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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 ({'failed'}) and 34 missing columns ({'health', 'total_support', 'address', 'studytime', 'Mjob', 'schoolsup', 'romantic', 'freetime', 'famrel', 'school', 'total_alcohol', 'traveltime', 'Walc', 'Fedu', 'absences', 'Dalc', 'famsup', 'age', 'reason', 'guardian', 'Fjob', 'internet', 'higher', 'famsize', 'paid', 'parent_edu_mean', 'sex', 'Medu', 'activities', 'high_risk', 'nursery', 'goout', 'failures', 'Pstatus'}).
This happened while the csv dataset builder was generating data using
hf://datasets/justin-kelem/student-dropout-prediction/y_train.csv (at revision 6e153c723553e52d58e9357c2e8cde81d9645b1d), ['hf://datasets/justin-kelem/student-dropout-prediction@6e153c723553e52d58e9357c2e8cde81d9645b1d/X_train.csv', 'hf://datasets/justin-kelem/student-dropout-prediction@6e153c723553e52d58e9357c2e8cde81d9645b1d/y_train.csv']
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
failed: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 370
to
{'school': Value('int64'), 'sex': Value('int64'), 'age': Value('float64'), 'address': Value('int64'), 'famsize': Value('int64'), 'Pstatus': Value('int64'), 'Medu': Value('float64'), 'Fedu': Value('float64'), 'Mjob': Value('int64'), 'Fjob': Value('int64'), 'reason': Value('int64'), 'guardian': Value('int64'), 'traveltime': Value('float64'), 'studytime': Value('float64'), 'failures': Value('float64'), 'schoolsup': Value('int64'), 'famsup': Value('int64'), 'paid': Value('int64'), 'activities': Value('int64'), 'nursery': Value('int64'), 'higher': Value('int64'), 'internet': Value('int64'), 'romantic': Value('int64'), 'famrel': Value('float64'), 'freetime': Value('float64'), 'goout': Value('float64'), 'Dalc': Value('float64'), 'Walc': Value('float64'), 'health': Value('float64'), 'absences': Value('float64'), 'parent_edu_mean': Value('float64'), 'total_alcohol': Value('float64'), 'high_risk': Value('float64'), 'total_support': 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 1361, 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 940, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1839, 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 ({'failed'}) and 34 missing columns ({'health', 'total_support', 'address', 'studytime', 'Mjob', 'schoolsup', 'romantic', 'freetime', 'famrel', 'school', 'total_alcohol', 'traveltime', 'Walc', 'Fedu', 'absences', 'Dalc', 'famsup', 'age', 'reason', 'guardian', 'Fjob', 'internet', 'higher', 'famsize', 'paid', 'parent_edu_mean', 'sex', 'Medu', 'activities', 'high_risk', 'nursery', 'goout', 'failures', 'Pstatus'}).
This happened while the csv dataset builder was generating data using
hf://datasets/justin-kelem/student-dropout-prediction/y_train.csv (at revision 6e153c723553e52d58e9357c2e8cde81d9645b1d), ['hf://datasets/justin-kelem/student-dropout-prediction@6e153c723553e52d58e9357c2e8cde81d9645b1d/X_train.csv', 'hf://datasets/justin-kelem/student-dropout-prediction@6e153c723553e52d58e9357c2e8cde81d9645b1d/y_train.csv']
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.
school int64 | sex int64 | age float64 | address int64 | famsize int64 | Pstatus int64 | Medu float64 | Fedu float64 | Mjob int64 | Fjob int64 | reason int64 | guardian int64 | traveltime float64 | studytime float64 | failures float64 | schoolsup int64 | famsup int64 | paid int64 | activities int64 | nursery int64 | higher int64 | internet int64 | romantic int64 | famrel float64 | freetime float64 | goout float64 | Dalc float64 | Walc float64 | health float64 | absences float64 | parent_edu_mean float64 | total_alcohol float64 | high_risk float64 | total_support float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 1 | -0.529411 | 1 | 0 | 1 | 1.169153 | 1.333832 | 3 | 4 | 2 | 0 | -0.635701 | 1.20293 | -0.446388 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0.017757 | 0.705163 | -0.102461 | -0.527952 | -1.004242 | 0.338061 | -0.758644 | 1.390799 | -0.892956 | -0.280175 | 0.399313 |
0 | 0 | -0.529411 | 1 | 0 | 1 | 1.169153 | 0.417547 | 4 | 1 | 1 | 1 | -0.635701 | 1.20293 | -0.446388 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | -1.104456 | 0.705163 | 0.77261 | 0.599297 | 1.300895 | 0.338061 | -0.492276 | 0.87857 | 1.11898 | -0.280175 | 2.017041 |
0 | 1 | -0.529411 | 1 | 0 | 1 | -0.687391 | -1.415022 | 2 | 2 | 0 | 1 | 2.154321 | -1.210568 | -0.446388 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0.017757 | -0.276474 | -0.102461 | -0.527952 | -1.004242 | 0.338061 | 0.040461 | -1.170346 | -0.892956 | -0.280175 | -1.218416 |
0 | 0 | -0.529411 | 1 | 0 | 1 | -0.687391 | -0.498737 | 0 | 2 | 1 | 1 | -0.635701 | -0.003819 | 0.884354 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | -1.104456 | -2.239746 | -0.977532 | -0.527952 | -1.004242 | 1.055024 | 0.040461 | -0.658117 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | -1.311158 | 1 | 1 | 0 | 0.240881 | -0.498737 | 3 | 2 | 1 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0.017757 | -1.25811 | -0.977532 | -0.527952 | -1.004242 | -1.812826 | -0.758644 | -0.145888 | -0.892956 | -0.280175 | 0.399313 |
0 | 0 | -1.311158 | 1 | 0 | 1 | 1.169153 | 1.333832 | 3 | 3 | 0 | 1 | -0.635701 | -1.210568 | -0.446388 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | -1.104456 | -0.276474 | 0.77261 | 0.599297 | 0.532516 | 1.055024 | -0.758644 | 1.390799 | 0.615996 | -0.280175 | 2.017041 |
0 | 1 | -0.529411 | 1 | 0 | 1 | 1.169153 | 0.417547 | 4 | 2 | 1 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | -1.104456 | 0.705163 | -0.102461 | 0.599297 | 0.532516 | -0.378901 | 0.573198 | 0.87857 | 0.615996 | -0.280175 | 0.399313 |
0 | 0 | 1.034083 | 1 | 0 | 1 | -0.687391 | -1.415022 | 2 | 2 | 0 | 2 | 0.75931 | 1.20293 | -0.446388 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 0.017757 | 0.705163 | 0.77261 | -0.527952 | -1.004242 | -0.378901 | -0.758644 | -1.170346 | -0.892956 | -0.280175 | 0.399313 |
1 | 1 | 1.034083 | 1 | 1 | 1 | -1.615664 | 0.417547 | 0 | 3 | 0 | 1 | -0.635701 | -1.210568 | 0.884354 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0.017757 | -0.276474 | -0.102461 | 0.599297 | 0.532516 | -0.378901 | 0.173645 | -0.658117 | 0.615996 | -0.280175 | -1.218416 |
0 | 0 | 0.252336 | 1 | 0 | 1 | -1.615664 | -1.415022 | 0 | 2 | 3 | 1 | -0.635701 | 1.20293 | 0.884354 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0.017757 | -0.276474 | 0.77261 | -0.527952 | -1.004242 | 1.055024 | -0.758644 | -1.682575 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | 1.034083 | 1 | 1 | 1 | 0.240881 | 0.417547 | 3 | 1 | 1 | 0 | -0.635701 | -0.003819 | 0.884354 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | -1.104456 | -1.25811 | 0.77261 | 0.599297 | 1.300895 | 0.338061 | 0.97275 | 0.366341 | 1.11898 | 3.569192 | 0.399313 |
0 | 1 | -0.529411 | 1 | 0 | 1 | -0.687391 | 0.417547 | 2 | 2 | 1 | 0 | 0.75931 | -1.210568 | -0.446388 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1.139969 | -0.276474 | -0.102461 | -0.527952 | -1.004242 | -0.378901 | -0.758644 | -0.145888 | -0.892956 | -0.280175 | -1.218416 |
0 | 1 | 0.252336 | 1 | 1 | 1 | -1.615664 | -1.415022 | 1 | 2 | 0 | 1 | 0.75931 | -1.210568 | 0.884354 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0.017757 | 0.705163 | 0.77261 | -0.527952 | -0.235863 | 1.055024 | -0.492276 | -1.682575 | -0.389972 | -0.280175 | 0.399313 |
1 | 0 | 1.034083 | 0 | 0 | 1 | -0.687391 | -0.498737 | 0 | 2 | 2 | 1 | 0.75931 | 1.20293 | -0.446388 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1.139969 | -0.276474 | -0.102461 | -0.527952 | 0.532516 | 0.338061 | -0.492276 | -0.658117 | 0.113012 | -0.280175 | -1.218416 |
0 | 1 | 1.815831 | 1 | 0 | 1 | 0.240881 | 0.417547 | 2 | 2 | 1 | 2 | -0.635701 | -0.003819 | 0.884354 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0.017757 | 0.705163 | 0.77261 | -0.527952 | -1.004242 | -0.378901 | 1.90504 | 0.366341 | -0.892956 | 3.569192 | 0.399313 |
0 | 1 | 0.252336 | 1 | 0 | 1 | 1.169153 | 1.333832 | 4 | 4 | 3 | 1 | -0.635701 | -0.003819 | -0.446388 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0.017757 | 1.686799 | 1.647681 | -0.527952 | 0.532516 | -1.095864 | 1.105934 | 1.390799 | 0.113012 | -0.280175 | 2.017041 |
0 | 1 | -0.529411 | 1 | 1 | 1 | 1.169153 | -0.498737 | 4 | 2 | 0 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0.017757 | 1.686799 | -1.852603 | -0.527952 | 0.532516 | 1.055024 | -0.492276 | 0.366341 | 0.113012 | -0.280175 | -1.218416 |
0 | 1 | -0.529411 | 1 | 1 | 1 | -0.687391 | -0.498737 | 2 | 2 | 3 | 1 | 0.75931 | -0.003819 | -0.446388 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1.139969 | 0.705163 | 0.77261 | 0.599297 | 1.300895 | 1.055024 | -0.758644 | -0.658117 | 1.11898 | -0.280175 | 0.399313 |
0 | 0 | -0.529411 | 1 | 1 | 1 | -1.615664 | -0.498737 | 2 | 3 | 3 | 0 | -0.635701 | -0.003819 | -0.446388 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0.017757 | 0.705163 | -0.102461 | -0.527952 | -1.004242 | -1.812826 | -0.225907 | -1.170346 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | -0.529411 | 1 | 0 | 1 | 1.169153 | 1.333832 | 4 | 4 | 0 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | -1.104456 | -0.276474 | -0.977532 | 0.599297 | -1.004242 | 1.055024 | -0.758644 | 1.390799 | -0.389972 | -0.280175 | 0.399313 |
0 | 0 | -0.529411 | 0 | 0 | 1 | 0.240881 | 0.417547 | 3 | 2 | 3 | 0 | -0.635701 | 1.20293 | 0.884354 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0.017757 | -2.239746 | -0.977532 | -0.527952 | -1.004242 | -1.095864 | -0.758644 | 0.366341 | -0.892956 | -0.280175 | 2.017041 |
0 | 1 | 1.034083 | 0 | 1 | 1 | 0.240881 | -0.498737 | 3 | 2 | 3 | 1 | 0.75931 | 1.20293 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1.139969 | 0.705163 | -0.977532 | -0.527952 | -1.004242 | 0.338061 | 0.306829 | -0.145888 | -0.892956 | -0.280175 | 0.399313 |
0 | 0 | -1.311158 | 1 | 0 | 1 | 1.169153 | 1.333832 | 3 | 4 | 2 | 0 | -0.635701 | -0.003819 | 0.884354 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 0.017757 | 0.705163 | 0.77261 | -0.527952 | -1.004242 | -0.378901 | -0.492276 | 1.390799 | -0.892956 | -0.280175 | 2.017041 |
0 | 1 | -1.311158 | 1 | 0 | 1 | 1.169153 | 1.333832 | 1 | 3 | 1 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 1.139969 | 0.705163 | -0.977532 | 1.726547 | 1.300895 | 1.055024 | -0.758644 | 1.390799 | 1.621964 | -0.280175 | 0.399313 |
0 | 0 | -0.529411 | 1 | 1 | 1 | 0.240881 | 0.417547 | 2 | 2 | 3 | 1 | 0.75931 | -0.003819 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0.017757 | 0.705163 | 1.647681 | -0.527952 | -1.004242 | 0.338061 | -0.225907 | 0.366341 | -0.892956 | -0.280175 | 0.399313 |
0 | 0 | 1.034083 | 1 | 0 | 1 | -0.687391 | 0.417547 | 0 | 2 | 0 | 1 | -0.635701 | 1.20293 | -0.446388 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0.017757 | -0.276474 | -0.102461 | -0.527952 | -0.235863 | -0.378901 | -0.225907 | -0.145888 | -0.389972 | -0.280175 | 0.399313 |
0 | 1 | -0.529411 | 1 | 0 | 1 | 0.240881 | 0.417547 | 0 | 2 | 3 | 2 | 2.154321 | -0.003819 | -0.446388 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 1.139969 | -0.276474 | -0.102461 | -0.527952 | 0.532516 | -1.095864 | 0.040461 | 0.366341 | 0.113012 | -0.280175 | 2.017041 |
0 | 0 | 0.252336 | 1 | 0 | 1 | 0.240881 | 1.333832 | 0 | 3 | 1 | 1 | -0.635701 | 1.20293 | 0.884354 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0.017757 | 0.705163 | -0.102461 | 1.726547 | 1.300895 | 1.055024 | 2.970513 | 0.87857 | 1.621964 | 3.569192 | 0.399313 |
0 | 0 | -0.529411 | 1 | 0 | 1 | -0.687391 | -0.498737 | 3 | 3 | 1 | 1 | -0.635701 | -1.210568 | 2.215095 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | -3.348881 | -1.25811 | -0.977532 | -0.527952 | 0.532516 | 1.055024 | 1.105934 | -0.658117 | 0.113012 | 3.569192 | 0.399313 |
0 | 1 | 1.034083 | 1 | 0 | 1 | 1.169153 | 1.333832 | 4 | 3 | 1 | 1 | 0.75931 | -1.210568 | -0.446388 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | -1.104456 | -1.25811 | 0.77261 | -0.527952 | 1.300895 | -0.378901 | 2.171408 | 1.390799 | 0.615996 | -0.280175 | -1.218416 |
0 | 1 | -1.311158 | 1 | 0 | 1 | 0.240881 | 1.333832 | 2 | 2 | 1 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1.139969 | 1.686799 | -1.852603 | -0.527952 | -1.004242 | 1.055024 | -0.758644 | 0.87857 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | 4.161072 | 1 | 0 | 1 | 0.240881 | -1.415022 | 3 | 3 | 2 | 1 | -0.635701 | -1.210568 | 3.545837 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1.139969 | 0.705163 | 1.647681 | 3.981045 | 2.069274 | -1.812826 | 1.372303 | -0.658117 | 3.130916 | 3.569192 | -1.218416 |
0 | 1 | 1.815831 | 1 | 0 | 1 | 0.240881 | -0.498737 | 3 | 0 | 1 | 1 | -0.635701 | -1.210568 | 3.545837 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0.017757 | 1.686799 | 0.77261 | -0.527952 | -1.004242 | 0.338061 | -0.758644 | -0.145888 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | 0.252336 | 0 | 1 | 1 | -1.615664 | -0.498737 | 2 | 2 | 3 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | -2.226669 | -1.25811 | -0.977532 | 1.726547 | 0.532516 | 1.055024 | 0.306829 | -1.170346 | 1.11898 | -0.280175 | -1.218416 |
0 | 1 | 1.815831 | 1 | 0 | 1 | -1.615664 | -0.498737 | 2 | 3 | 0 | 2 | -0.635701 | -0.003819 | 0.884354 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0.017757 | 1.686799 | -0.977532 | 0.599297 | -0.235863 | 0.338061 | -0.359092 | -1.170346 | 0.113012 | -0.280175 | -1.218416 |
0 | 1 | 1.034083 | 1 | 0 | 1 | 1.169153 | 0.417547 | 4 | 2 | 0 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0.017757 | -0.276474 | -0.977532 | -0.527952 | -1.004242 | -0.378901 | -0.492276 | 0.87857 | -0.892956 | -0.280175 | 0.399313 |
0 | 0 | 0.252336 | 0 | 0 | 1 | 0.240881 | 1.333832 | 0 | 3 | 0 | 0 | -0.635701 | 1.20293 | -0.446388 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 0.017757 | -0.276474 | 0.77261 | 0.599297 | 2.069274 | 1.055024 | -0.758644 | 0.87857 | 1.621964 | -0.280175 | 0.399313 |
0 | 0 | -0.529411 | 1 | 1 | 1 | 1.169153 | 1.333832 | 4 | 4 | 3 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0.017757 | 1.686799 | -0.977532 | -0.527952 | -0.235863 | -0.378901 | -0.758644 | 1.390799 | -0.389972 | -0.280175 | 0.399313 |
0 | 0 | 1.034083 | 1 | 0 | 1 | -0.687391 | 0.417547 | 2 | 3 | 3 | 0 | -0.635701 | 2.409679 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0.017757 | 1.686799 | 1.647681 | -0.527952 | 0.532516 | -1.095864 | -0.225907 | -0.145888 | 0.113012 | -0.280175 | 0.399313 |
0 | 1 | -1.311158 | 1 | 1 | 0 | 1.169153 | -0.498737 | 1 | 1 | 2 | 0 | 0.75931 | -1.210568 | 0.884354 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1.139969 | 1.686799 | 1.647681 | 1.726547 | 1.300895 | 1.055024 | 0.040461 | 0.366341 | 1.621964 | -0.280175 | -1.218416 |
0 | 0 | -0.529411 | 1 | 0 | 1 | 1.169153 | 0.417547 | 4 | 2 | 2 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | -3.348881 | -0.276474 | -0.977532 | -0.527952 | -1.004242 | -1.812826 | 0.573198 | 0.87857 | -0.892956 | -0.280175 | -1.218416 |
0 | 1 | -1.311158 | 1 | 0 | 1 | 1.169153 | 1.333832 | 3 | 2 | 0 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 1.139969 | -0.276474 | -0.102461 | -0.527952 | -1.004242 | 1.055024 | -0.225907 | 1.390799 | -0.892956 | -0.280175 | 0.399313 |
1 | 0 | 1.034083 | 0 | 1 | 1 | 1.169153 | 1.333832 | 4 | 3 | 0 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 1.139969 | 0.705163 | -0.102461 | 1.726547 | 1.300895 | -1.095864 | -0.225907 | 1.390799 | 1.621964 | -0.280175 | -1.218416 |
0 | 1 | 0.252336 | 1 | 1 | 1 | 1.169153 | 1.333832 | 2 | 4 | 1 | 0 | 0.75931 | -1.210568 | -0.446388 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0.017757 | -2.239746 | -1.852603 | 0.599297 | -0.235863 | 1.055024 | -0.758644 | 1.390799 | 0.113012 | -0.280175 | -1.218416 |
0 | 0 | 1.034083 | 0 | 0 | 1 | 1.169153 | 1.333832 | 4 | 2 | 3 | 1 | 0.75931 | -0.003819 | -0.446388 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0.017757 | -0.276474 | 0.77261 | 0.599297 | -0.235863 | 0.338061 | 0.306829 | 1.390799 | 0.113012 | -0.280175 | -1.218416 |
0 | 1 | -1.311158 | 1 | 1 | 1 | -0.687391 | -0.498737 | 3 | 3 | 1 | 1 | 0.75931 | -0.003819 | -0.446388 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 1.139969 | -0.276474 | -0.102461 | -0.527952 | 0.532516 | 0.338061 | -0.225907 | -0.658117 | 0.113012 | -0.280175 | -1.218416 |
0 | 0 | -1.311158 | 1 | 1 | 0 | 1.169153 | 0.417547 | 2 | 2 | 0 | 1 | -0.635701 | -0.003819 | -0.446388 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1.139969 | -1.25811 | -0.977532 | -0.527952 | -1.004242 | 1.055024 | 0.306829 | 0.87857 | -0.892956 | -0.280175 | 2.017041 |
0 | 0 | -1.311158 | 1 | 0 | 1 | -1.615664 | -1.415022 | 2 | 2 | 1 | 0 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 0.017757 | -0.276474 | -0.977532 | 0.599297 | 0.532516 | 0.338061 | -0.492276 | -1.682575 | 0.615996 | -0.280175 | 0.399313 |
0 | 1 | -0.529411 | 1 | 0 | 1 | -0.687391 | -0.498737 | 3 | 2 | 3 | 0 | 0.75931 | -0.003819 | 0.884354 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 0.017757 | 0.705163 | -0.977532 | -0.527952 | -1.004242 | -0.378901 | 0.839566 | -0.658117 | -0.892956 | 3.569192 | -1.218416 |
0 | 0 | 0.252336 | 0 | 1 | 1 | 1.169153 | 1.333832 | 3 | 2 | 2 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 1.139969 | -1.25811 | -1.852603 | -0.527952 | -0.235863 | -0.378901 | 0.839566 | 1.390799 | -0.389972 | -0.280175 | 0.399313 |
0 | 0 | 1.034083 | 1 | 1 | 1 | 0.240881 | 0.417547 | 3 | 3 | 1 | 1 | -0.635701 | 2.409679 | -0.446388 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 1.139969 | -0.276474 | -0.102461 | -0.527952 | -1.004242 | -1.812826 | 0.173645 | 0.366341 | -0.892956 | -0.280175 | 0.399313 |
0 | 0 | 0.252336 | 1 | 0 | 1 | -1.615664 | -1.415022 | 2 | 2 | 0 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0.017757 | 0.705163 | 0.77261 | -0.527952 | 0.532516 | -1.812826 | -0.225907 | -1.682575 | 0.113012 | -0.280175 | 0.399313 |
0 | 0 | 0.252336 | 0 | 0 | 1 | 1.169153 | 0.417547 | 4 | 2 | 3 | 1 | 0.75931 | 1.20293 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0.017757 | 0.705163 | -0.977532 | -0.527952 | -1.004242 | 0.338061 | 0.040461 | 0.87857 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | -1.311158 | 1 | 0 | 1 | -0.687391 | -0.498737 | 3 | 3 | 1 | 0 | -0.635701 | 2.409679 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1.139969 | 1.686799 | 0.77261 | -0.527952 | -0.235863 | 1.055024 | 0.040461 | -0.658117 | -0.389972 | -0.280175 | 0.399313 |
0 | 1 | 0.252336 | 1 | 0 | 1 | 0.240881 | -0.498737 | 3 | 3 | 0 | 1 | -0.635701 | -1.210568 | 3.545837 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1.139969 | 1.686799 | 1.647681 | 0.599297 | 1.300895 | 1.055024 | 1.372303 | -0.145888 | 1.11898 | 3.569192 | 0.399313 |
0 | 1 | -0.529411 | 1 | 0 | 1 | 0.240881 | 0.417547 | 3 | 2 | 1 | 0 | -0.635701 | 1.20293 | -0.446388 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1.139969 | -0.276474 | -0.102461 | -0.527952 | -1.004242 | 1.055024 | -0.492276 | 0.366341 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | -0.529411 | 1 | 0 | 1 | -1.615664 | -0.498737 | 3 | 3 | 2 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | -1.104456 | -0.276474 | -0.102461 | -0.527952 | -0.235863 | -0.378901 | -0.492276 | -1.170346 | -0.389972 | -0.280175 | 0.399313 |
1 | 1 | 1.034083 | 0 | 1 | 1 | -1.615664 | -0.498737 | 0 | 3 | 2 | 0 | 2.154321 | -1.210568 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 0.017757 | -0.276474 | -0.102461 | 0.599297 | 0.532516 | -0.378901 | -0.359092 | -1.170346 | 0.615996 | -0.280175 | 0.399313 |
0 | 1 | -0.529411 | 1 | 0 | 1 | 1.169153 | 1.333832 | 4 | 4 | 0 | 0 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1.139969 | 0.705163 | 0.77261 | -0.527952 | -0.235863 | 1.055024 | -0.492276 | 1.390799 | -0.389972 | -0.280175 | 0.399313 |
0 | 1 | -0.529411 | 0 | 0 | 1 | 1.169153 | 1.333832 | 4 | 4 | 0 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | -1.104456 | 1.686799 | 1.647681 | 0.599297 | 2.069274 | 0.338061 | 0.306829 | 1.390799 | 1.621964 | -0.280175 | -1.218416 |
0 | 1 | 0.252336 | 1 | 0 | 1 | 0.240881 | 0.417547 | 2 | 2 | 3 | 0 | -0.635701 | -0.003819 | -0.446388 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0.017757 | -0.276474 | 0.77261 | -0.527952 | 1.300895 | 0.338061 | -0.225907 | 0.366341 | 0.615996 | -0.280175 | -1.218416 |
0 | 0 | -0.529411 | 1 | 1 | 1 | -0.687391 | 1.333832 | 2 | 1 | 0 | 0 | 0.75931 | -0.003819 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0.017757 | -1.25811 | -0.977532 | -0.527952 | -0.235863 | 1.055024 | -0.492276 | 0.366341 | -0.389972 | -0.280175 | 0.399313 |
1 | 0 | 1.034083 | 1 | 1 | 1 | -1.615664 | -1.415022 | 0 | 3 | 0 | 0 | 0.75931 | 1.20293 | -0.446388 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1.139969 | -0.276474 | -0.977532 | -0.527952 | -1.004242 | 0.338061 | -0.758644 | -1.682575 | -0.892956 | -0.280175 | -1.218416 |
0 | 0 | -1.311158 | 1 | 0 | 1 | -1.615664 | -1.415022 | 0 | 2 | 0 | 1 | 2.154321 | -1.210568 | -0.446388 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 0.017757 | -0.276474 | -0.102461 | -0.527952 | -0.235863 | 0.338061 | -0.758644 | -1.682575 | -0.389972 | -0.280175 | 0.399313 |
0 | 1 | 0.252336 | 1 | 1 | 0 | 1.169153 | -1.415022 | 3 | 2 | 1 | 1 | 0.75931 | -1.210568 | -0.446388 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0.017757 | 1.686799 | 0.77261 | 0.599297 | 1.300895 | 1.055024 | 3.236881 | -0.145888 | 1.11898 | -0.280175 | -1.218416 |
0 | 1 | 0.252336 | 0 | 0 | 1 | 0.240881 | 1.333832 | 0 | 2 | 0 | 1 | 2.154321 | -0.003819 | -0.446388 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1.139969 | 0.705163 | 1.647681 | 0.599297 | 1.300895 | 1.055024 | -0.758644 | 0.87857 | 1.11898 | -0.280175 | -1.218416 |
0 | 0 | -0.529411 | 1 | 1 | 1 | 1.169153 | 1.333832 | 1 | 1 | 2 | 1 | -0.635701 | 1.20293 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1.139969 | 0.705163 | 1.647681 | -0.527952 | -1.004242 | 0.338061 | -0.225907 | 1.390799 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | -0.529411 | 0 | 0 | 0 | 1.169153 | 1.333832 | 2 | 4 | 3 | 1 | 0.75931 | 1.20293 | -0.446388 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | -2.226669 | 0.705163 | -0.102461 | -0.527952 | -1.004242 | 1.055024 | 0.173645 | 1.390799 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | 0.252336 | 1 | 1 | 1 | 1.169153 | 0.417547 | 1 | 2 | 0 | 1 | 0.75931 | -0.003819 | -0.446388 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | -2.226669 | 1.686799 | 1.647681 | -0.527952 | 1.300895 | 1.055024 | 1.105934 | 0.87857 | 0.615996 | -0.280175 | -1.218416 |
0 | 1 | 1.034083 | 1 | 1 | 1 | -0.687391 | -0.498737 | 2 | 2 | 0 | 1 | -0.635701 | 2.409679 | -0.446388 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0.017757 | 1.686799 | 1.647681 | 0.599297 | 1.300895 | 1.055024 | -0.492276 | -0.658117 | 1.11898 | -0.280175 | 0.399313 |
1 | 1 | 0.252336 | 1 | 0 | 1 | 0.240881 | 0.417547 | 1 | 2 | 0 | 1 | 0.75931 | -0.003819 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0.017757 | 1.686799 | 0.77261 | 0.599297 | 0.532516 | -0.378901 | -0.492276 | 0.366341 | 0.615996 | -0.280175 | 0.399313 |
0 | 1 | 0.252336 | 1 | 1 | 1 | 1.169153 | 1.333832 | 3 | 2 | 1 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1.139969 | -0.276474 | 1.647681 | 2.853796 | 2.069274 | -0.378901 | 0.97275 | 1.390799 | 2.627932 | -0.280175 | 0.399313 |
0 | 1 | 1.815831 | 1 | 1 | 0 | 1.169153 | 0.417547 | 3 | 0 | 3 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0.017757 | -0.276474 | -1.852603 | -0.527952 | -1.004242 | -1.812826 | 0.839566 | 0.87857 | -0.892956 | -0.280175 | 0.399313 |
0 | 0 | -0.529411 | 1 | 1 | 1 | -0.687391 | -0.498737 | 0 | 2 | 0 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0.017757 | -0.276474 | 0.77261 | -0.527952 | -0.235863 | -1.095864 | -0.225907 | -0.658117 | -0.389972 | -0.280175 | 0.399313 |
0 | 1 | 0.252336 | 1 | 1 | 1 | 1.169153 | 1.333832 | 4 | 2 | 3 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0.017757 | 0.705163 | 0.77261 | -0.527952 | 0.532516 | 1.055024 | -0.758644 | 1.390799 | 0.113012 | -0.280175 | 0.399313 |
1 | 0 | 1.815831 | 1 | 1 | 1 | 0.240881 | -0.498737 | 3 | 3 | 1 | 2 | 0.75931 | -0.003819 | 2.215095 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | -1.104456 | -1.25811 | -0.977532 | -0.527952 | -1.004242 | -0.378901 | -0.225907 | -0.145888 | -0.892956 | -0.280175 | -1.218416 |
0 | 1 | -1.311158 | 1 | 0 | 1 | -0.687391 | -0.498737 | 2 | 2 | 1 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0.017757 | -1.25811 | -0.977532 | -0.527952 | -0.235863 | 1.055024 | -0.492276 | -0.658117 | -0.389972 | -0.280175 | 0.399313 |
0 | 1 | -1.311158 | 1 | 0 | 1 | 1.169153 | -0.498737 | 4 | 2 | 1 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0.017757 | -0.276474 | -0.102461 | 0.599297 | -0.235863 | 1.055024 | -0.492276 | 0.366341 | 0.113012 | -0.280175 | 0.399313 |
0 | 0 | 0.252336 | 1 | 0 | 1 | 1.169153 | 1.333832 | 3 | 4 | 1 | 1 | 0.75931 | -1.210568 | 0.884354 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0.017757 | -1.25811 | 0.77261 | 0.599297 | 0.532516 | -1.095864 | 2.437776 | 1.390799 | 0.615996 | 3.569192 | 0.399313 |
0 | 0 | -0.529411 | 1 | 0 | 1 | 0.240881 | 1.333832 | 0 | 2 | 0 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | -2.226669 | 0.705163 | -0.102461 | -0.527952 | -0.235863 | -0.378901 | 0.839566 | 0.87857 | -0.389972 | -0.280175 | 0.399313 |
1 | 1 | 1.034083 | 0 | 1 | 1 | -1.615664 | -1.415022 | 0 | 2 | 2 | 1 | 0.75931 | -0.003819 | 0.884354 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0.017757 | 0.705163 | -0.102461 | 0.599297 | 0.532516 | 1.055024 | -0.492276 | -1.682575 | 0.615996 | -0.280175 | -1.218416 |
0 | 0 | 0.252336 | 1 | 1 | 1 | 0.240881 | -0.498737 | 2 | 2 | 3 | 1 | 0.75931 | -0.003819 | -0.446388 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0.017757 | 0.705163 | 0.77261 | -0.527952 | 0.532516 | -1.812826 | -0.492276 | -0.145888 | 0.113012 | -0.280175 | -1.218416 |
0 | 0 | 0.252336 | 1 | 0 | 0 | 0.240881 | 0.417547 | 1 | 2 | 3 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | -1.104456 | -0.276474 | -0.102461 | -0.527952 | 0.532516 | -0.378901 | 0.040461 | 0.366341 | 0.113012 | -0.280175 | 0.399313 |
0 | 1 | -1.311158 | 0 | 0 | 1 | 1.169153 | 1.333832 | 2 | 2 | 1 | 0 | 3.549332 | 2.409679 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | -3.348881 | -0.276474 | 1.647681 | 1.726547 | 2.069274 | -1.812826 | 0.040461 | 1.390799 | 2.124948 | -0.280175 | 0.399313 |
0 | 1 | 0.252336 | 1 | 0 | 1 | 0.240881 | 0.417547 | 1 | 2 | 1 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0.017757 | 0.705163 | -0.102461 | -0.527952 | 0.532516 | 1.055024 | -0.225907 | 0.366341 | 0.113012 | -0.280175 | 0.399313 |
0 | 0 | 1.815831 | 1 | 1 | 1 | 0.240881 | -0.498737 | 3 | 2 | 3 | 2 | 0.75931 | -0.003819 | 0.884354 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 0.017757 | -1.25811 | -0.977532 | -0.527952 | -0.235863 | -1.812826 | 2.171408 | -0.145888 | -0.389972 | 3.569192 | 0.399313 |
0 | 1 | -1.311158 | 1 | 0 | 1 | 1.169153 | 0.417547 | 4 | 2 | 3 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0.017757 | 0.705163 | -1.852603 | -0.527952 | -1.004242 | -1.812826 | -0.758644 | 0.87857 | -0.892956 | -0.280175 | -1.218416 |
0 | 1 | 0.252336 | 1 | 1 | 1 | -0.687391 | -0.498737 | 2 | 2 | 1 | 0 | -0.635701 | -0.003819 | -0.446388 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0.017757 | 0.705163 | -0.977532 | 3.981045 | 2.069274 | 0.338061 | -0.225907 | -0.658117 | 3.130916 | -0.280175 | -1.218416 |
0 | 1 | 0.252336 | 1 | 0 | 1 | 1.169153 | 1.333832 | 3 | 4 | 1 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1.139969 | -1.25811 | -0.102461 | -0.527952 | -0.235863 | 1.055024 | -0.225907 | 1.390799 | -0.389972 | -0.280175 | -1.218416 |
0 | 1 | 1.034083 | 1 | 1 | 1 | 0.240881 | 1.333832 | 3 | 2 | 1 | 1 | -0.635701 | -0.003819 | -0.446388 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0.017757 | -0.276474 | -0.102461 | -0.527952 | 0.532516 | 1.055024 | 0.706382 | 0.87857 | 0.113012 | -0.280175 | -1.218416 |
1 | 0 | 0.252336 | 0 | 0 | 1 | 1.169153 | 1.333832 | 4 | 3 | 2 | 0 | 0.75931 | -0.003819 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0.017757 | -0.276474 | -0.102461 | -0.527952 | -0.235863 | 1.055024 | -0.225907 | 1.390799 | -0.389972 | -0.280175 | 0.399313 |
0 | 0 | -1.311158 | 1 | 0 | 1 | 1.169153 | -0.498737 | 2 | 2 | 3 | 1 | -0.635701 | 1.20293 | -0.446388 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1.139969 | -0.276474 | -0.102461 | -0.527952 | 0.532516 | -1.812826 | -0.225907 | 0.366341 | 0.113012 | -0.280175 | 0.399313 |
0 | 0 | -1.311158 | 1 | 0 | 1 | 1.169153 | 1.333832 | 4 | 3 | 0 | 1 | -0.635701 | 1.20293 | -0.446388 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0.017757 | -1.25811 | -0.977532 | -0.527952 | -1.004242 | 1.055024 | -0.492276 | 1.390799 | -0.892956 | -0.280175 | 0.399313 |
0 | 1 | -0.529411 | 0 | 0 | 1 | -0.687391 | -1.415022 | 2 | 2 | 0 | 1 | 0.75931 | -1.210568 | -0.446388 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | -1.104456 | -0.276474 | -0.977532 | -0.527952 | 0.532516 | -0.378901 | -0.758644 | -1.170346 | 0.113012 | -0.280175 | -1.218416 |
0 | 1 | 1.034083 | 1 | 1 | 1 | 1.169153 | 1.333832 | 4 | 4 | 1 | 1 | -0.635701 | -1.210568 | -0.446388 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | -3.348881 | 0.705163 | -0.977532 | 0.599297 | -0.235863 | -1.812826 | -0.092723 | 1.390799 | 0.113012 | -0.280175 | 0.399313 |
1 | 1 | 1.034083 | 0 | 0 | 1 | 0.240881 | -0.498737 | 2 | 2 | 0 | 1 | 0.75931 | -1.210568 | 0.884354 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | -2.226669 | 1.686799 | 1.647681 | 3.981045 | 2.069274 | 1.055024 | 0.573198 | -0.145888 | 3.130916 | -0.280175 | 0.399313 |
0 | 1 | 0.252336 | 1 | 1 | 1 | 1.169153 | 0.417547 | 4 | 2 | 0 | 1 | 0.75931 | -0.003819 | -0.446388 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0.017757 | 0.705163 | 0.77261 | 2.853796 | 1.300895 | 0.338061 | -0.225907 | 0.87857 | 2.124948 | -0.280175 | -1.218416 |
0 | 0 | 1.034083 | 1 | 0 | 1 | -1.615664 | -1.415022 | 2 | 2 | 1 | 1 | 0.75931 | -0.003819 | -0.446388 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1.139969 | 0.705163 | 0.77261 | -0.527952 | -1.004242 | 0.338061 | -0.225907 | -1.682575 | -0.892956 | -0.280175 | 0.399313 |
1 | 0 | 1.034083 | 0 | 0 | 1 | -1.615664 | -1.415022 | 2 | 2 | 1 | 1 | 3.549332 | 1.20293 | -0.446388 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0.017757 | -0.276474 | -0.977532 | -0.527952 | -0.235863 | 0.338061 | -0.492276 | -1.682575 | -0.389972 | -0.280175 | -1.218416 |
0 | 0 | 1.034083 | 1 | 0 | 1 | 1.169153 | 1.333832 | 1 | 1 | 3 | 0 | -0.635701 | -0.003819 | 0.884354 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | -2.226669 | 0.705163 | 0.77261 | -0.527952 | -1.004242 | 0.338061 | 1.239119 | 1.390799 | -0.892956 | 3.569192 | 2.017041 |
End of preview.
YAML Metadata Warning:The task_ids "binary-classification" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, text2text-generation, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering, pose-estimation
Student Dropout Prediction Dataset
Dataset Description
Preprocessed dataset for early dropout prediction in secondary schools. Based on the UCI Student Performance Dataset (Cortez & Silva, 2008).
Dataset Structure
| File | Description | Rows |
|---|---|---|
| X_train.csv | Training features | 316 |
| X_test.csv | Test features | 79 |
| y_train.csv | Training labels | 316 |
| y_test.csv | Test labels | 79 |
| student-mat.csv | Original math dataset | 395 |
| student-por.csv | Original portuguese dataset | 649 |
Features
34 socio-behavioral variables including :
- Academic history (failures, absences, study time)
- Family context (parent education, family support)
- Behavioral indicators (social activity, alcohol consumption)
Target Variable
Binary classification :
- 0 : Pass (final grade >= 10/20)
- 1 : Fail / Dropout risk (final grade < 10/20)
Preprocessing
- Categorical variables encoded
- Feature engineering applied (parent_edu_mean, total_alcohol, high_risk, total_support)
- Train/test split : 80/20
Model Performance
Logistic Regression trained on this dataset achieves :
- Recall : 80.77%
- Precision : 44.68%
- F1-Score : 0.578
Source
Cortez, P., & Silva, A. (2008). Using Data Mining to Predict Secondary School Student Performance. UCI Machine Learning Repository.
Related Resources
- Prediction app : https://student-dropout-prediction-fxj3vscls4vnvm9hpj2263.streamlit.app
- GitHub : https://github.com/justinkelem708-ops/student-dropout-prediction
License
CC BY 4.0
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