matplotlib / anatomyofmatplotlib

Anatomy of Matplotlib -- tutorial developed for the SciPy conference

Introduction

This tutorial is a complete re-imagining of how one should teach users the matplotlib library. Hopefully, this tutorial may serve as inspiration for future restructuring of the matplotlib documentation. Plus, I have some ideas of how to improve this tutorial.

Please fork and contribute back improvements! Feel free to use this tutorial for conferences and other opportunities for training.

The tutorial can be viewed on nbviewer:

• Part 0: Introduction To NumPy
• Part 1: Overview of Matplotlib
• Part 2: Plotting Methods
• Part 3: How To Speak MPL
• Part 4: Limits, Legends, and Layouts
• Part 5: Artists
• Part 6: mpl_toolkits

Installation

All you need is matplotlib (v1.5 or greater) and jupyter installed. You can use your favorite Python package installer for this:

conda install matplotlib jupyter
git clone https://github.com/matplotlib/AnatomyOfMatplotlib.git
cd AnatomyOfMatplotlib
jupyter notebook

A browser window should appear and you can verify that everything works as expected by clicking on the Test Install.ipynb notebook. There, you will see a "code cell" that you can execute. Run it, and you should see a very simple line plot, indicating that all is well.

anatomyofmatplotlib's Issues

need to fix link regarding MEPs

in Part 1, MEPs are mentioned and links to the Wiki, which is no long the right location, I think

imshow color bar

Hello matplotlib developers,

I was watching the Youtube recording: Anatomy of Matplotlib from SciPy 2018, and I have a question about AnatomyOfMatplotlib/solutions/2.2-vmin_vmax_imshow_and_colorbars.py

From line 17 to 18...

for ax, data in zip(axes, [data1, data2, data3]):
im = ax.imshow(data, vmin=0, vmax=3, interpolation='nearest')

I am assuming data3 has bigger values, followed by data2 and data2, since data3 is multiplied by 3. Suppose if I switch the order of the list in line 17 from:

for ax, data in zip(axes, [data1, data2, data3]):

to:

for ax, data in zip(axes, [data3, data2, data1]):

So, the last im object would data1 which has a 10 by 10 array with max value of 1. Since we are giving the last im object to make the colorbar, would that mean the range color bar spans from 0 to around 1? Or does matplotlib somehow manage to look at all three plotted imshows and perceive that the maximum value amongst the three imshows is around 3?

Thank you!

problem with floating axes demo in part 6

It doesn't work when running through the examples, but if it is the first thing executing (say, after restarting the kernel), it works fine.

Remove backend and add resolve nteract: matplotlib.use('nbagg')

Backend is no longer necessary IMO. Using a backend results in the following error on Jupyter.

Javascript Error: IPython is not defined

Also adding %matplotlib inline before importing matplotlib resolves the displaying of graphs.

Should I fix them in the notebooks and send a PR?

Thanks.

Anatomy of a plot image is too wide

It causes the text in the cell to require side-scrolling

Chapter 2 subsec colorbars example data missing

Seems like the example data used in chapter 2 at the colorbar example is no longer supported as of py 3.1. bivariate_normal.npy is not in any folder and has apparantly been discontinued.

Add animation examples now that nbagg is used

make examples progressive

In part 2, the example is too much to do at once. Rather, it would make sense to build up that example as more is taught. Perhaps a new feature for IPython notebooks would be useful (floating cells?)

Matplotlib