Hugging Face's logo

Datasets:
VGalaxies666
/
rossmann

Tasks:
Time Series Forecasting
Sub-tasks:
univariate-time-series-forecasting
multivariate-time-series-forecasting
Size:
100K<n<1M
Tags:
time-series
forecasting
benchmark
fev
tsfile
apache-tsfile
License:
Dataset card Files
xet
 Community
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
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.

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.

rossmann (TsFile format)

This repository contains time-series forecasting data stored in Apache TsFile format.

Summary

Licensing and citation requirements follow the original source. This repository does not claim ownership of the original data.

Dataset Statistics

Frequency Series Median series length TsFile rows (observations) Dynamic columns Static columns Data files
1D 1,115 942 7,352,310 7 10 1D/1D_1..1D_2.tsfile (2 shards)
1W 1,115 133 889,770 6 10 1W/1W.tsfile

Files

The Hugging Face dataset card YAML points configs.data_files to all *.tsfile files in this repository.

  • 1D/1D_1.tsfile
  • 1D/1D_2.tsfile
  • 1W/1W.tsfile

TsFile Storage Model

  • Each original series (id) is stored as one TsFile device.
  • Static covariate columns are stored as TAG columns: Store, StoreType, Assortment, CompetitionDistance, CompetitionOpenSinceMonth, CompetitionOpenSinceYear, Promo2, Promo2SinceWeek, Promo2SinceYear, PromoInterval.
  • Time-varying targets and dynamic covariates are stored as FIELD measurements.
  • Source timestamp values are mapped to the TsFile Time column as millisecond timestamps.
  • Table name(s): rossmann_1D, rossmann_1W.

Column Schema

Column Role TsFile type
Time Time column INT64
id TAG (device dimension) STRING
Store TAG (device dimension) DOUBLE
StoreType TAG (device dimension) STRING
Assortment TAG (device dimension) STRING
CompetitionDistance TAG (device dimension) DOUBLE
CompetitionOpenSinceMonth TAG (device dimension) DOUBLE
CompetitionOpenSinceYear TAG (device dimension) DOUBLE
Promo2 TAG (device dimension) DOUBLE
Promo2SinceWeek TAG (device dimension) DOUBLE
Promo2SinceYear TAG (device dimension) DOUBLE
PromoInterval TAG (device dimension) STRING
DayOfWeek FIELD (measurement) FLOAT
Sales FIELD (measurement) FLOAT
Customers FIELD (measurement) FLOAT
Open FIELD (measurement) FLOAT
Promo FIELD (measurement) FLOAT
StateHoliday FIELD (measurement) STRING
SchoolHoliday FIELD (measurement) FLOAT

Note: 2230 original id values contained invalid identifier characters and were normalized to valid device names, for example 1→_1, 2→_2, 3→_3.

Conversion Notes

  • The source FEV format stores each time series as one nested row containing id, timestamp[], and target or covariate arrays.
  • The TsFile conversion flattens those nested arrays into long rows. Therefore, the TsFile rows values above correspond to the number of timestamped observations after flattening.
  • TAG columns identify the device and static metadata. FIELD columns contain values that change over time.
  • Large logical tables may be split into multiple .tsfile shards such as <name>_1.tsfile, <name>_2.tsfile, and so on. Shards listed for the same frequency belong to the same logical table.

Reading Example 

from tsfile import TsFileReader

reader = TsFileReader("1D/1D_1.tsfile")
schemas = reader.get_all_table_schemas()
# Table name(s): rossmann_1D, rossmann_1W
Downloads last month
17
Total file size:
9.02 MB