pandas is now in Open Collective, where you can see the project finances. Expenses and more details are still being added, but the main sources of income of the project are already available.

You will also find in Open Collective the rest of NumFOCUS supported projects, such as Jupyter, SciPy, etc.

The book "Python for Data Analysis", by original pandas creator Wes McKinney, has an open access version of it's 3rd edition, with all chapters.

https://wesmckinney.com/book/

Bodo has just become a pandas and NumFOCUS financial supporter. Bodo is a just in time compiler that allows executing pandas code in a parallel way without running the pandas underlying code based on NumPy. This should help run pandas code faster and at scale. Bodo funds will be used to improve pandas API, and will contribute to pandas general maintenance and to the wider community.

pandas is adopting PDEPs, similar to PEPs in Python and NEPs in NumPy. The formal proposal process should make discussions more efficients, and future plans clearer and more visible. First PDEP about PDEPs workflow has been proposed and is accepting (and welcoming) feedback:

https://github.com/pandas-dev/pandas/pull/47444

There is now a browser-based interactive terminal in the pandas website: https://pandas.pydata.org/getting_started.html

The Python interpreter and dependencies are shipped as a WebAssembly binary, and it doesn't use a backend, everything you run is executed locally in the browser process. The only limitation is that the browser runs in it a sandbox, and I/O is limited. For example, downloading files from other websites is not allowed due to cross-domain (CORS) limitations.

pandas-stubs 1.4.2.220622 has been released. This is the first official version of pandas-stubs by the pandas team, after merging the two third-party projects Microsoft python-type-stubs and VirtusLabs pandas_stubs.

pandas-stubs is useful to have type checking in your pandas projects. By installing pandas-stubs you can validate that types in your code are consistent. You can see an example here: https://github.com/pandas-dev/pandas-stubs#usage

You can install pandas-stubs via pip and conda-forge.

We are pleased to announce the release of pandas v1.4.3.

This is a patch release in the 1.4.x series and includes some regression fixes and bug fixes. We recommend that all users in the 1.4.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==1.4.3

Or from conda-forge

    conda install -c conda-forge pandas==1.4.3

pandas core dev Jeff Reback gave a talk on the past, present and future of pandas: https://m.youtube.com/watch?v=7JHqxODJG9k

pandas added some new sponsors in the last few months. Thanks Voltron Data, Quansight Labs, NVIDIA and Bodo for supporting pandas development. You can see the full list of sponsors in our home page: https://pandas.pydata.org/

PDEP-1 has been accepted, being the first pandas enhancement proposal, and setting the guidelines fo discussions about the pandas future. This will not only make discussions easier, but it will also bring clarity and transparency to the project plans.

We just updated our Team page to show more clearly the active maintainers who are currently working on pandas (in a broad sense, 22 maintainers).

We want to thank the maintainers who are not active anymore, but who helped build what pandas is today: Wouter Overmeire, Skipper Seabold, Jeff Tratner, Stephan Hoyer, chris-b1, Sinhrks, Phillip Cloud, Pietro Battiston, Jeremy Schendel, Kaiqi Dong, and Daniel Saxton.

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/