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Datasets:
Skyoung13
/
TimeSeriesRepo

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Time-series
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1M - 10M
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The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
item_id: string
start: timestamp[s]
freq: string
target: fixed_size_list<item: list<item: float>>[2]
  child 0, item: list<item: float>
      child 0, item: float
-- schema metadata --
huggingface: '{"info": {"features": {"item_id": {"dtype": "string", "_typ' + 247
to
{'item_id': Value(dtype='string', id=None), 'start': Value(dtype='timestamp[s]', id=None), 'freq': Value(dtype='string', id=None), 'target': Sequence(feature=Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), length=2, id=None), 'past_feat_dynamic_real': Sequence(feature=Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), length=11, id=None)}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1995, in _prepare_split_single
                  for _, table in generator:
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 797, in wrapped
                  for item in generator(*args, **kwargs):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/arrow/arrow.py", line 71, in _generate_tables
                  yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/arrow/arrow.py", line 59, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_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
              item_id: string
              start: timestamp[s]
              freq: string
              target: fixed_size_list<item: list<item: float>>[2]
                child 0, item: list<item: float>
                    child 0, item: float
              -- schema metadata --
              huggingface: '{"info": {"features": {"item_id": {"dtype": "string", "_typ' + 247
              to
              {'item_id': Value(dtype='string', id=None), 'start': Value(dtype='timestamp[s]', id=None), 'freq': Value(dtype='string', id=None), 'target': Sequence(feature=Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), length=2, id=None), 'past_feat_dynamic_real': Sequence(feature=Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), length=11, id=None)}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1524, 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 1099, in stream_convert_to_parquet
                  builder._prepare_split(
                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 2038, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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item_id
string
start
timestamp[s]
freq
string
target
sequence
past_feat_dynamic_real
sequence
0
2016-02-29T05:00:00
30T
[[55.0,123.0,207.0,341.0,526.0,709.0,1196.0,1595.0,1854.0,2558.0,2756.0,2528.0,2643.0,2203.0,1627.0,(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
1
2016-02-29T05:00:00
30T
[[26.0,43.0,58.0,132.0,207.0,323.0,370.0,617.0,991.0,1241.0,1723.0,1917.0,1625.0,1259.0,1027.0,691.0(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
2
2016-02-29T05:00:00
30T
[[18.0,35.0,68.0,118.0,254.0,393.0,542.0,741.0,906.0,1174.0,1248.0,1344.0,1248.0,1034.0,777.0,614.0,(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
3
2016-02-29T05:00:00
30T
[[12.0,46.0,80.0,77.0,159.0,245.0,468.0,880.0,1335.0,1614.0,1835.0,1980.0,1831.0,1472.0,1189.0,835.0(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
4
2016-02-29T05:00:00
30T
[[15.0,21.0,48.0,78.0,171.0,243.0,456.0,768.0,1124.0,1395.0,1761.0,2108.0,1996.0,1454.0,1209.0,805.0(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
5
2016-02-29T05:00:00
30T
[[10.0,20.0,34.0,78.0,90.0,179.0,328.0,482.0,738.0,854.0,1029.0,1204.0,1087.0,1037.0,720.0,630.0,471(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
6
2016-02-29T05:00:00
30T
[[6.0,12.0,22.0,43.0,59.0,141.0,198.0,332.0,515.0,601.0,776.0,844.0,681.0,582.0,473.0,439.0,304.0,28(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
7
2016-02-29T05:00:00
30T
[[2.0,10.0,8.0,16.0,34.0,47.0,87.0,121.0,178.0,221.0,326.0,427.0,396.0,354.0,244.0,200.0,166.0,164.0(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
8
2016-02-29T05:00:00
30T
[[7.0,15.0,19.0,21.0,45.0,65.0,119.0,190.0,245.0,292.0,505.0,517.0,501.0,445.0,391.0,273.0,221.0,176(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
9
2016-02-29T05:00:00
30T
[[2.0,4.0,20.0,21.0,37.0,53.0,117.0,153.0,223.0,335.0,451.0,586.0,507.0,450.0,344.0,268.0,236.0,169.(...TRUNCATED)
[[0.032260000705718994,0.032260000705718994,0.06452000141143799,0.06452000141143799,0.03226000070571(...TRUNCATED)
End of preview.

NetMan Time Series Repo

The NetMan Time Series Repo is a collection of open time series datasets for time series forecasting. It was collected for the purpose of pre-training Large Time Series Models.

Downloads last month
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Size of the auto-converted Parquet files (First 5GB per split):
4.85 GB
Number of rows (First 5GB per split):
143,716
Estimated number of rows:
1,783,011