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Update docs (#448)
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WenjieDu authored Jun 26, 2024
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -161,7 +161,7 @@ And what else? Please read on ;-)
👈 Time series datasets are taken as coffee beans at PyPOTS, and POTS datasets are incomplete coffee beans with missing parts that have their own meanings.
To make various public time-series datasets readily available to users,
<i>Time Series Data Beans (TSDB)</i> is created to make loading time-series datasets super easy!
Visit [TSDB](https://github.com/WenjieDu/TSDB) right now to know more about this handy tool 🛠, and it now supports a total of 170 open-source datasets!
Visit [TSDB](https://github.com/WenjieDu/TSDB) right now to know more about this handy tool 🛠, and it now supports a total of 172 open-source datasets!

<a href="https://github.com/WenjieDu/PyGrinder">
<img src="https://pypots.com/figs/pypots_logos/PyGrinder/logo_FFBG.svg" align="right" width="140" alt="PyGrinder logo"/>
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8 changes: 2 additions & 6 deletions docs/index.rst
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Expand Up @@ -220,7 +220,7 @@ And what else? Please read on ;-)
👈 Time series datasets are taken as coffee beans at PyPOTS, and POTS datasets are incomplete coffee beans with missing parts that have their own meanings.
To make various public time-series datasets readily available to users,
*Time Series Data Beans (TSDB)* is created to make loading time-series datasets super easy!
Visit `TSDB <https://github.com/WenjieDu/TSDB>`_ right now to know more about this handy tool 🛠, and it now supports a total of 170 open-source datasets!
Visit `TSDB <https://github.com/WenjieDu/TSDB>`_ right now to know more about this handy tool 🛠, and it now supports a total of 172 open-source datasets!

.. image:: https://pypots.com/figs/pypots_logos/PyGrinder/logo_FFBG.svg
:width: 150
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@article{du2023pypots,
title={{PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series}},
author={Wenjie Du},
journal={arXiv preprint arXiv:2305.18811},
year={2023},
eprint={2305.18811},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2305.18811},
doi={10.48550/arXiv.2305.18811},
}
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