Datasets:

VGalaxies666
/

rohlik_sales

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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rohlik_sales (TsFile format)

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

Summary

FEV subset: rohlik_sales
Unified source collection: autogluon/fev_datasets
Original source: https://www.kaggle.com/competitions/rohlik-sales-forecasting-challenge-v2
Paper / citation: [20]
Series: 5,390 / 5,243
Modalities: Time-series
TsFile rows (flattened observations): 84,930,705
Frequencies: 1D, 1W
TsFile files: 6
Time precision: milliseconds (INT64).

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	5,390	1,046	74,413,935	15	7	`1D/1D_1..1D_5.tsfile` (5 shards)
1W	5,243	150	10,516,770	15	7	`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
1D/1D_3.tsfile
1D/1D_4.tsfile
1D/1D_5.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: product_unique_id, name, L1_category_name_en, L2_category_name_en, L3_category_name_en, L4_category_name_en, warehouse.
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): rohlik_sales_1D, rohlik_sales_1W.

Column Schema

Column	Role	TsFile type
`Time`	Time column	INT64
`id`	TAG (device dimension)	STRING
`product_unique_id`	TAG (device dimension)	DOUBLE
`name`	TAG (device dimension)	STRING
`L1_category_name_en`	TAG (device dimension)	STRING
`L2_category_name_en`	TAG (device dimension)	STRING
`L3_category_name_en`	TAG (device dimension)	STRING
`L4_category_name_en`	TAG (device dimension)	STRING
`warehouse`	TAG (device dimension)	STRING
`total_orders`	FIELD (measurement)	FLOAT
`sales`	FIELD (measurement)	FLOAT
`sell_price_main`	FIELD (measurement)	FLOAT
`availability`	FIELD (measurement)	FLOAT
`type_0_discount`	FIELD (measurement)	FLOAT
`type_1_discount`	FIELD (measurement)	FLOAT
`type_2_discount`	FIELD (measurement)	FLOAT
`type_3_discount`	FIELD (measurement)	FLOAT
`type_4_discount`	FIELD (measurement)	FLOAT
`type_5_discount`	FIELD (measurement)	FLOAT
`type_6_discount`	FIELD (measurement)	FLOAT
`holiday`	FIELD (measurement)	FLOAT
`shops_closed`	FIELD (measurement)	FLOAT
`winter_school_holidays`	FIELD (measurement)	FLOAT
`school_holidays`	FIELD (measurement)	FLOAT

Note: 10633 original id values contained invalid identifier characters and were normalized to valid device names, for example 0→_0, 1→_1, 2→_2.

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): rohlik_sales_1D, rohlik_sales_1W

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