How to add details to a plot (in Python, using Matplotlib)
Task
After making a plot, we might want to add axis labels, a title, gridlines, or text. Plotting packages provide tons of tools for this sort of thing. What are some of the essentials?
Related tasks:
- How to create basic plots
- How to create a histogram
- How to create a box (and whisker) plot
- How to change axes, ticks, and scale in a plot
- How to create bivariate plots to compare groups
- How to plot interaction effects of treatments
Solution
We will create some fake data using Python lists, for simplicity. But everything we show below works also if your data is in columns of a DataFrame, such as df['age'].
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patient_height = [ 60, 64, 64, 65, 66, 66, 70, 72, 72, 76 ]
patient_weight = [ 141, 182, 169, 204, 138, 198, 180, 175, 244, 196 ]
The conventional way to import matplotlib in Python is as follows.
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import matplotlib.pyplot as plt
The following code creates a plot with many details added, but each is independent of the others, so you can take just the bit of code that you need.
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plt.scatter( patient_height, patient_weight )
plt.xlabel( 'This is the x axis label.' )
plt.ylabel( 'This is the y axis label.' )
plt.title( 'This is the title.' )
plt.grid() # Turns on gridlines
plt.text( 70, 200, 'Text at (70,200)' ) # Text method 1
plt.annotate( 'Text at (60,150)', (60,150) ) # Text method 2
plt.annotate( 'Text with arrow', xytext=(60,225), xy=(72,244),
arrowprops={'color':'red'} ) # Text with arrow
plt.show()
Content last modified on 24 July 2023.
See a problem? Tell us or edit the source.
Contributed by Nathan Carter (ncarter@bentley.edu)