Pandas and Beyond with Wes McKinney - 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.
▬▬▬▬ About the podcast ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
This video is the uncut, live recording of the Talk Python To Me podcast ( https://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 https://talkpython.fm/subscribe.
▬▬▬▬ Guests ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Wes McKinney
▬▬▬▬ Links and resources from the show ▬▬▬▬▬▬▬▬▬▬▬▬
Wes' Website: https://wesmckinney.com
Pandas: https://pandas.pydata.org
Apache Arrow: https://arrow.apache.org
Ibis: https://ibis-project.org
Python for Data Analysis - Groupby Summary: https://wesmckinney.com/book/data-aggregation.html#groupby-summary
Polars: https://pola.rs
Dask: https://www.dask.org
Sqlglot: https://sqlglot.com/sqlglot.html
Pandoc: https://pandoc.org
Quarto: https://quarto.org
Evidence framework: https://evidence.dev
pyscript: https://pyscript.net
duckdb: https://duckdb.org
Jupyterlite: https://jupyter.org/try-jupyter/lab/
Djangonauts: https://djangonaut.space
▬▬▬▬ Dive deeper ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Listen to the Talk Python To Me podcast at https://talkpython.fm and explore over 275 hours of Python courses at https://training.talkpython.fm/courses.
▬▬▬▬ Follow us on Social ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Mastodon: Michael - https://fosstodon.org/@mkennedy & Talk Python - https://fosstodon.org/@talkpython
Bluesky: Michael - https://bsky.app/profile/mkennedy.codes & Talk Python - https://bsky.app/profile/talkpython.fm
X: Michael - https://x.com/mkennedy & Talk Python - https://x.com/talkpython
▬▬▬▬ About the podcast ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
This video is the uncut, live recording of the Talk Python To Me podcast ( https://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 https://talkpython.fm/subscribe.
▬▬▬▬ Guests ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Wes McKinney
▬▬▬▬ Links and resources from the show ▬▬▬▬▬▬▬▬▬▬▬▬
Wes' Website: https://wesmckinney.com
Pandas: https://pandas.pydata.org
Apache Arrow: https://arrow.apache.org
Ibis: https://ibis-project.org
Python for Data Analysis - Groupby Summary: https://wesmckinney.com/book/data-aggregation.html#groupby-summary
Polars: https://pola.rs
Dask: https://www.dask.org
Sqlglot: https://sqlglot.com/sqlglot.html
Pandoc: https://pandoc.org
Quarto: https://quarto.org
Evidence framework: https://evidence.dev
pyscript: https://pyscript.net
duckdb: https://duckdb.org
Jupyterlite: https://jupyter.org/try-jupyter/lab/
Djangonauts: https://djangonaut.space
▬▬▬▬ Dive deeper ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Listen to the Talk Python To Me podcast at https://talkpython.fm and explore over 275 hours of Python courses at https://training.talkpython.fm/courses.
▬▬▬▬ Follow us on Social ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Mastodon: Michael - https://fosstodon.org/@mkennedy & Talk Python - https://fosstodon.org/@talkpython
Bluesky: Michael - https://bsky.app/profile/mkennedy.codes & Talk Python - https://bsky.app/profile/talkpython.fm
X: Michael - https://x.com/mkennedy & Talk Python - https://x.com/talkpython
