README.md

---
pretty_name: pyrregular
viewer: false
license:
- cc-by-4.0
- cc-by-nc-sa-4.0
- cc0-1.0
- odbl
- odc-by
- other
- unknown
license_name: dataset-specific
---

![Pyrregular: irregular time series datasets and benchmarks](https://github.com/fspinna/pyrregular/blob/main/assets/images/logo_01.png?raw=true)

# Pyrregular: Irregular Time Series Datasets and Benchmarks

**Published at ICLR 2026** · 38 datasets, including the benchmark of
34 datasets and 12 classifiers ·
[GitHub](https://github.com/fspinna/pyrregular) · [Documentation](https://fspinna.github.io/pyrregular/) ·
[PyPI](https://pypi.org/project/pyrregular/) ·
[Paper](https://openreview.net/forum?id=qetBM8nLkf)

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](https://github.com/fspinna/pyrregular) Python library, including the 34 of the ICLR 2026
benchmark. The files are HDF5, read by the library (the dataset viewer is off):

```bash
pip install pyrregular
```

```python
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](https://arxiv.org/abs/2505.06047) |
| Ais | [CC-BY-4.0](https://zenodo.org/records/8064564) | [source](https://zenodo.org/records/8064564) | [cite](https://doi.org/10.5281/zenodo.8064564) |
| AllGestureWiimoteX | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=AllGestureWiimoteX) |
| AllGestureWiimoteY | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=AllGestureWiimoteY) |
| AllGestureWiimoteZ | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=AllGestureWiimoteZ) |
| Animals | [other](https://research.fs.usda.gov/pnw/projects/starkeyproject) | [source](https://dl.acm.org/doi/pdf/10.1145/3167132.3167225) | [cite](https://doi.org/10.1145/3167132.3167225) |
| AsphaltObstaclesCoordinates | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=AsphaltObstaclesCoordinates) |
| AsphaltPavementTypeCoordinates | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=AsphaltPavementTypeCoordinates) |
| AsphaltRegularityCoordinates | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=AsphaltRegularityCoordinates) |
| CharacterTrajectories | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/175/character+trajectories) | [source](https://timeseriesclassification.com/) | [cite](https://doi.org/10.24432/C58G7V) |
| CombinedTrajectories | [CC-BY-NC-SA-4.0](https://www.kaggle.com/datasets/donotmess/combined-trajectories) | [source](https://www.kaggle.com/datasets/donotmess/combined-trajectories) | [cite](https://www.kaggle.com/datasets/donotmess/combined-trajectories) |
| DodgerLoopDay | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/157/dodgers+loop+sensor) | [source](https://timeseriesclassification.com/) | [cite](https://doi.org/10.24432/C51P50) |
| DodgerLoopGame | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/157/dodgers+loop+sensor) | [source](https://timeseriesclassification.com/) | [cite](https://doi.org/10.24432/C51P50) |
| DodgerLoopWeekend | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/157/dodgers+loop+sensor) | [source](https://timeseriesclassification.com/) | [cite](https://doi.org/10.24432/C51P50) |
| Garment | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/597/productivity+prediction+of+garment+employees) | [source](https://archive.ics.uci.edu/dataset/597/productivity+prediction+of+garment+employees) | [cite](https://doi.org/10.24432/C51S6D) |
| Geolife | [unknown](https://www.microsoft.com/en-us/download/details.aspx?id=52367) | [source](https://www.microsoft.com/en-us/download/details.aspx?id=52367) | [cite](https://www.microsoft.com/en-us/research/publication/geolife-gps-trajectory-dataset-user-guide/) |
| GeolifeSupervised | [unknown](https://www.microsoft.com/en-us/download/details.aspx?id=52367) | [source](https://www.microsoft.com/en-us/download/details.aspx?id=52367) | [cite](https://www.microsoft.com/en-us/research/publication/geolife-gps-trajectory-dataset-user-guide/) |
| GestureMidAirD1 | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=GestureMidAirD1) |
| GestureMidAirD2 | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=GestureMidAirD2) |
| GestureMidAirD3 | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=GestureMidAirD3) |
| GesturePebbleZ1 | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=GesturePebbleZ1) |
| GesturePebbleZ2 | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=GesturePebbleZ2) |
| InsectWingbeat | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=InsectWingbeat) |
| JapaneseVowels | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/128/japanese+vowels) | [source](https://timeseriesclassification.com/) | [cite](https://doi.org/10.24432/C5NS47) |
| Ldfpa | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/196/localization+data+for+person+activity) | [source](https://archive.ics.uci.edu/dataset/196/localization+data+for+person+activity) | [cite](https://doi.org/10.24432/C57G8X) |
| MelbournePedestrian | [CC-BY-4.0](https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/) | [source](https://timeseriesclassification.com/) | [cite](https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/) |
| Mimic3 | [ODbL-1.0](https://physionet.org/content/mimiciii-demo/1.4/) | [source](https://physionet.org/content/mimiciii-demo/1.4/) | [cite](https://doi.org/10.13026/C2HM2Q) |
| PLAID | [CC-BY-4.0](https://figshare.com/articles/PLAID_2014/11605074) | [source](https://timeseriesclassification.com/) | [cite](https://doi.org/10.6084/m9.figshare.11605074) |
| Pamap2 | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/231/pamap2+physical+activity+monitoring) | [source](https://archive.ics.uci.edu/dataset/231/pamap2+physical+activity+monitoring) | [cite](https://doi.org/10.24432/C5NW2H) |
| Physionet2012 | [ODC-By-1.0](https://physionet.org/content/challenge-2012/1.0.0/) | [source](https://physionet.org/content/challenge-2012/1.0.0/) | [cite](https://physionet.org/content/challenge-2012/1.0.0/) |
| Physionet2019 | [CC-BY-4.0](https://physionet.org/content/challenge-2019/1.0.0/) | [source](https://physionet.org/content/challenge-2019/1.0.0/) | [cite](https://doi.org/10.13026/v64v-d857) |
| PickupGestureWiimoteZ | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=PickupGestureWiimoteZ) |
| Seabirds | [CC0-1.0](https://datadryad.org/dataset/doi:10.5061/dryad.t7ck5) | [source](https://doi.org/10.5061/dryad.t7ck5) | [cite](https://doi.org/10.5061/dryad.t7ck5) |
| ShakeGestureWiimoteZ | unknown | [source](https://timeseriesclassification.com/) | [cite](https://timeseriesclassification.com/description.php?Dataset=ShakeGestureWiimoteZ) |
| SpokenArabicDigits | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/195/spoken+arabic+digit) | [source](https://timeseriesclassification.com/) | [cite](https://doi.org/10.24432/C52C9Q) |
| TDrive | [unknown](https://www.microsoft.com/en-us/research/publication/t-drive-trajectory-data-sample/) | [source](https://www.microsoft.com/en-us/research/publication/t-drive-trajectory-data-sample/) | [cite](https://doi.org/10.1145/2020408.2020462) |
| Taxi | [CC-BY-4.0](https://archive.ics.uci.edu/dataset/339/taxi+service+trajectory+prediction+challenge+ecml+pkdd+2015) | [source](https://archive.ics.uci.edu/dataset/339/taxi+service+trajectory+prediction+challenge+ecml+pkdd+2015) | [cite](https://doi.org/10.24432/C55W25) |
| Vehicles | unknown | [source](https://dl.acm.org/doi/pdf/10.1145/3167132.3167225) | [cite](https://doi.org/10.1145/3167132.3167225) |

## Citation

Please cite the original source of each dataset (Citation column) and pyrregular:

```bibtex
@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}
}
```