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The problem with all these nice new visualization libraries for Python, is that they all (at least the shinny nice ones) fail totally short when it comes to do B&W graphics for journal publications. Things like filling patterns, line patterns etc, are mostly missing.

I still use Matplotlib and I can make it look beautiful and exactly how I want... it's just a lot more work to get the shinny bits.



For my thesis, I tried a couple of different options, but in the end the only one that really made publication-grade output was gnuplot with the epslatex terminal. It's a bit fiddly to get it up and running, but hands down the best result I think.

EDIT: Spelling.


The underlying vega library supports overriding styles for color and line properties - it may not be as difficult as you imagine to generate B&W graph outputs for print.


Once you have a web / javascript output, there are a bunch of possibilities:

https://observablehq.com/search?query=stippling

https://observablehq.com/search?query=dithering

https://observablehq.com/search?query=halftone

https://observablehq.com/search?query=crosshatch

(Or go out and look around github or the broader web to find many more options.)


I save the data from python or matlab and use pgfplots to create stunning plots. Nothing I saw in any other plotting lib came ever close to pgfplots in terms of beauty and flexibility.


It is a great package. Two disadvantages are that the interfacte is not very pythonic and that there is no interactivity.


second that. also for the scientific community at large, big portions of "not-so-happy"-matplotlib-users are just using whatever they/their admin installed sometime ago, which probably is outdated and does not include a bunch of features introduced in v3


Plotnine is the best when you are making a plot to put in a pdf or on paper.




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