Re:Python Data Visualization 2018: Why So Many Libraries?
by gh02t on Friday November 16, 2018 @07:18PM
(#18473035)
I'd argue exactly the opposite, the reason there are so many is that it's really hard to write a good data visualization framework. Data visualization encompasses a vast range of different tasks that are often only loosely related, and it's extremely difficult (if not impossible) to write one library that serves all uses well. Add on top of that the fact that you have different output types - web, interactive analysis, print etc and you end up with a situation where you get lots of different libraries optimized for different use cases.
And that's not even counting differences of opinion on aesthetics...
Re:Python Data Visualization 2018: Why So Many Libraries?
by bigreddot on Friday November 16, 2018 @10:12PM
(#18473706)
5+ years and 321 contributors later, I can state that Bokeh was not easy to write. Fairly sure MPL and Plotly devs would disagree with this assessment as well.
Python has a multitude of vis systems because there are multiple use-cases, sometimes overlapping and sometimes not, and different people prioritize these very differently (and that's OK).
What eventually happened was that the BDFL blessed Django and most of the others withered. Some had enough ecosystem, or were components of some other larger project, or had a niche advantage of Django, and they managed to survive.
I think the reason why web frameworks and data viz systems proliferate in Python is just that they are so easy to write, yet still challenging enough to be really fun, and you get a lot of highly, uh, visible feedback and reward for doing it.