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A comment on Python Data Visualization 2018: Why So Many Libraries?. Parent comment

Re:Python Data Visualization 2018: Why So Many Libraries? by ObscureMind on Friday November 16, 2018 @02:56PM (#18471503)
Check plotnine, which is a decent reimplementation of ggplot2 in python: https://plotnine.readthedocs.io/en/latest/
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Re:Python Data Visualization 2018: Why So Many Libraries? by kugestu on Friday November 16, 2018 @06:08PM (#18472697)
I find myself often using the R ggplot2 documentation for using plotnine - it is such a decent port!
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Re:Python Data Visualization 2018: Why So Many Libraries? by minimaxir on Friday November 16, 2018 @03:20PM (#18471656)
Huh, when I was looking into Python options I had thought plotnine was dead, but looking at the GitHub that's not the case: https://github.com/has2k1/plotnine

I'll give it a shot! :)

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Re:Python Data Visualization 2018: Why So Many Libraries? by ExcaliburZero on Friday November 16, 2018 @03:03PM (#18471549)
Plotnine is quite nice. Its api is very similar to R's ggplot so it gives you the same level of expressiveness and flexibility while being able to stay the Python ecosystem to use numpy, pandas, etc..
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Re:Python Data Visualization 2018: Why So Many Libraries? by ObscureMind on Friday November 16, 2018 @03:06PM (#18471568)
The authors also provide a reimplementation of dplyr in Python that integrates well with plotnine: https://github.com/has2k1/plydata
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