Many times, people want to graph data from a file. There are many types of files, and many ways you may extract data from a file to graph it. Here, we'll show a couple of ways one might do this. First, we'll use the built-in csv module to load CSV files, then we'll show how to utilize NumPy, which is a third-party module, to load files.

sample code: pythonprogramming.net
hkinsley.com
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sentdex.com
seaofbtc.com

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.