[selectron]

One of my biggest frustrations with python for data science is how bad the documentation for matplotlib is. Also the default settings leave a lot to be desired - look at the color map scatter plots to see what I mean. What is with all that white-space around the graph?

[Jmoir]

I fully agree with the crappy documentation. Which to be honest isn't consistent with the rest of the python sphere. Documentation tends to be pretty good generally. It's a shame.

[lowmagnet]

I find pandas documentation verbose but ultimately not real world. Every one of them generates random values which aren't visually distinct. Makes it hard to follow operations.

[theseatoms]

I completely agree with this assessment. Demonstration of the functionality is technically all there. It's often just hard to parse.

(Admittedly, this is a bit of a nitpick for free software. Overall, I'm very happy with the package.)

[a_bonobo]

tight_layout() gets rid of all that whitespace :)

There are some alternatives with pretty defaults - I personally love seaborn [1] which builds on top of matplotlib, but seaborn is even more "do it the way I like it or suffer the consequences" - however, the coming v2.0 of Matplotlib comes with a few API changes and a different default color scheme: http://matplotlib.org/style_changes.html or http://matplotlib.1069221.n5.nabble.com/matplotlib-v2-0-0b1-...

[1] http://stanford.edu/~mwaskom/software/seaborn/examples/index...

[bunderbunder]

For what it's worth, the Python version of ggplot seems to be making some headway.

http://ggplot.yhathq.com