Mailman 3 June 2025 - Pandas-dev

Next pandas community meeting - Wednesday January 22, UTC 18:00
by Joris Van den Bossche Jan. 14, 2026

Jan. 14, 2026

Hi all, A reminder that tomorrow we have the next bi-monthly (twice a month) dev call (Wednesday, January 22) at 18:00 UTC. Our calendar is at https://pandas.pydata.org/docs/dev/development/community.html to check your local time. The pandas Community Meeting is a regular sync meeting for the project's maintainers which is open to the community. All are welcome to attend! Video Call: https://numfocus-org.zoom.us/j/84024486573?pwd=QnVOUkozc3VzeXVsYnJEM1h4QVBG… Meeting notes: https://docs.google.com/document/u/1/d/1tGbTiYORHiSPgVMXawiweGJlBw5dOkVJLY-… Joris

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ANN: pandas 2.3.0
by emailformattr＠gmail.com June 8, 2025

June 8, 2025

We are pleased to announce the release of pandas v2.3.0. This is a minor release in the 2.3.x series. We recommend that all users in the 2.3.x series upgrade to this version. See the release notes (https://pandas.pydata.org/pandas-docs/version/2.3.0/whatsnew/v2.3.0.html) for a list of all the changes. The release can be installed from PyPI python -m pip install --upgrade pandas==2.3.0 Or from conda-forge conda install -c conda-forge pandas==2.3.0 Please report any issues with the release on the pandas issue tracker (https://github.com/pandas-dev/pandas/issues/new/choose). Thanks to all the contributors (https://pandas.pydata.org/pandas-docs/version/2.3.0/whatsnew/v2.3.0.html#co…) who made this release possible.

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Default read_csv engine in pandas 3.0
by Marc Garcia June 4, 2025

June 4, 2025

Hi there, I was thinking the upcoming pandas 3.0 release would be a good opportunity to change the default engine for pandas.read_csv, and make it be pyarrow for users who have pyarrow installed. It could work in a similar way as read_parquet that the default depends on what's installed (with the difference that the C engine will always be installed). The motivation for the change is that I think in general (at least in my experience) the pyarrow engine runs in half the time as the C engine. And I think the behavior will be somehow consistent to what's been discussed for strings, so I think it'll be easy for users to understand and get used to. Since read_csv is such a common function it'd be good to get feedback from people who thinks this is not a good idea, and understand the problems this can cause. For users with pyarrow not installed in the environment there wouldn't be any change in how pandas works. Thanks!

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