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    I really love the idea of ggplot and the aesthetic of the charts, but the dependencies make it somewhat impractical to use for light-weight applications. It needs a Fortran compiler, Numpy/Scipy, Matplotlib, and whatever else in between, installing it can be quite a lengthy pain.

    Is anyone aware of any maintained Python charting libraries that are less dependency-heavy? Searching yields many results with untouched code from 2009 and older.

    It appears much of the advancement in charting libraries is going towards JavaScript/SVG client-side rendered toolkits.

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      I am particularly partial to jgraph, which is a small C program with basically no dependencies.

      I have this in my ~/bin to convert jgr files to trimmed PDFs (requires pdfcrop from texlive and ps2pdf from ghostscript, I think):

      jgraph -P "$1" | ps2pdf - - | pdfcrop - "$2"
      

      I’m not aware of any language bindings for jgraph, but if you spend an hour with its man page, you should be able to write simple jgr files in a jiffy. (Maybe skim the lecture notes on the author’s web page first.)

      Fun fact: jgraph was written in 1992 but didn’t stop compiling until ca. October 2012. At that point, the author fixed it and released a new version.

      As an Archlinux user, I’m obligated to inform you that I maintain a package for it in the AUR.

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        Is anyone aware of any maintained Python charting libraries that are less dependency-heavy?

        Seaborn perhaps? http://stanford.edu/~mwaskom/software/seaborn/index.html

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          Ah, seaborn looks very nice too, but alas has the exact same dependencies as ggplot. :)

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            I did not notice it uses the same base libs as ggplot.py. I been taking the easy route by installing via anacoda, which makes most of these dependency installs simple on OS X.