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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 ({'Downloaded from wid.world on 04-12-2024 at 21:30:24'}) and 1 missing columns ({'Downloaded from wid.world on 04-12-2024 at 21:31:11'}). This happened while the csv dataset builder was generating data using hf://datasets/Rongxi-Situ/final-project-espm157/carbon10.csv (at revision bfdbac5c3b0585b39b4fe5a91db505ed923691a5) 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 1870, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 Downloaded from wid.world on 04-12-2024 at 21:30:24: string -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 463 to {'Downloaded from wid.world on 04-12-2024 at 21:31:11': Value(dtype='string', 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 1417, 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 1049, 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 1000, 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 1741, 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 1872, 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 ({'Downloaded from wid.world on 04-12-2024 at 21:30:24'}) and 1 missing columns ({'Downloaded from wid.world on 04-12-2024 at 21:31:11'}). This happened while the csv dataset builder was generating data using hf://datasets/Rongxi-Situ/final-project-espm157/carbon10.csv (at revision bfdbac5c3b0585b39b4fe5a91db505ed923691a5) 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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Downloaded from wid.world on 04-12-2024 at 21:31:11
string |
---|
Country ;Percentile ;"lpfghg_999_i_2019 |
Personal carbon footprint (all sectors) |
Top 1% | Average per capita group emissions | all ages | individual | | ppp | constant (2023) |
2019" |
country;percentile;carbon1value |
Afghanistan;p99p100;9.4152756 |
Albania;p99p100;29.836241 |
Algeria;p99p100;17.034573 |
Angola;p99p100;21.448517 |
Argentina;p99p100;51.490891 |
Armenia;p99p100;28.852394 |
Australia;p99p100;180.54671 |
Austria;p99p100;107.82352 |
Azerbaijan;p99p100;40.699203 |
Bahamas;p99p100;90.249382 |
Bahrain;p99p100;141.04196 |
Bangladesh;p99p100;11.737609 |
Belarus;p99p100;36.859367 |
Belgium;p99p100;108.89626 |
Belize;p99p100;34.863289 |
Benin;p99p100;10.997051 |
Bhutan;p99p100;34.194656 |
Bolivia;p99p100;52.916824 |
Bosnia and Herzegovina;p99p100;37.950626 |
Botswana;p99p100;134.80569 |
Brazil;p99p100;49.694252 |
Brunei Darussalam;p99p100;55.963219 |
Bulgaria;p99p100;57.908772 |
Burkina Faso;p99p100;13.189 |
Burundi;p99p100;5.0122037 |
Cabo Verde;p99p100;21.458847 |
Cambodia;p99p100;27.882879 |
Cameroon;p99p100;10.344449 |
Canada;p99p100;218.41786 |
Central African Republic;p99p100;18.679415 |
Chad;p99p100;20.126135 |
Chile;p99p100;84.611053 |
China;p99p100;133.69409 |
Colombia;p99p100;36.687553 |
Congo;p99p100;28.739618 |
Costa Rica;p99p100;37.764275 |
Cote d’Ivoire;p99p100;8.1330786 |
Croatia;p99p100;39.065357 |
Cuba;p99p100;23.443777 |
Cyprus;p99p100;100.60763 |
Czech Republic;p99p100;82.250282 |
DR Congo;p99p100;5.0049086 |
Denmark;p99p100;97.483162 |
Djibouti;p99p100;15.306952 |
Dominican Republic;p99p100;46.0868 |
Ecuador;p99p100;27.790155 |
Egypt;p99p100;25.431219 |
El Salvador;p99p100;10.652072 |
Eritrea;p99p100;10.692892 |
Estonia;p99p100;139.78195 |
Ethiopia;p99p100;1.2883829 |
Finland;p99p100;95.57312 |
France;p99p100;65.086761 |
Gabon;p99p100;26.967974 |
Gambia;p99p100;6.232821 |
Georgia;p99p100;59.061081 |
Germany;p99p100;108.65565 |
Ghana;p99p100;8.1029224 |
Greece;p99p100;49.102459 |
Guatemala;p99p100;20.336243 |
Guinea;p99p100;9.8068657 |
Guyana;p99p100;56.131634 |
Haiti;p99p100;12.482513 |
Honduras;p99p100;23.063637 |
Hong Kong;p99p100;266.10776 |
Hungary;p99p100;78.447678 |
Iceland;p99p100;109.91031 |
India;p99p100;31.70841 |
Indonesia;p99p100;38.717907 |
Iran;p99p100;128.48314 |
Iraq;p99p100;59.209053 |
Ireland;p99p100;81.487221 |
Israel;p99p100;112.3671 |
Italy;p99p100;61.10223 |
Jamaica;p99p100;36.042473 |
Japan;p99p100;103.93093 |
Jordan;p99p100;35.133915 |
Kazakhstan;p99p100;145.49635 |
Kenya;p99p100;10.768522 |
Korea;p99p100;168.78526 |
Kuwait;p99p100;263.38043 |
Kyrgyzstan;p99p100;45.969021 |
Lao PDR;p99p100;73.557304 |
Latvia;p99p100;74.840416 |
Lebanon;p99p100;50.153271 |
Lesotho;p99p100;25.099142 |
Liberia;p99p100;2.4574718 |
Libya;p99p100;19.52408 |
Lithuania;p99p100;71.980438 |
Luxembourg;p99p100;315.05017 |
Macao;p99p100;132.05154 |
Madagascar;p99p100;8.36413 |
Malawi;p99p100;6.9961886 |
Malaysia;p99p100;93.00779 |
Maldives;p99p100;30.655561 |
End of preview.
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