Matplotlib
Figures, axes and artists — what actually draws your chart.
Foundations
4/4The objects a chart is made of, and the two APIs for reaching them.
- 1
Figure, Axes and Artist
Every matplotlib question is really “which object owns this?”
10 min0/3 - 2
plt versus ax
Why half the examples online look nothing like the other half
11 min0/3 - 3
Your first plot
Six lines, and five of them are about being readable
12 min0/3 - 4
Showing and saving
Backends, the blank-file trap, and getting a file worth sending
11 min0/3
The plot types
4/4Lines, scatters, bars and distributions — and which question each answers.
- 5
Lines
What the segment between two points is actually claiming
12 min0/3 - 6
Scatter plots
Do these two columns move together — and how much can you read into that
12 min0/3 - 7
Bar charts
Sort them, turn them sideways, and never cut the baseline
12 min0/3 - 8
Distributions
What one column looks like before you average it
13 min0/3
Making it readable
4/4Labels, scales, colour and annotation.
- 9
Ticks and labels
Locators say where, formatters say what — almost every tick problem is one of the two
12 min0/3 - 10
Scales and limits
Log axes, zero baselines, and why twin axes can prove anything
12 min0/3 - 11
Colour
Three families, and picking the wrong one invents structure that is not there
12 min0/3 - 12
Annotation
Where a chart stops showing data and starts making a claim
12 min0/3
Layout
3/3Several plots in one figure, and getting them to fit.
In practice
3/3Styles, pandas integration, and exporting for real use.
Capstones
2/2A dashboard, and a figure fit to publish.
