Pandas - History and Future - Talk Python to Me Ep.462

This episode dives into some of the most important data science libraries from the Python space with one of its pioneers: Wes McKinney. He's the creator or co-creator of pandas, Apache Arrow, and Ibis projects and an entrepreneur in this space.
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This video is the uncut, live recording of the Talk Python To Me podcast ( talkpython.fm ). We cover Python-focused topics every week and publish the edited and polished version in audio form. Subscribe in your podcast player of choice (100% free) at talkpython.fm/subscribe.
▬▬▬▬ Guests ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Wes' Website: wesmckinney.com/
▬▬▬▬ Links and resources from the show ▬▬▬▬▬▬▬▬▬▬▬▬
Pandas: pandas.pydata.org/
Apache Arrow: arrow.apache.org/
Ibis: ibis-project.org/
Python for Data Analysis - Groupby Summary: wesmckinney.com/book/data-agg...
Polars: pola.rs/
Dask: www.dask.org/
Sqlglot: sqlglot.com/sqlglot.html
Pandoc: pandoc.org/
Quarto: quarto.org/
Evidence framework: evidence.dev/
pyscript: pyscript.net/
duckdb: duckdb.org/
Jupyterlite: jupyter.org/try-jupyter/lab/
Djangonauts: djangonaut.space/
Listen this episode on Talk Python: talkpython.fm/episodes/show/4...
Episode transcripts: talkpython.fm/episodes/transc...
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[@KevinOMalleyisonlysmallreally]

This is a great talk, but I found Pandas for everyone to be a great book on this for the non-dev python users.

[@marco_gorelli]

34:43 "import numpy as pd" I hope nobody actually writes that 😆

[@tam31433]

Import polars as pd :)

[@marco_gorelli]

@@tam31433 I actually saw that in a bug report once