Matplotlib learning path

Intermediate Matplotlib

Control axes and ticks, annotate the story, show spread and uncertainty, stack data, plot pandas DataFrames and save figures for reports.

7 lessons

Set axis limits, choose tick positions and labels, and switch to a log scale with set_yscale.

Point at important values with ax.annotate, add notes with ax.text and mark targets with axhline.

Compare the spread of several groups with ax.boxplot and ax.violinplot.

Show how parts add up over time with stacked bars (bottom=) and ax.stackplot.

Show measurement uncertainty with ax.errorbar and a shaded band with fill_between.

Turn a pandas DataFrame into a chart with df.plot and customize it with Matplotlib.

Save charts as PNG or SVG with fig.savefig and control their size, resolution and margins.