Datasets:
Pyrregular: Irregular Time Series Datasets and Benchmarks
Published at ICLR 2026 · 38 datasets, including the benchmark of 34 datasets and 12 classifiers · GitHub · Documentation · PyPI · Paper
Naturally irregular time series (uneven sampling, missing observations, signals recorded at different times, variable-length sequences) in one standardized format, for classification and regression. These are the datasets of the pyrregular Python library, including the 34 of the ICLR 2026 benchmark. The files are HDF5, read by the library (the dataset viewer is off):
pip install pyrregular
from pyrregular import load_dataset
df = load_dataset("Garment.h5")
The files are versioned with git tags (data-v1, ...); each pyrregular release
downloads one fixed version.
Licenses
Each dataset keeps the license of its original source; we redistribute it in a
converted format, with attribution. unknown means the source states no license
(most of these come from the UEA & UCR time series archive). If you hold the rights
to a dataset and want it removed or its attribution changed, please open an issue
at https://github.com/fspinna/pyrregular/issues.
| Dataset | License | Source | Citation |
|---|---|---|---|
| Abf | CC-BY-4.0 | source | cite |
| Ais | CC-BY-4.0 | source | cite |
| AllGestureWiimoteX | unknown | source | cite |
| AllGestureWiimoteY | unknown | source | cite |
| AllGestureWiimoteZ | unknown | source | cite |
| Animals | other | source | cite |
| AsphaltObstaclesCoordinates | unknown | source | cite |
| AsphaltPavementTypeCoordinates | unknown | source | cite |
| AsphaltRegularityCoordinates | unknown | source | cite |
| CharacterTrajectories | CC-BY-4.0 | source | cite |
| CombinedTrajectories | CC-BY-NC-SA-4.0 | source | cite |
| DodgerLoopDay | CC-BY-4.0 | source | cite |
| DodgerLoopGame | CC-BY-4.0 | source | cite |
| DodgerLoopWeekend | CC-BY-4.0 | source | cite |
| Garment | CC-BY-4.0 | source | cite |
| Geolife | unknown | source | cite |
| GeolifeSupervised | unknown | source | cite |
| GestureMidAirD1 | unknown | source | cite |
| GestureMidAirD2 | unknown | source | cite |
| GestureMidAirD3 | unknown | source | cite |
| GesturePebbleZ1 | unknown | source | cite |
| GesturePebbleZ2 | unknown | source | cite |
| InsectWingbeat | unknown | source | cite |
| JapaneseVowels | CC-BY-4.0 | source | cite |
| Ldfpa | CC-BY-4.0 | source | cite |
| MelbournePedestrian | CC-BY-4.0 | source | cite |
| Mimic3 | ODbL-1.0 | source | cite |
| PLAID | CC-BY-4.0 | source | cite |
| Pamap2 | CC-BY-4.0 | source | cite |
| Physionet2012 | ODC-By-1.0 | source | cite |
| Physionet2019 | CC-BY-4.0 | source | cite |
| PickupGestureWiimoteZ | unknown | source | cite |
| Seabirds | CC0-1.0 | source | cite |
| ShakeGestureWiimoteZ | unknown | source | cite |
| SpokenArabicDigits | CC-BY-4.0 | source | cite |
| TDrive | unknown | source | cite |
| Taxi | CC-BY-4.0 | source | cite |
| Vehicles | unknown | source | cite |
Citation
Please cite the original source of each dataset (Citation column) and pyrregular:
@inproceedings{
spinnato2026pyrregular,
title={{PYRREGULAR}: A Unified Framework for Irregular Time Series, with Classification Benchmarks},
author={Francesco Spinnato and Cristiano Landi},
booktitle={The Fourteenth International Conference on Learning Representations},
year={2026},
url={https://openreview.net/forum?id=qetBM8nLkf}
}
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