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Comment by sfpotter

Very cool effort. That said, and it's probably because of the kind of work that I do, but I have almost never found the four challenges to be any kind of a problem for me. Although I do think there is some kind of contradiction there. Plotting (exploratory data analyis ("EDA"), really) is all about distilling key insights and finding features hidden in data. But you have to some kind of intuition about where the needle in the haystack is. IME, throwing up a ton of plots and being able to scrub around in them never seems to provide much insight. It's also very fast---usually the feedback loop is like "make a plot, go away and think about it for an hour, decide what plot I need to make next, repeat". If there is too much data on the screen it defeats the point of EDA a little bit.

For me, matplotlib still reigns supreme. Rather than a fancy new visualization framework, I'd love for matplotlib to just be improved (admittedly, fastplotlib covers a different set of needs than what matplotlib does... but the author named it what they named it, so they have invited comparison. ;-) ).

Two things for me at least that would go a long way:

1) Better 3D plotting. It sucks, it's slow, it's basically unusable, although I do like how it looks most of the time. I mainly use PyVista now but it sure would be nice to have the power of a PyVista in a matplotlib subplot with a style consistent with the rest of matplotlib.

2) Some kind of WYSIWYG editor that will let you propagate changes back into your plot easily. It's faster and easier to adjust your plot layout visually rather than in code. I'd love to be able to make a plot, open up a WYSIWYG editor, lay things out a bit, and have those changes propagate back to code so that I can save it for all time.

(If these features already exist I'll be ecstatic ;-) )

parent sfpotter 1 year ago

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