Dataset Preview
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 4 new columns ({'1.13385', '1.13403', '00:00', '1.13782'}) and 4 missing columns ({'17:00', '1.13722', '1.13727', '1.13649'}).
This happened while the csv dataset builder was generating data using
hf://datasets/isaiahbjork/fx/EURUSD_1D_2022.csv (at revision cb82e0e135ab97986f712805cecbf7e5356c6590)
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
2022.01.02: string
00:00: string
1.1369: double
1.13782: double
1.13385: double
1.13403: double
0: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1048
to
{'2022.01.02': Value('string'), '17:00': Value('string'), '1.1369': Value('float64'), '1.13727': Value('float64'), '1.13649': Value('float64'), '1.13722': Value('float64'), '0': Value('int64')}
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 1456, 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 1055, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, 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 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 4 new columns ({'1.13385', '1.13403', '00:00', '1.13782'}) and 4 missing columns ({'17:00', '1.13722', '1.13727', '1.13649'}).
This happened while the csv dataset builder was generating data using
hf://datasets/isaiahbjork/fx/EURUSD_1D_2022.csv (at revision cb82e0e135ab97986f712805cecbf7e5356c6590)
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.
2022.01.02 string | 17:00 string | 1.1369 float64 | 1.13727 float64 | 1.13649 float64 | 1.13722 float64 | 0 int64 |
|---|---|---|---|---|---|---|
2022.01.02 | 17:15 | 1.13722 | 1.13724 | 1.137 | 1.137 | 0 |
2022.01.02 | 17:30 | 1.137 | 1.13741 | 1.137 | 1.13733 | 0 |
2022.01.02 | 17:45 | 1.13734 | 1.13735 | 1.13727 | 1.13729 | 0 |
2022.01.02 | 18:00 | 1.13721 | 1.13782 | 1.13721 | 1.13727 | 0 |
2022.01.02 | 18:15 | 1.13728 | 1.1376 | 1.13696 | 1.13733 | 0 |
2022.01.02 | 18:30 | 1.13733 | 1.13742 | 1.13695 | 1.13727 | 0 |
2022.01.02 | 18:45 | 1.13728 | 1.13728 | 1.13692 | 1.13727 | 0 |
2022.01.02 | 19:00 | 1.13726 | 1.13755 | 1.13705 | 1.13707 | 0 |
2022.01.02 | 19:15 | 1.13707 | 1.13709 | 1.13664 | 1.13664 | 0 |
2022.01.02 | 19:30 | 1.13663 | 1.13668 | 1.13608 | 1.13625 | 0 |
2022.01.02 | 19:45 | 1.13625 | 1.13636 | 1.13609 | 1.13618 | 0 |
2022.01.02 | 20:00 | 1.13619 | 1.13646 | 1.1361 | 1.13629 | 0 |
2022.01.02 | 20:15 | 1.13629 | 1.13651 | 1.13599 | 1.13613 | 0 |
2022.01.02 | 20:30 | 1.13614 | 1.13616 | 1.13498 | 1.13574 | 0 |
2022.01.02 | 20:45 | 1.13571 | 1.13599 | 1.13517 | 1.13584 | 0 |
2022.01.02 | 21:00 | 1.13584 | 1.13585 | 1.13487 | 1.13496 | 0 |
2022.01.02 | 21:15 | 1.13491 | 1.13509 | 1.1348 | 1.13494 | 0 |
2022.01.02 | 21:30 | 1.13491 | 1.13496 | 1.13446 | 1.13489 | 0 |
2022.01.02 | 21:45 | 1.13486 | 1.13491 | 1.13423 | 1.13425 | 0 |
2022.01.02 | 22:00 | 1.13428 | 1.13467 | 1.13423 | 1.1344 | 0 |
2022.01.02 | 22:15 | 1.13439 | 1.13441 | 1.13421 | 1.13438 | 0 |
2022.01.02 | 22:30 | 1.13439 | 1.13464 | 1.13412 | 1.13463 | 0 |
2022.01.02 | 22:45 | 1.13462 | 1.135 | 1.13456 | 1.13481 | 0 |
2022.01.02 | 23:00 | 1.13482 | 1.13482 | 1.1343 | 1.13464 | 0 |
2022.01.02 | 23:15 | 1.13462 | 1.13489 | 1.13456 | 1.13484 | 0 |
2022.01.02 | 23:30 | 1.13481 | 1.13481 | 1.13463 | 1.13463 | 0 |
2022.01.02 | 23:45 | 1.13463 | 1.13464 | 1.13385 | 1.13403 | 0 |
2022.01.03 | 00:00 | 1.13404 | 1.13411 | 1.1339 | 1.13398 | 0 |
2022.01.03 | 00:15 | 1.13396 | 1.13408 | 1.13364 | 1.13366 | 0 |
2022.01.03 | 00:30 | 1.13365 | 1.13405 | 1.13359 | 1.13405 | 0 |
2022.01.03 | 00:45 | 1.13407 | 1.13407 | 1.13371 | 1.13378 | 0 |
2022.01.03 | 01:00 | 1.13378 | 1.1342 | 1.13377 | 1.13401 | 0 |
2022.01.03 | 01:15 | 1.13401 | 1.13426 | 1.1338 | 1.13411 | 0 |
2022.01.03 | 01:30 | 1.13408 | 1.13451 | 1.13408 | 1.13429 | 0 |
2022.01.03 | 01:45 | 1.13431 | 1.13462 | 1.13428 | 1.13429 | 0 |
2022.01.03 | 02:00 | 1.1343 | 1.1346 | 1.13397 | 1.13439 | 0 |
2022.01.03 | 02:15 | 1.13438 | 1.1344 | 1.13362 | 1.13363 | 0 |
2022.01.03 | 02:30 | 1.13364 | 1.13395 | 1.13349 | 1.13394 | 0 |
2022.01.03 | 02:45 | 1.13395 | 1.135 | 1.13361 | 1.1348 | 0 |
2022.01.03 | 03:00 | 1.13479 | 1.13479 | 1.13368 | 1.13423 | 0 |
2022.01.03 | 03:15 | 1.13421 | 1.13458 | 1.13352 | 1.1337 | 0 |
2022.01.03 | 03:30 | 1.13369 | 1.13414 | 1.13354 | 1.13393 | 0 |
2022.01.03 | 03:45 | 1.13394 | 1.1347 | 1.13382 | 1.13465 | 0 |
2022.01.03 | 04:00 | 1.13465 | 1.13563 | 1.13444 | 1.13557 | 0 |
2022.01.03 | 04:15 | 1.13556 | 1.1356 | 1.13385 | 1.13389 | 0 |
2022.01.03 | 04:30 | 1.13387 | 1.13515 | 1.13356 | 1.13478 | 0 |
2022.01.03 | 04:45 | 1.13474 | 1.13554 | 1.13443 | 1.13516 | 0 |
2022.01.03 | 05:00 | 1.13516 | 1.13587 | 1.13506 | 1.13576 | 0 |
2022.01.03 | 05:15 | 1.13578 | 1.13596 | 1.13546 | 1.13554 | 0 |
2022.01.03 | 05:30 | 1.13552 | 1.13557 | 1.13506 | 1.13517 | 0 |
2022.01.03 | 05:45 | 1.13518 | 1.13591 | 1.13517 | 1.13551 | 0 |
2022.01.03 | 06:00 | 1.13552 | 1.1358 | 1.13514 | 1.13574 | 0 |
2022.01.03 | 06:15 | 1.13575 | 1.13661 | 1.13571 | 1.13604 | 0 |
2022.01.03 | 06:30 | 1.13606 | 1.1362 | 1.13575 | 1.13582 | 0 |
2022.01.03 | 06:45 | 1.13581 | 1.13584 | 1.13518 | 1.13554 | 0 |
2022.01.03 | 07:00 | 1.13554 | 1.13562 | 1.13493 | 1.13552 | 0 |
2022.01.03 | 07:15 | 1.13551 | 1.13561 | 1.13495 | 1.13534 | 0 |
2022.01.03 | 07:30 | 1.13532 | 1.13534 | 1.13465 | 1.13508 | 0 |
2022.01.03 | 07:45 | 1.13507 | 1.13594 | 1.13479 | 1.13586 | 0 |
2022.01.03 | 08:00 | 1.13588 | 1.13588 | 1.13497 | 1.13554 | 0 |
2022.01.03 | 08:15 | 1.13552 | 1.13633 | 1.13508 | 1.13629 | 0 |
2022.01.03 | 08:30 | 1.13628 | 1.13641 | 1.1347 | 1.1352 | 0 |
2022.01.03 | 08:45 | 1.13522 | 1.13531 | 1.13458 | 1.13506 | 0 |
2022.01.03 | 09:00 | 1.13507 | 1.13517 | 1.13375 | 1.13383 | 0 |
2022.01.03 | 09:15 | 1.13384 | 1.13389 | 1.1325 | 1.13262 | 0 |
2022.01.03 | 09:30 | 1.13261 | 1.13291 | 1.13229 | 1.13237 | 0 |
2022.01.03 | 09:45 | 1.13236 | 1.13236 | 1.12997 | 1.13061 | 0 |
2022.01.03 | 10:00 | 1.13064 | 1.13092 | 1.13021 | 1.13041 | 0 |
2022.01.03 | 10:15 | 1.13043 | 1.13093 | 1.12919 | 1.12958 | 0 |
2022.01.03 | 10:30 | 1.12956 | 1.12995 | 1.12928 | 1.12995 | 0 |
2022.01.03 | 10:45 | 1.12996 | 1.13011 | 1.12902 | 1.12915 | 0 |
2022.01.03 | 11:00 | 1.12916 | 1.1297 | 1.12907 | 1.12962 | 0 |
2022.01.03 | 11:15 | 1.12962 | 1.12988 | 1.12888 | 1.12926 | 0 |
2022.01.03 | 11:30 | 1.12924 | 1.12955 | 1.12863 | 1.12869 | 0 |
2022.01.03 | 11:45 | 1.12868 | 1.12913 | 1.12828 | 1.12888 | 0 |
2022.01.03 | 12:00 | 1.12888 | 1.12899 | 1.12825 | 1.12841 | 0 |
2022.01.03 | 12:15 | 1.12843 | 1.12863 | 1.12797 | 1.12817 | 0 |
2022.01.03 | 12:30 | 1.12814 | 1.12848 | 1.12797 | 1.12844 | 0 |
2022.01.03 | 12:45 | 1.12846 | 1.12867 | 1.1282 | 1.12837 | 0 |
2022.01.03 | 13:00 | 1.12837 | 1.12882 | 1.12833 | 1.12876 | 0 |
2022.01.03 | 13:15 | 1.12879 | 1.12919 | 1.12862 | 1.12906 | 0 |
2022.01.03 | 13:30 | 1.12907 | 1.12964 | 1.12905 | 1.12964 | 0 |
2022.01.03 | 13:45 | 1.12964 | 1.12969 | 1.12937 | 1.12948 | 0 |
2022.01.03 | 14:00 | 1.12948 | 1.12982 | 1.12936 | 1.12981 | 0 |
2022.01.03 | 14:15 | 1.12983 | 1.12986 | 1.12959 | 1.12979 | 0 |
2022.01.03 | 14:30 | 1.12981 | 1.12995 | 1.1295 | 1.12956 | 0 |
2022.01.03 | 14:45 | 1.12956 | 1.12992 | 1.12949 | 1.12971 | 0 |
2022.01.03 | 15:00 | 1.1297 | 1.1299 | 1.1296 | 1.12962 | 0 |
2022.01.03 | 15:15 | 1.12962 | 1.1299 | 1.12958 | 1.12966 | 0 |
2022.01.03 | 15:30 | 1.12964 | 1.13003 | 1.12959 | 1.12964 | 0 |
2022.01.03 | 15:45 | 1.12964 | 1.12975 | 1.12937 | 1.12963 | 0 |
2022.01.03 | 16:00 | 1.12963 | 1.12971 | 1.12943 | 1.12963 | 0 |
2022.01.03 | 16:15 | 1.12963 | 1.12972 | 1.1296 | 1.1297 | 0 |
2022.01.03 | 16:30 | 1.12973 | 1.12992 | 1.12973 | 1.12981 | 0 |
2022.01.03 | 16:45 | 1.12982 | 1.12992 | 1.12965 | 1.12965 | 0 |
2022.01.03 | 17:00 | 1.12965 | 1.12968 | 1.12965 | 1.12965 | 0 |
2022.01.03 | 17:15 | 1.12967 | 1.12982 | 1.12929 | 1.12948 | 0 |
2022.01.03 | 17:30 | 1.12948 | 1.12963 | 1.12945 | 1.12947 | 0 |
2022.01.03 | 17:45 | 1.12947 | 1.12961 | 1.12945 | 1.12945 | 0 |
2022.01.03 | 18:00 | 1.12948 | 1.12976 | 1.12946 | 1.12975 | 0 |
End of preview.
No dataset card yet
- Downloads last month
- 2