In this Matplotlib tutorial, we're going to be talking about some of the possible customizations to graphs. In order to start modifying the subplots, we have to define them. We will talk about them soon, but there are two major ways to define subplots, and to structure them. For now, we'll just use one of them, but we will be explaining them shortly.

sample code: pythonprogramming.net
hkinsley.com
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1. Introduction and Line
2. Legends titles and labels
3. bar charts and histograms
4. Scatter Plots
5. stack plots
6. Pie Charts
7. loading data from files
8. getting data from the internet
9. converting data from the internet
10. basic customizations, rotating labels
11. handling unix time
12. more customization of colors and fills
13. spines and horizontal lines
14. candlestick OHLC graphs
15. styles
16. Live graphs
17. annotations and placing text
18. annotating last price to edge of matplotlib graph example
19. subplots
20. implementing subplots to our stock chart
21. adding more indicator data to our charts
22. cleaning chart, custom fills, pruning
23. sharex axis
24. multi y axis plotting volume on stock chart
25. customizing Matplotlib Legends
26. Basemap intro
27. Basemap customization options
28. plotting coordinates on a map with Basemap
29. matplotlib 3d intro
30. 3d scatter plot
31. 3d bar charts
32. conclusion

Learn how to visualize data in the form of line graphs, bar charts, pie charts, 3D graphs, and more with Python 3 and Matplotlib.