Datasets:

VGalaxies666
/

kaggle_web_traffic

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
              tsfile.exceptions.FileOpenError: 28: 
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
                  scan = self._scan_metadata(all_files)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
                  with self._open_reader(file) as reader:
                       ~~~~~~~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
                  return TsFileReader(file)
                File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
              SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
              
              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/split_names.py", line 66, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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kaggle_web_traffic (TsFile format)

145063 daily time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2017-09-10.

This repository contains the full source .tsf series from the Monash Time Series Forecasting Repository converted to Apache TsFile format.

Summary

Source dataset: Monash-University/monash_tsf
Original source: https://zenodo.org/record/4656080
Monash subset: kaggle_web_traffic
Modalities: Time-series
Source series: 145,063
Rows: 116,485,589 flattened timestamped observations
Frequency: daily
Forecast horizon metadata: 59
Missing-values metadata: True
Equal-length metadata: True
Missing target values preserved as NaN: 7,027,348
Series length range: 803 to 803
TsFile output: 117 files (kaggle_web_traffic_1.tsfile .. kaggle_web_traffic_99.tsfile)

Files

kaggle_web_traffic_1.tsfile
kaggle_web_traffic_10.tsfile
kaggle_web_traffic_100.tsfile
kaggle_web_traffic_101.tsfile
kaggle_web_traffic_102.tsfile
kaggle_web_traffic_103.tsfile
kaggle_web_traffic_104.tsfile
kaggle_web_traffic_105.tsfile
kaggle_web_traffic_106.tsfile
kaggle_web_traffic_107.tsfile
kaggle_web_traffic_108.tsfile
kaggle_web_traffic_109.tsfile
kaggle_web_traffic_11.tsfile
kaggle_web_traffic_110.tsfile
kaggle_web_traffic_111.tsfile
kaggle_web_traffic_112.tsfile
kaggle_web_traffic_113.tsfile
kaggle_web_traffic_114.tsfile
kaggle_web_traffic_115.tsfile
kaggle_web_traffic_116.tsfile
kaggle_web_traffic_117.tsfile
kaggle_web_traffic_12.tsfile
kaggle_web_traffic_13.tsfile
kaggle_web_traffic_14.tsfile
kaggle_web_traffic_15.tsfile
kaggle_web_traffic_16.tsfile
kaggle_web_traffic_17.tsfile
kaggle_web_traffic_18.tsfile
kaggle_web_traffic_19.tsfile
kaggle_web_traffic_2.tsfile
... 87 more .tsfile shards

TsFile Schema

Column	Role	TsFile type
`Time`	TIME	INT64
`series_id`	TAG	STRING
`series_name`	TAG	STRING
`start_timestamp`	TAG	STRING
`target`	FIELD	FLOAT

Conversion Notes

Each source .tsf data row is stored as one TsFile device.
Source .tsf attributes are stored as TAG columns.
The target series values are flattened into timestamped rows and stored as a FLOAT FIELD.
Time is synthesized from the source start timestamp and the .tsf frequency metadata, with millisecond precision.
Large outputs may be sharded by the TsFile conversion tool; all listed shards belong to the same logical table kaggle_web_traffic.

Reading Example

from tsfile import TsFileReader

reader = TsFileReader("kaggle_web_traffic_1.tsfile")
schemas = reader.get_all_table_schemas()

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Total file size:

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