SDWPF: A Dataset for Spatial Dynamic Wind Power Forecasting Challenge at KDD Cup 2022
Paper • 2208.04360 • Published • 1
Datasets:
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.
kdd_cup_2022 (TsFile format)
This repository contains time-series forecasting data stored in Apache TsFile format.
Summary
- FEV subset:
kdd_cup_2022 - Unified source collection:
autogluon/fev_datasets - Original source: https://aistudio.baidu.com/competition/detail/152/0/task-definition
- Paper / citation: [14]
- Series: 134
- Modalities: Time-series
- TsFile rows (flattened observations): 63,355,200
- Frequencies: 10T, 1D, 30T
- TsFile files: 8
- 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 |
|---|---|---|---|---|---|---|
| 10T | 134 | 35,279 | 47,273,860 | 10 | 0 | 10T/10T_1..10T_5.tsfile (5 shards) |
| 1D | 134 | 243 | 325,620 | 10 | 0 | 1D/1D.tsfile |
| 30T | 134 | 11,758 | 15,755,720 | 10 | 0 | 30T/30T_1..30T_2.tsfile (2 shards) |
Files
The Hugging Face dataset card YAML points configs.data_files to all *.tsfile files in this repository.
10T/10T_1.tsfile10T/10T_2.tsfile10T/10T_3.tsfile10T/10T_4.tsfile10T/10T_5.tsfile1D/1D.tsfile30T/30T_1.tsfile30T/30T_2.tsfile
TsFile Storage Model
- Each original series (
id) is stored as one TsFile device. - Time-varying targets and dynamic covariates are stored as FIELD measurements.
- Source
timestampvalues are mapped to the TsFileTimecolumn as millisecond timestamps. - Table name(s): kdd_cup_2022_10T, kdd_cup_2022_1D, kdd_cup_2022_30T.
Column Schema
| Column | Role | TsFile type |
|---|---|---|
Time |
Time column | INT64 |
id |
TAG (device dimension) | STRING |
Wspd |
FIELD (measurement) | FLOAT |
Wdir |
FIELD (measurement) | FLOAT |
Etmp |
FIELD (measurement) | FLOAT |
Itmp |
FIELD (measurement) | FLOAT |
Ndir |
FIELD (measurement) | FLOAT |
Pab1 |
FIELD (measurement) | FLOAT |
Pab2 |
FIELD (measurement) | FLOAT |
Pab3 |
FIELD (measurement) | FLOAT |
Prtv |
FIELD (measurement) | FLOAT |
Patv |
FIELD (measurement) | FLOAT |
Note: 402 original
idvalues contained invalid identifier characters and were normalized to valid device names, for example 1→_1, 10→_10, 100→_100.
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 rowsvalues 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
.tsfileshards 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("10T/10T_1.tsfile")
schemas = reader.get_all_table_schemas()
# Table name(s): kdd_cup_2022_10T, kdd_cup_2022_1D, kdd_cup_2022_30T
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