Altair: Declarative Visualization in Python


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To see the ‘Table of associated records‘ go the bottom, Pag. 2 ( 👩‍🎓 🖥 For free online version, on the image).


Unclassified recommendation



PyData, Brian Granger. Source: youtu.be/aRxahWy-ul8

Altair is a declarative statistical visualization library for Python. With Altair you can spend more time understanding your data and its meaning. Altair’s API is simple, friendly and consistent and built on top of the powerful Vega-Lite JSON specification. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code.

altair-viz/altair

Authors

(Unofficial biography. For informational purposes only)


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Jake Vanderplas

Director of Open Software at the University of Washington’s eScience institute, and researches and teaches in a variety of areas, including Astronomy, Astrostatistics, Machine Learning, and Scalable Computation.

Brian Granger. (Principal Technical Program Manager at Amazon Web).

“Brian is an Associate Professor of Physics at Cal Poly State University in San Luis Obispo, CA, where he teaches Physics and Data Science and does research in interactive computing. He is a leader of the Python project, co-founder of Project Jupyter and is an active contributor to a number of other open source projects focused on data science in Python. In 2016, he co-created the Altair package for statistical visualization in Python. He is a advisory board member of the NumFOCUS Foundation and a faculty fellow of the Cal Poly Center for Innovation and Entrepreneurship”. (Source: physics.calpoly.edu/bgranger).

Resultado de imagen de UW Interactive Data Lab

UW Interactive Data Lab

The UW Interactive Data Lab began its life as the Stanford Visualization Group, founded in the late 1990s by Prof. Pat Hanrahan. Early Stanford projects included the Polaris system, now commercialized as Tableau Software. Their projects include new languages, theoretical models, exploratory analysis tools, and design tools for interactive visualization, techniques for representing uncertainty, and perceptual experiments to assess how well visualizations work. (Source: idl.cs.washington.edu/about).


🔘 Pages

Github tutorial shell: github.com/altair-viz/altair
Docs Altair: altair-viz.github.io

Thank you very much for this work to @jakevdp, @ellisonbg, @uwdata via @States_AI_IA #Python #ebook #openscience #openaccess #ai #artificialintelligence #ia #thebibleai


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