381
| 0.245
| 0.04
|
99
|
Ivory Coast
| 4.944
| 0.569
| 0.808
| 0.232
| 0.352
| 0.154
| 0.09
|
100
|
Nepal
| 4.913
| 0.446
| 1.226
| 0.677
| 0.439
| 0.285
| 0.089
|
End of preview.