Stem plots in Matplotlib

By Martin McBride, 2022-07-09
Tags: matplotlib stem plot
Categories: matplotlib numpy


A stem plot is quite similar to a bar chart. The difference is that, instead of using a bar for each data point, a stem plot uses a vertical line with a marker at the top.

Here is an example stem plot:

This is very similar to the bar chart we created earlier.

Stem plots can be useful if there are a lot of data points. Since the line and marker occupy less area than the bar, the plot looks less cluttered. This is largely a matter of personal taste.

The code is very similar:

import matplotlib.pyplot as plt
import csv

with open("2009-temp-monthly.csv") as csv_file:
    csv_reader = csv.reader(csv_file, quoting=csv.QUOTE_NONNUMERIC)
    temperature = [x[0] for x in csv_reader]

month_names = ["J", "F", "M", "A", "M", "J",
               "J", "A", "S", "O", "N", "D"]

months = range(12)

plt.title("Monthly temperature 2009")
plt.xlabel("Month")
plt.ylabel("Temperature")
plt.xticks(months, month_names)

plt.stem(months, temperature)
plt.show()

This code is available on github as stemplot-monthly-temperatures.py.

The only difference is the call to plt.stem rather than plt.bar.

Styling stem plots

We can style a stem plot in a similar way to a line plot or scatter plot, with the following optional parameters:

  • The fmt parameter uses a string to specify basic colour, line style, and marker shape options. Use this for simple formatting.
  • The color parameter sets the line colour, using named colours of RGB values.
  • The linewidth parameter sets the width of the line.
  • The linestyle parameter can create dashed lines of various types.
  • The marker, markeredgecolor, markeredgewidth, markerfacecolor, and markersize control the marker appearance.

These options are covered in more detail in the article line and marker styles.

See also

If you found this article useful, you might be interested in the book NumPy Recipes or other books by the same author.

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