Customizing Plots
Add titles, labels, and legends.
From Raw to Readable
A bare chart shows data but tells the reader little. Customization adds the context that turns a plot into a clear message: titles, axis labels, legends, ticks, and annotations.
All of these are methods on the axes object.
Titles
Give every axes a title with ax.set_title('Monthly Sales'). A figure-wide title uses fig.suptitle('Report').
The title should state what the chart shows, not just repeat the column name.
raw_label = 'sales_q1'
nice_title = raw_label.replace('_', ' ').title()
print('Title:', nice_title)All lessons in this course
- Figures and Axes
- Line, Bar and Scatter Plots
- Customizing Plots
- Subplots and Layouts