After some discussions and couple of proofs of concept, pandas has decided to move our build system to Meson, from the existing setuptools one (i.e. setup.py build_ext). This is a step other projects in the ecosystem like NumPY already took. The pandas codebase contains a large amount of Cython files that need to be compiled, and using Meson should speed up things and make the build configuration more maintainable.

The main discussion happened in https://github.com/pandas-dev/pandas/pull/47988, thanks core developer Will Ayd for leading the change.

We are happy to announce the release candidate of pandas 1.5.0.

It can be installed from our conda-forge and PyPI packages via mamba, conda and pip, for example:

mamba install -c conda-forge/label/pandas_rc pandas==1.5.0rc0
python -m pip install --upgrade --pre pandas==1.5.0rc0

Users having pandas code in production and maintainers of libraries with pandas as a dependency are strongly recommended to run their test suites with the release candidate, and report any breaking change to our issue tracker before the official 1.5.0 release.

You can find the documentation of pandas 1.5.0 here, and the list of changes in 1.5.0, in the release notes page.

We expect to release the final version of pandas 1.5.0 on September 7th, but the final date will depend on the issues reported to the release candidate.

We are pleased to announce the release of pandas v1.5.0.

This release includes some new features, bug fixes and performance improvements.

See the release notes for a list of all the changes.

The release can be installed from PyPI

python -m pip install --upgrade pandas==1.5.0

Or from conda-forge

mamba install -c conda-forge pandas=1.5.0

Packages for ARM and PowerPC are still being built, and will be available in the next hours.

Please report any issues with the release on the pandas issue tracker.

This release has been made possible thanks to around 260 contributors. 22 being core developers, and around 70% being first time contributors. It has also been possible thanks to the organisations supporting the development of pandas: NumFOCUS, Two Sigma, Voltron Data, d-fine, Quansight, NVIDIA, Tidelift, Chan Zuckerberg Initiative and Bodo.

We are renewing our code of conduct committee. Please apply if you want to help pandas make sure we are the welcoming, inclusive and diverse community we want to be: https://forms.gle/vEY1uhHd1kTco5ja8

Last few hours to apply to become a member of the pandas code of conduct committee: https://forms.gle/vEY1uhHd1kTco5ja8

We are happy to announce that Luke Manley has been promoted to the pandas core development team. Luke has been doing a great job improving pandas performance. You can find the full list of pandas maintainers in our team page. Welcome Luke!

If you are interested in contributing to pandas, and don't know where to start, you can join the first new contributors meeting next week.

https://pandas.pydata.org/docs/development/meeting.html#calendar

We are pleased to announce the release of pandas v1.5.1.

This is a patch release in the 1.5.x series and includes some regression fixes and bug fixes. We recommend that all users in the 1.5.x series upgrade to this version.

See the release notes for a list of all the changes.

The release can be installed from PyPI

python -m pip install --upgrade pandas==1.5.1

Or from conda-forge

mamba install -c conda-forge pandas==1.5.1

We are now in Mastodon, you can follow us at: https://fosstodon.org/@pandas_dev/

Next new contributors meeting is tomorrow, you're welcome to join if you want to contribute to pandas and would appreciate some guidance and engage with new and existing contributors. https://pandas.pydata.org/docs/development/meeting.html#calendar

We are pleased to announce the release of pandas v1.5.2.

This is a patch release in the 1.5.x series and includes some regression fixes and bug fixes. We recommend that all users in the 1.5.x series upgrade to this version.

See the release notes for a list of all the changes.

The release can be installed from PyPI

python -m pip install --upgrade pandas==1.5.2

Or from conda-forge

mamba install -c conda-forge pandas==1.5.2

We are pleased to announce the release of pandas v1.5.3.

This is a patch release in the 1.5.x series and includes some regression fixes and bug fixes. We recommend that all users in the 1.5.x series upgrade to this version.

See the release notes for a list of all the changes.

The release can be installed from PyPI

python -m pip install --upgrade pandas==1.5.3

Or from conda-forge

mamba install -c conda-forge pandas==1.5.3

We are happy to announce the release candidate of pandas 2.0.0.

It can be installed from our conda-forge and PyPI packages via mamba, conda and pip, for example:

mamba install -c conda-forge/label/pandas_rc pandas==2.0.0rc0
python -m pip install --upgrade --pre pandas==2.0.0rc0

Users having pandas code in production and maintainers of libraries with pandas as a dependency are strongly recommended to run their test suites with the release candidate, and report any breaking change to our issue tracker before the official 2.0.0 release.

You can find the documentation of pandas 2.0.0 here, and the list of changes in 2.0.0, in the release notes page.

We expect to release the final version of pandas 2.0.0 in around two, but the final date will depend on the issues reported to the release candidate.

#pandas 2.0 will be released soon. I wrote about one of the most important changes we're shipping with it.

https://datapythonista.me/blog/pandas-20-and-the-arrow-revolution-part-i

Today is release day, and I'm tweeting live all the pandas 2.0 release progress:

https://mobile.twitter.com/datapythonista/status/1642779019476123649

We're happy to announce the release of #pandas 2.0.0.

You can install it with pip install pandas or mamba install -c conda-forge pandas.

You can find what's new in this version in the release notes.

Thanks to all contributors and sponsors who made this release possible!

https://pandas.pydata.org/pandas-docs/version/2.0.0/whatsnew/v2.0.0.html

pandas 2.0.1 has just been released. The new version contain bug fixes to the recent 2.0.0 release, making 2.0 more stable. New features are being added to the 2.1 version which will be released in few months.

You can install the new release as usual via pip and mamba/conda.

We are excited to share that #pandas 2.0.2 has just been released. Users in the 2.0.x series are recommended to upgrade to this version.

Full list of changes and contributors: https://pandas.pydata.org/docs/whatsnew/v2.0.2.html

Several pandas maintainers will join the Python Dataframe Summit 2023 to discuss the future of dataframes: https://df-summit-23.pydata.org/

Major sponsors of the participating projects like #pandas are invited to join the discussions.