A friend of mine created a page to show code snippets and comparisons between a few of the plotting libraries available in Python (and R) -- http://pythonplot.com/
Python Data Visualization 2018: Why So Many Libraries?
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Re: Python Data Visualization 2018: Why So Many Libraries?
#12There's also Vaex for big(ger) data visualization.
It's in the image, in green, slightly above the center, and mentioned twice in the text.
Re: Python Data Visualization 2018: Why So Many Libraries?
#13I wonder if Plotly will ever take privacy and security seriously... I've had this ticket open for years. https://github.com/plotly/plotly.js/issues/316
The transparent button-removal config option is a fair workaround. (in the Plotly R docs, removing the button is the first code example: https://www.rdocumentation.org/packages/plotly/versions/4.8.... )
Re: Python Data Visualization 2018: Why So Many Libraries?
#14I can totally recommend vega and vega-lite. It's just json and web based so it pretty language independent. There's no difference between just messing around with data sciency stuff in a repl or making a graph for your website, it's all the same.
Re: Python Data Visualization 2018: Why So Many Libraries?
#15Re: Python Data Visualization 2018: Why So Many Libraries?
#16There's like 15 comments in this post and 10 different suggestions on what visualization library to use. That's not great.
Re: Python Data Visualization 2018: Why So Many Libraries?
#17There's like 15 comments in this post and 10 different suggestions on what visualization library to use. That's not great.
Yup. A likely result is that if you pick one and spend the time to learn it and use it for a project, there's a non-trivial chance that the choice you make will be join the ever growing collection of library abandon-ware in the not too distant future.
This is why my favorite Python visualization tools are not Python - I've been burned too many times by libraries coming and going, and I just don't have the time to spend farting around trying to track the latest library fads.
Re: Python Data Visualization 2018: Why So Many Libraries?
#18I wonder if Plotly will ever take privacy and security seriously... I've had this ticket open for years. https://github.com/plotly/plotly.js/issues/316
The transparent button-removal config option is a fair workaround. (in the Plotly R docs, removing the button is the first code example: https://www.rdocumentation.org/packages/plotly/versions/4.8.... )
1) shouldn't be there at all IMHO 2) should be off by default if anyone still thinks it is even remotely a good idea
Re: Python Data Visualization 2018: Why So Many Libraries?
#19Missed one! Spotify just released their own dataviz library yesterday https://labs.spotify.com/2018/11/15/introducing-chartify-eas...
(which is a wrapper for bokeh, sounds good to me)
Re: Python Data Visualization 2018: Why So Many Libraries?
#20I'm pretty good at Python and do most of my work in it nowadays, but if I need to make a data visualization, I still go to R just for ggplot2. Nothing currently in Python compares (not even the "ggplot2 port"), and it takes an order of magnitude longer to make a comparable viz.
Check plotnine, which is a decent reimplementation of ggplot2 in python:
https://plotnine.readthedocs.io/en/latest/