R is better if your work output is ideas/communication oriented. Reports, tables, notebooks, graphs etc.
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My Jupyter/Pandoc workflow makes reporting pretty comparable. But, 9/10 times when I come across a really brilliant portrayal of something and try to figure out where it came from, it's R.
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Python has good libraries too, but Pythonistae are typically worse about using them thoughtfully. The ones who *are* good tend to have day jobs that don't necessarily align with making good data viz. So it's more a social problem than a tooling problem.
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Yea, sometimes I feel the same way. And, actually, one major aspect of the social problem: I think we need more dev advocates like
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Why not both? You can use R's "reticulate" package to combine the power of Python and the visualization tools of R if there's something in R that really scratches your itch. Or you can go the other way and use the rpy2 module to embed R in a python process.
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Yea, I was doing the latter for a while. I need practice it more though so it doesn't have as much friction, even if its only perceptual.
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We have students in our lab who are very good matplotlib scripters, but as the lone person whose primary lang is
#rstats in the lab, I always get comments on the pretty graphs, mostly via ggplot2. -
Also, having done plenty of Matlab graphs during my PhD, I have been so happy with plotting in
#rstats, even before I discovered tidy data and ggplot2.
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