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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 6 new columns ({'column_10', 'column_3', 'column_8', 'column_4', 'column_9', 'column_7'}) and 15 missing columns ({'CO(GT)', 'NOx(GT)', 'RH', 'PT08.S5(O3)', 'AH', 'NMHC(GT)', 'PT08.S4(NO2)', 'PT08.S3(NOx)', 'Date', 'T', 'Time', 'NO2(GT)', 'C6H6(GT)', 'PT08.S1(CO)', 'PT08.S2(NMHC)'}).
This happened while the csv dataset builder was generating data using
hf://datasets/THULab/TSCB_dataset/Arade.csv (at revision 84fb3a99723d72c46bb0c50ffee2f828778a3d95), ['hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Air-Quality.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Arade.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Bar-Crawl.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Bird-migration.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Comments.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/IGlocations2.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Metro-Traffic.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/NYC_Yellow_Taxi_Trip.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/RealEstate1.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/RealEstate2.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Romance.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Telco.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/TrainsUK2.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Uberlandia.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Wins.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/YaleLanguages.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/medium_posts.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/meteoblue.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/poisson_timestamps.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/rating.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/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/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/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
column_3: double
column_4: double
column_7: double
column_8: double
column_9: int64
column_10: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 977
to
{'Date': Value('int64'), 'Time': Value('int64'), 'CO(GT)': Value('float64'), 'PT08.S1(CO)': Value('int64'), 'NMHC(GT)': Value('int64'), 'C6H6(GT)': Value('float64'), 'PT08.S2(NMHC)': Value('int64'), 'NOx(GT)': Value('int64'), 'PT08.S3(NOx)': Value('int64'), 'NO2(GT)': Value('int64'), 'PT08.S4(NO2)': Value('int64'), 'PT08.S5(O3)': Value('int64'), 'T': Value('float64'), 'RH': Value('float64'), 'AH': 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 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
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 6 new columns ({'column_10', 'column_3', 'column_8', 'column_4', 'column_9', 'column_7'}) and 15 missing columns ({'CO(GT)', 'NOx(GT)', 'RH', 'PT08.S5(O3)', 'AH', 'NMHC(GT)', 'PT08.S4(NO2)', 'PT08.S3(NOx)', 'Date', 'T', 'Time', 'NO2(GT)', 'C6H6(GT)', 'PT08.S1(CO)', 'PT08.S2(NMHC)'}).
This happened while the csv dataset builder was generating data using
hf://datasets/THULab/TSCB_dataset/Arade.csv (at revision 84fb3a99723d72c46bb0c50ffee2f828778a3d95), ['hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Air-Quality.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Arade.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Bar-Crawl.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Bird-migration.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Comments.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/IGlocations2.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Metro-Traffic.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/NYC_Yellow_Taxi_Trip.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/RealEstate1.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/RealEstate2.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Romance.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Telco.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/TrainsUK2.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Uberlandia.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/Wins.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/YaleLanguages.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/medium_posts.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/meteoblue.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/poisson_timestamps.csv', 'hf://datasets/THULab/TSCB_dataset@84fb3a99723d72c46bb0c50ffee2f828778a3d95/rating.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.
Date int64 | Time int64 | CO(GT) float64 | PT08.S1(CO) int64 | NMHC(GT) int64 | C6H6(GT) float64 | PT08.S2(NMHC) int64 | NOx(GT) int64 | PT08.S3(NOx) int64 | NO2(GT) int64 | PT08.S4(NO2) int64 | PT08.S5(O3) int64 | T float64 | RH float64 | AH float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,078,876,800,000,000 | 0 | 2.6 | 1,360 | 150 | 11.9 | 1,046 | 166 | 1,056 | 113 | 1,692 | 1,268 | 13.6 | 48.9 | 0.7578 |
1,078,876,800,000,000 | 1,000,000,000,000 | 2 | 1,292 | 112 | 9.4 | 955 | 103 | 1,174 | 92 | 1,559 | 972 | 13.3 | 47.7 | 0.7255 |
1,078,876,800,000,000 | 2,000,000,000,000 | 2.2 | 1,402 | 88 | 9 | 939 | 131 | 1,140 | 114 | 1,555 | 1,074 | 11.9 | 54 | 0.7502 |
1,078,876,800,000,000 | 3,000,000,000,000 | 2.2 | 1,376 | 80 | 9.2 | 948 | 172 | 1,092 | 122 | 1,584 | 1,203 | 11 | 60 | 0.7867 |
1,078,876,800,000,000 | 4,000,000,000,000 | 1.6 | 1,272 | 51 | 6.5 | 836 | 131 | 1,205 | 116 | 1,490 | 1,110 | 11.2 | 59.6 | 0.7888 |
1,078,876,800,000,000 | 5,000,000,000,000 | 1.2 | 1,197 | 38 | 4.7 | 750 | 89 | 1,337 | 96 | 1,393 | 949 | 11.2 | 59.2 | 0.7848 |
1,078,963,200,000,000 | 6,000,000,000,000 | 1.2 | 1,185 | 31 | 3.6 | 690 | 62 | 1,462 | 77 | 1,333 | 733 | 11.3 | 56.8 | 0.7603 |
1,078,963,200,000,000 | 7,000,000,000,000 | 1 | 1,136 | 31 | 3.3 | 672 | 62 | 1,453 | 76 | 1,333 | 730 | 10.7 | 60 | 0.7702 |
1,078,963,200,000,000 | 8,000,000,000,000 | 0.9 | 1,094 | 24 | 2.3 | 609 | 45 | 1,579 | 60 | 1,276 | 620 | 10.7 | 59.7 | 0.7648 |
1,078,963,200,000,000 | 9,000,000,000,000 | 0.6 | 1,010 | 19 | 1.7 | 561 | -200 | 1,705 | -200 | 1,235 | 501 | 10.3 | 60.2 | 0.7517 |
1,078,963,200,000,000 | 10,000,000,000,000 | -200 | 1,011 | 14 | 1.3 | 527 | 21 | 1,818 | 34 | 1,197 | 445 | 10.1 | 60.5 | 0.7465 |
1,078,963,200,000,000 | 11,000,000,000,000 | 0.7 | 1,066 | 8 | 1.1 | 512 | 16 | 1,918 | 28 | 1,182 | 422 | 11 | 56.2 | 0.7366 |
1,078,963,200,000,000 | 12,000,000,000,000 | 0.7 | 1,052 | 16 | 1.6 | 553 | 34 | 1,738 | 48 | 1,221 | 472 | 10.5 | 58.1 | 0.7353 |
1,078,963,200,000,000 | 13,000,000,000,000 | 1.1 | 1,144 | 29 | 3.2 | 667 | 98 | 1,490 | 82 | 1,339 | 730 | 10.2 | 59.6 | 0.7417 |
1,078,963,200,000,000 | 14,000,000,000,000 | 2 | 1,333 | 64 | 8 | 900 | 174 | 1,136 | 112 | 1,517 | 1,102 | 10.8 | 57.4 | 0.7408 |
1,078,963,200,000,000 | 15,000,000,000,000 | 2.2 | 1,351 | 87 | 9.5 | 960 | 129 | 1,079 | 101 | 1,583 | 1,028 | 10.5 | 60.6 | 0.7691 |
1,078,963,200,000,000 | 16,000,000,000,000 | 1.7 | 1,233 | 77 | 6.3 | 827 | 112 | 1,218 | 98 | 1,446 | 860 | 10.8 | 58.4 | 0.7552 |
1,078,963,200,000,000 | 17,000,000,000,000 | 1.5 | 1,179 | 43 | 5 | 762 | 95 | 1,328 | 92 | 1,362 | 671 | 10.5 | 57.9 | 0.7352 |
1,078,963,200,000,000 | 18,000,000,000,000 | 1.6 | 1,236 | 61 | 5.2 | 774 | 104 | 1,301 | 95 | 1,401 | 664 | 9.5 | 66.8 | 0.7951 |
1,078,963,200,000,000 | 19,000,000,000,000 | 1.9 | 1,286 | 63 | 7.3 | 869 | 146 | 1,162 | 112 | 1,537 | 799 | 8.3 | 76.4 | 0.8393 |
1,078,963,200,000,000 | 20,000,000,000,000 | 2.9 | 1,371 | 164 | 11.5 | 1,034 | 207 | 983 | 128 | 1,730 | 1,037 | 8 | 81.1 | 0.8736 |
1,078,963,200,000,000 | 21,000,000,000,000 | 2.2 | 1,310 | 79 | 8.8 | 933 | 184 | 1,082 | 126 | 1,647 | 946 | 8.3 | 79.8 | 0.8778 |
1,078,963,200,000,000 | 22,000,000,000,000 | 2.2 | 1,292 | 95 | 8.3 | 912 | 193 | 1,103 | 131 | 1,591 | 957 | 9.7 | 71.2 | 0.8569 |
1,078,963,200,000,000 | 23,000,000,000,000 | 2.9 | 1,383 | 150 | 11.2 | 1,020 | 243 | 1,008 | 135 | 1,719 | 1,104 | 9.8 | 67.6 | 0.8185 |
1,078,963,200,000,000 | 24,000,000,000,000 | 4.8 | 1,581 | 307 | 20.8 | 1,319 | 281 | 799 | 151 | 2,083 | 1,409 | 10.3 | 64.2 | 0.8065 |
1,078,963,200,000,000 | 25,000,000,000,000 | 6.9 | 1,776 | 461 | 27.4 | 1,488 | 383 | 702 | 172 | 2,333 | 1,704 | 9.7 | 69.3 | 0.8319 |
1,078,963,200,000,000 | 26,000,000,000,000 | 6.1 | 1,640 | 401 | 24 | 1,404 | 351 | 743 | 165 | 2,191 | 1,654 | 9.6 | 67.8 | 0.8133 |
1,078,963,200,000,000 | 27,000,000,000,000 | 3.9 | 1,313 | 197 | 12.8 | 1,076 | 240 | 957 | 136 | 1,707 | 1,285 | 9.1 | 64 | 0.7419 |
1,078,963,200,000,000 | 28,000,000,000,000 | 1.5 | 965 | 61 | 4.7 | 749 | 94 | 1,325 | 85 | 1,333 | 821 | 8.2 | 63.4 | 0.6905 |
1,078,963,200,000,000 | 29,000,000,000,000 | 1 | 913 | 26 | 2.6 | 629 | 47 | 1,565 | 53 | 1,252 | 552 | 8.2 | 60.8 | 0.6657 |
1,079,049,600,000,000 | 30,000,000,000,000 | 1.7 | 1,080 | 55 | 5.9 | 805 | 122 | 1,254 | 97 | 1,375 | 816 | 8.3 | 58.5 | 0.6438 |
1,079,049,600,000,000 | 31,000,000,000,000 | 1.9 | 1,044 | 53 | 6.4 | 829 | 133 | 1,247 | 110 | 1,378 | 832 | 7.7 | 59.7 | 0.6308 |
1,079,049,600,000,000 | 32,000,000,000,000 | 1.4 | 988 | 40 | 4.1 | 718 | 82 | 1,396 | 91 | 1,304 | 692 | 7.1 | 61.8 | 0.6276 |
1,079,049,600,000,000 | 33,000,000,000,000 | 0.8 | 889 | 21 | 1.9 | 574 | -200 | 1,680 | -200 | 1,187 | 512 | 7 | 62.3 | 0.6261 |
1,079,049,600,000,000 | 34,000,000,000,000 | -200 | 831 | 10 | 1.1 | 506 | 21 | 1,893 | 32 | 1,134 | 384 | 6.1 | 65.9 | 0.6248 |
1,079,049,600,000,000 | 35,000,000,000,000 | 0.6 | 847 | 7 | 1 | 501 | 30 | 1,895 | 44 | 1,155 | 394 | 6.3 | 65 | 0.6233 |
1,079,049,600,000,000 | 36,000,000,000,000 | 0.8 | 927 | 17 | 1.8 | 571 | 56 | 1,685 | 71 | 1,223 | 487 | 6.8 | 62.9 | 0.6234 |
1,079,049,600,000,000 | 37,000,000,000,000 | 1.4 | 1,091 | 33 | 4.4 | 730 | 109 | 1,387 | 104 | 1,361 | 748 | 6.4 | 65.1 | 0.6316 |
1,079,049,600,000,000 | 38,000,000,000,000 | 4.4 | 1,587 | 202 | 17.9 | 1,236 | 307 | 897 | 141 | 1,900 | 1,400 | 7.3 | 63.1 | 0.6499 |
1,079,049,600,000,000 | 39,000,000,000,000 | -200 | 1,545 | -200 | 22.1 | 1,353 | -200 | 767 | -200 | 2,058 | 1,588 | 9.2 | 56.2 | 0.6561 |
1,079,049,600,000,000 | 40,000,000,000,000 | 3.1 | 1,350 | 208 | 14 | 1,118 | 187 | 912 | 122 | 1,712 | 1,237 | 13.2 | 41.7 | 0.632 |
1,079,049,600,000,000 | 41,000,000,000,000 | 2.7 | 1,263 | 166 | 11.6 | 1,037 | 216 | 969 | 143 | 1,598 | 1,167 | 14.3 | 38.4 | 0.6243 |
1,079,049,600,000,000 | 42,000,000,000,000 | 2.1 | 1,206 | 114 | 10.2 | 986 | 143 | 1,035 | 113 | 1,537 | 959 | 15 | 36.5 | 0.6195 |
1,079,049,600,000,000 | 43,000,000,000,000 | 2.5 | 1,252 | 140 | 11 | 1,016 | 160 | 1,008 | 116 | 1,593 | 983 | 16.1 | 34.5 | 0.6262 |
1,079,049,600,000,000 | 44,000,000,000,000 | 2.7 | 1,287 | 169 | 12.8 | 1,078 | 163 | 949 | 123 | 1,660 | 1,061 | 16.3 | 35.7 | 0.656 |
1,079,049,600,000,000 | 45,000,000,000,000 | 2.9 | 1,353 | 185 | 14.2 | 1,122 | 190 | 922 | 126 | 1,740 | 1,139 | 15.8 | 37 | 0.661 |
1,079,049,600,000,000 | 46,000,000,000,000 | 2.8 | 1,309 | 165 | 12.7 | 1,073 | 178 | 954 | 120 | 1,657 | 1,112 | 15.9 | 37.2 | 0.6657 |
1,079,049,600,000,000 | 47,000,000,000,000 | 2.4 | 1,274 | 133 | 11.7 | 1,041 | 150 | 1,006 | 119 | 1,610 | 994 | 16.9 | 34.3 | 0.6549 |
1,079,049,600,000,000 | 48,000,000,000,000 | 3.9 | 1,510 | 233 | 19.3 | 1,277 | 206 | 812 | 149 | 1,910 | 1,410 | 15.1 | 39.6 | 0.6766 |
1,079,049,600,000,000 | 49,000,000,000,000 | 3.7 | 1,525 | 242 | 18.2 | 1,246 | 202 | 821 | 145 | 1,847 | 1,448 | 14.4 | 43.4 | 0.7084 |
1,079,049,600,000,000 | 50,000,000,000,000 | 6.6 | 1,843 | 488 | 32.6 | 1,610 | 340 | 624 | 170 | 2,390 | 1,887 | 12.9 | 50.5 | 0.7478 |
1,079,049,600,000,000 | 51,000,000,000,000 | 4.4 | 1,598 | 333 | 20.1 | 1,299 | 274 | 752 | 149 | 1,941 | 1,627 | 12.1 | 53.3 | 0.7536 |
1,079,049,600,000,000 | 52,000,000,000,000 | 3.5 | 1,484 | 215 | 14.3 | 1,127 | 253 | 839 | 139 | 1,723 | 1,491 | 11 | 59.1 | 0.774 |
1,079,049,600,000,000 | 53,000,000,000,000 | 5.4 | 1,677 | 367 | 21.8 | 1,346 | 300 | 741 | 134 | 2,062 | 1,657 | 9.7 | 64.6 | 0.7771 |
1,079,136,000,000,000 | 54,000,000,000,000 | 2.7 | 1,280 | 122 | 9.6 | 964 | 193 | 963 | 113 | 1,544 | 1,285 | 9.5 | 64.1 | 0.7597 |
1,079,136,000,000,000 | 55,000,000,000,000 | 1.9 | 1,196 | 67 | 7.4 | 873 | 139 | 1,071 | 97 | 1,463 | 1,144 | 9.1 | 63.9 | 0.7423 |
1,079,136,000,000,000 | 56,000,000,000,000 | 1.6 | 1,184 | 43 | 5.4 | 782 | 83 | 1,176 | 82 | 1,365 | 1,043 | 8.8 | 63.9 | 0.7256 |
1,079,136,000,000,000 | 57,000,000,000,000 | 1.7 | 1,172 | 46 | 5.4 | 783 | -200 | 1,179 | -200 | 1,380 | 996 | 7.8 | 67.5 | 0.7173 |
1,079,136,000,000,000 | 58,000,000,000,000 | -200 | 1,147 | 56 | 6.2 | 821 | 109 | 1,132 | 83 | 1,412 | 992 | 7 | 71.1 | 0.7158 |
1,079,136,000,000,000 | 59,000,000,000,000 | 1 | 978 | 30 | 2.6 | 625 | 62 | 1,420 | 65 | 1,274 | 819 | 8.3 | 63.6 | 0.6982 |
1,079,136,000,000,000 | 60,000,000,000,000 | 1.2 | 1,100 | 27 | 2.9 | 646 | 53 | 1,406 | 60 | 1,268 | 835 | 7.2 | 67.5 | 0.6887 |
1,079,136,000,000,000 | 61,000,000,000,000 | 1.5 | 1,112 | 47 | 5.1 | 770 | 139 | 1,228 | 77 | 1,409 | 940 | 6.3 | 71.9 | 0.6932 |
1,079,136,000,000,000 | 62,000,000,000,000 | 2.7 | 1,336 | 132 | 11.8 | 1,043 | 256 | 935 | 96 | 1,678 | 1,192 | 6.5 | 71.6 | 0.6945 |
1,079,136,000,000,000 | 63,000,000,000,000 | 3.7 | 1,408 | 239 | 15.1 | 1,153 | 295 | 830 | 119 | 1,777 | 1,411 | 9.6 | 59.7 | 0.7124 |
1,079,136,000,000,000 | 64,000,000,000,000 | 3.2 | 1,447 | 160 | 12.9 | 1,081 | 250 | 869 | 126 | 1,667 | 1,465 | 12.4 | 51.2 | 0.7335 |
1,079,136,000,000,000 | 65,000,000,000,000 | 4.1 | 1,542 | 283 | 16.1 | 1,184 | 296 | 808 | 158 | 1,780 | 1,583 | 15.6 | 42.2 | 0.7451 |
1,079,136,000,000,000 | 66,000,000,000,000 | 3.6 | 1,451 | 210 | 14 | 1,117 | 239 | 875 | 161 | 1,679 | 1,387 | 18.4 | 33.8 | 0.709 |
1,079,136,000,000,000 | 67,000,000,000,000 | 2.8 | 1,328 | 154 | 12.3 | 1,059 | 153 | 987 | 124 | 1,600 | 1,101 | 19.4 | 31.3 | 0.695 |
1,079,136,000,000,000 | 68,000,000,000,000 | 2 | 1,207 | 112 | 8.6 | 924 | 118 | 1,088 | 102 | 1,488 | 850 | 18 | 34.8 | 0.7127 |
1,079,136,000,000,000 | 69,000,000,000,000 | 2 | 1,240 | 108 | 9.2 | 947 | 119 | 1,049 | 116 | 1,532 | 947 | 18.4 | 33.6 | 0.7042 |
1,079,136,000,000,000 | 70,000,000,000,000 | 2.5 | 1,306 | 111 | 10.2 | 987 | 138 | 1,004 | 124 | 1,554 | 1,078 | 17.6 | 35.1 | 0.7012 |
1,079,136,000,000,000 | 71,000,000,000,000 | 2.3 | 1,326 | 97 | 10.6 | 1,000 | 148 | 976 | 125 | 1,602 | 1,084 | 16.7 | 37.8 | 0.7117 |
1,079,136,000,000,000 | 72,000,000,000,000 | 3.2 | 1,473 | 191 | 15.5 | 1,163 | 227 | 831 | 148 | 1,779 | 1,395 | 16.1 | 41 | 0.7451 |
1,079,136,000,000,000 | 73,000,000,000,000 | 4.2 | 1,609 | 258 | 19.6 | 1,286 | 277 | 758 | 165 | 1,922 | 1,612 | 15.8 | 42.4 | 0.7569 |
1,079,136,000,000,000 | 74,000,000,000,000 | 4.2 | 1,611 | 284 | 19.2 | 1,274 | 279 | 754 | 161 | 1,915 | 1,697 | 15.7 | 44.1 | 0.7786 |
1,079,136,000,000,000 | 75,000,000,000,000 | 4.2 | 1,621 | 269 | 18.3 | 1,247 | 283 | 762 | 159 | 1,860 | 1,886 | 15.3 | 46.8 | 0.8091 |
1,079,136,000,000,000 | 76,000,000,000,000 | 3.1 | 1,444 | 180 | 13.1 | 1,089 | 214 | 844 | 143 | 1,748 | 1,624 | 14.6 | 48.6 | 0.806 |
1,079,136,000,000,000 | 77,000,000,000,000 | 2.6 | 1,418 | 116 | 10.9 | 1,010 | 172 | 892 | 130 | 1,603 | 1,536 | 14.7 | 49.3 | 0.8193 |
1,079,222,400,000,000 | 78,000,000,000,000 | 2.9 | 1,534 | 93 | 11 | 1,013 | 190 | 889 | 129 | 1,611 | 1,535 | 13.9 | 53.6 | 0.8498 |
1,079,222,400,000,000 | 79,000,000,000,000 | 2.8 | 1,484 | 131 | 11.9 | 1,045 | 174 | 880 | 119 | 1,624 | 1,530 | 14.6 | 51.5 | 0.8536 |
1,079,222,400,000,000 | 80,000,000,000,000 | 2.5 | 1,367 | 92 | 8.6 | 925 | 128 | 953 | 104 | 1,543 | 1,337 | 12.5 | 58.9 | 0.8537 |
1,079,222,400,000,000 | 81,000,000,000,000 | 2.4 | 1,344 | 132 | 9.7 | 968 | -200 | 921 | -200 | 1,620 | 1,278 | 11.6 | 63.4 | 0.8674 |
1,079,222,400,000,000 | 82,000,000,000,000 | -200 | 1,130 | 56 | 5.2 | 773 | 70 | 1,130 | 82 | 1,452 | 1,051 | 12.1 | 61.1 | 0.8603 |
1,079,222,400,000,000 | 83,000,000,000,000 | 1.2 | 1,062 | 32 | 3.7 | 691 | 53 | 1,272 | 70 | 1,377 | 929 | 11.5 | 63.1 | 0.8533 |
1,079,222,400,000,000 | 84,000,000,000,000 | 1 | 1,076 | 29 | 2.5 | 618 | 44 | 1,395 | 63 | 1,333 | 872 | 11.6 | 62.2 | 0.8473 |
1,079,222,400,000,000 | 85,000,000,000,000 | 0.9 | 1,028 | 27 | 2.4 | 615 | 74 | 1,384 | 67 | 1,340 | 853 | 10.4 | 67.6 | 0.853 |
1,079,222,400,000,000 | 86,000,000,000,000 | 1.4 | 1,155 | 36 | 4.2 | 722 | 101 | 1,225 | 84 | 1,414 | 959 | 11.6 | 62.7 | 0.853 |
1,079,222,400,000,000 | 87,000,000,000,000 | 1.6 | 1,235 | 57 | 6.4 | 828 | 118 | 1,055 | 83 | 1,527 | 1,093 | 12.4 | 60 | 0.8627 |
1,079,222,400,000,000 | 88,000,000,000,000 | 2.2 | 1,332 | 129 | 8.6 | 923 | 144 | 952 | 98 | 1,614 | 1,225 | 14.5 | 53.1 | 0.8728 |
1,079,222,400,000,000 | 89,000,000,000,000 | 2.8 | 1,445 | 148 | 10.9 | 1,009 | 176 | 878 | 114 | 1,696 | 1,355 | 16.9 | 46.1 | 0.8789 |
1,079,222,400,000,000 | 90,000,000,000,000 | 2.8 | 1,416 | 145 | 10.7 | 1,002 | 161 | 907 | 119 | 1,677 | 1,262 | 19.3 | 38.3 | 0.8474 |
1,079,222,400,000,000 | 91,000,000,000,000 | 2 | 1,281 | 93 | 7.5 | 880 | 113 | 1,084 | 104 | 1,525 | 980 | 21.2 | 31.4 | 0.7812 |
1,079,222,400,000,000 | 92,000,000,000,000 | 1.8 | 1,207 | 84 | 7.5 | 879 | 103 | 1,104 | 102 | 1,490 | 872 | 21.4 | 30.2 | 0.7616 |
1,079,222,400,000,000 | 93,000,000,000,000 | 1.9 | 1,258 | 99 | 8.2 | 906 | 112 | 1,081 | 107 | 1,511 | 900 | 21.9 | 29 | 0.7525 |
1,079,222,400,000,000 | 94,000,000,000,000 | 3 | 1,458 | 150 | 11.9 | 1,045 | 170 | 974 | 129 | 1,646 | 1,099 | 22.2 | 28.4 | 0.7516 |
1,079,222,400,000,000 | 95,000,000,000,000 | 2.9 | 1,438 | 156 | 12 | 1,051 | 180 | 943 | 128 | 1,668 | 1,206 | 21.3 | 30.8 | 0.7696 |
1,079,222,400,000,000 | 96,000,000,000,000 | 2.5 | 1,478 | 122 | 12.2 | 1,055 | 160 | 929 | 121 | 1,671 | 1,262 | 19.7 | 36.7 | 0.8307 |
1,079,222,400,000,000 | 97,000,000,000,000 | 4.6 | 1,808 | 262 | 20.6 | 1,312 | 261 | 753 | 157 | 1,993 | 1,698 | 18.4 | 41.7 | 0.8732 |
1,079,222,400,000,000 | 98,000,000,000,000 | 5.9 | 1,898 | 341 | 23.1 | 1,381 | 325 | 681 | 173 | 2,103 | 1,905 | 17.6 | 46.1 | 0.921 |
1,079,222,400,000,000 | 99,000,000,000,000 | 3.4 | 1,560 | 214 | 14.7 | 1,140 | 217 | 784 | 146 | 1,818 | 1,648 | 16.7 | 49.6 | 0.932 |
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