Exploring Python Frameworks for Data Science Advancements

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This chapter delves into how Python frameworks like streamlit and dash are revolutionizing data science by facilitating the conversion of pandas code into interactive websites without extensive web development knowledge. It discusses the benefits of WebAssembly in executing the scientific Python stack in a browser, showcasing projects like DuckDB and Piadide that enhance web development capabilities.

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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Links from the show

Wes' Website: wesmckinney.com
Pandas: pandas.pydata.org
Apache Arrow: arrow.apache.org
Ibis: ibis-project.org
Python for Data Analysis - Groupby Summary: wesmckinney.com/book
Polars: pola.rs
Dask: dask.org
Sqlglot: sqlglot.com
Pandoc: pandoc.org
Quarto: quarto.org
Evidence framework: evidence.dev
pyscript: pyscript.net
duckdb: duckdb.org
Jupyterlite: jupyter.org
Djangonauts: djangonaut.space
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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