An area chart looks like a Line graph with the region between the line and the x-axis filled in. The filled area emphasizes the magnitude of the quantity at each x value, not just its shape. Single-series area charts are essentially line charts with a visual nudge toward quantity matters; the real value of area charts is in the stacked form, where multiple series are stacked on top of each other and the total area shows the cumulative quantity.
Image: Stacked 100% area chart, CC BY-SA 3.0
The typical use case is contribution or ratio visualization over time. Sales by representative across four months, with each representative’s line filled and stacked, makes it easy to see both:
- The total (the height of the top edge at each month).
- The individual contributions (the height of each band).
Stacked area charts share a weakness with stacked bar charts: bands above the bottom one don’t sit on a common baseline, which makes comparing them at a glance harder than it should be. If a representative grew their sales but everyone above them shrunk theirs, the band’s vertical position changes even though its height didn’t. Reading individual contributions accurately requires more visual care than a grouped chart would.
For categorical totals where the categories don’t have a meaningful order on the x-axis, area charts are inappropriate. They’re for continuous x-axes — time, age, position — where the filled area between successive points has a coherent meaning.
In Matplotlib, ax.fill_between(x, y1, y2) fills the area between two curves; ax.stackplot(x, *series) draws a stacked area chart from multiple series.