4 ms·

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

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?

lowmagnet 10y ago
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 10y ago
  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.)
Jmoir 10y ago
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.
bunderbunder 10y ago
For what it's worth, the Python version of ggplot seems to be making some headway. http://ggplot.yhathq.com http://ggplot.yhathq.com
a_bonobo 10y ago
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 http://matplotlib.org/style_changes.html or http://matplotlib.1069221.n5.nabble.com/matplotlib-v2-0-0b1-td47165.html http://matplotlib.1069221.n5.nabble.com/matplotlib-v2-0-0b1-... [1] http://stanford.edu/~mwaskom/software/seaborn/examples/index.html http://stanford.edu/~mwaskom/software/seaborn/examples/index...

4 ms·

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

by selectron 10y ago

lowmagnet 10y ago
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 10y ago
  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.)
Jmoir 10y ago
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.
bunderbunder 10y ago
For what it's worth, the Python version of ggplot seems to be making some headway. http://ggplot.yhathq.com http://ggplot.yhathq.com
a_bonobo 10y ago
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 http://matplotlib.org/style_changes.html or http://matplotlib.1069221.n5.nabble.com/matplotlib-v2-0-0b1-td47165.html http://matplotlib.1069221.n5.nabble.com/matplotlib-v2-0-0b1-... [1] http://stanford.edu/~mwaskom/software/seaborn/examples/index.html http://stanford.edu/~mwaskom/software/seaborn/examples/index...