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This guide will look at the use of matplotlib, which is an abbreviation for the matrix plotting library. When using matplotlib, typically the pyplot module is used, an abbreviation for Python plot. This guide will first explore the basics of pyplot via procedural programming and then look at further customisation using object orientated programming (OOP). This guide will use the Spyder 5 IDE as it has a Variable Explorer which fully supports matplotlib.

Before getting started with matplotlib you should be comfortable with the Python programming language and numpy. The ndarray data structure will be used to store the data that is to be plotted.

Written Guides:
https://dellwindowsreinstallationguide.com/python/
Python Playlist:
https://www.youtube.com/playlist?list=PL1RkaknDn7v-EO4V38oDBkZNd6_530nan

0:00:37 Importing the Data Science Libraries
0:02:25 Automatic vs Inline Plotting
0:05:49 pyplot Procedural Programming (figure, axes, plot, xlabel, ylabel, title, xlim, ylim, xscale, yscale)
0:20:10 fig, ax, lines Object Orientated Programming
0:30:52 Subplots numpy array (subplots) and Subplot Mosaic dictionary (subplot_mosaic)
0:36:21 Understanding how to encode color
0:40:20 Line2D (plot, step, semilogx, semilogy, axvline, axhline, axline)
0:52:50 Gridlines (grid)
0:55:53 PathCollection (scatter)
1:04:14 Patches (bar, barh, pie, hist)
1:20:00 Text, Annotate and Latex (text and annotate)
1:24:30 Tick Parameters (xaxis, yticks, ticks, ticklabels)
1:26:06 Latex
1:31:20 Twinned AxesSubplots (tick_params, twinx and twiny)
1:34:00 Distribution Plots (boxplot and violinplot)
1:35:28 3D Data as 2D arrays (meshgrid)
1:39:28 3D Visualisation in 2D using a colormap (matplot, pcolor, pcolormesh, contour, contourf)
1:44:54 3D Visualisation in 2D using a Axes3DSubplot (plot_wireframe, plot_surface, contour3D, contourf3D)
1:47:50 Working with images (imread and imshow)

#matplotlib #python #Spyder