So I’m considering going deep into a data viz library, and I’m wondering what you people think. I’m not asking reddit because I know for a fact that all the hardcore people that know their stuff are on lemmy.

Here are my requirements:

  • API must at least pretend to be reasonably designed.
    • I know that viz libraries are complex. But I want something with carefully chosen primitives that scale reasonably well from “data goes in, chart goes out” to nit-picky adjustments.
  • Defaults must not be ugly.
    • Or at least there should be an easy way to bypass the default ugliness. I know that design is subjective, but how am I supposed to trust a library that operates on the visual space and yet decides that a bad default is ok?
    • Here looks like ggplot has the upper hand. But there is a stylesheet that makes matplotlib look like ggplot, so maybe that’s not a big problem.
  • Must have a future.
    • The github contribution chart on matplotlib just keep going up, it’s insane. While ggplot not so much. But maybe it’s hard to compete with the python hype machine, and that is that.
  • Bonus points if interactive and renders to web too.

Non-requirements:

  • Easy learning curve.
    • I am a hardcore programm0r. I like it rough, as long as it’s worth the effort.
  • Heavy math stuff.
    • I’m not designing rockets or wind turbines. I just want a way to visually represent data as lines, charts, pies, or maps, or maybe violins if I’m feeling fancy.

Thanks

  • @Zeth0s
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    1 year ago

    ggplot is absolutely the best in town, for a ton of reasons, if you are doing real viz and stats. Unfortunately is R only, which, as a hardcore programmer, you’d hate. (I honestly like it, but we are not many).

    Go for plotly as others suggested