Using subplots in Matplotlib

We have already seen how to add two data sets to a single line plot or bar chart.

Sometimes it is useful to be able to add several different graphs to the same image. This is done using sub-plots.

Subplot example

Here are 2 line plots of daily temperature and rainfall for 2009:

Here is the code to create this plot:

import matplotlib.pyplot as plt
import csv

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

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

days = range(365)

plt.subplot(2, 1, 1)
plt.plot(days, temperature)
plt.ylabel("Temperature")
plt.subplot(2, 1, 2)
plt.plot(days, rain)
plt.xlabel("Day")
plt.ylabel("Rain")
plt.suptitle("2009 weather")
plt.show()

We first read in both data sources, to create the temperature and rain lists, and also the days list as normal.

Subplots are arranged in a grid, like this:

This shows that the plots are arranged as 2 rows and 1 column. The plots are numbered 1 and 2.

Here is the code to plot the first graph:

plt.subplot(2, 1, 1)
plt.plot(days, temperature)
plt.ylabel("Temperature")

We create the first subplot using the plt.subplot(rows, cols, index) function. This takes three parameters:

• The number of rows, which is 2 in our case.
• The number of columns, which is 1 in our case.
• The plot number, which is 1 for the first plot. This ensures that the plot is placed in the top position.

We then call the plot and ylabel functions. Because we called the subplot function first, those functions apply to the subplot rather than the whole graph.

We create the second subplot by calling plt.subplot a second time:

plt.subplot(2, 1, 2)
plt.plot(days, rain)
plt.xlabel("Day")
plt.ylabel("Rain")

This time the rows and columns are the same, but we set the plot number to 2 to indicate that this plot should go in the bottom position.

We also add an xlabel set to Day. This is only added to the bottom plot because both plots use the x-axis to show days, so it is not necessary to label both plots.

Finally, we add a title:

plt.suptitle("2009 weather")

When we have multiple plots we use suptitle rather than title (that isn't a typo - it is suptitle not subtitle). This applies a title to the entire image (whereas title can be used to apply a title to each subplot).

Subplot layout

The case above used 2 subplots, arranged as 2 rows, and 1 column. Here is an alternative layout, with 6 subplots arranged as 2 rows of 3 columns:

The code to create a plot like this is:

plt.subplot(2, 3, 1)
# create plot 1
plt.subplot(2, 3, 2)
# create plot 2
plt.subplot(2, 3, 3)
# create plot 3
plt.subplot(2, 3, 4)
# create plot 4
plt.subplot(2, 3, 5)
# create plot 5
plt.subplot(2, 3, 6)
# create plot 6

This time each call to subplot has:

• row set to 2.
• cols set to 3.
• index set to the plot number.

Plots are numbered 1 to 6, row by row, as shown in the image above.

We can create more complex layouts, like this:

Here, the top row of images is created using a 2-row, 3-column grid, exactly like the previous example. Since these three plots occupy the first three positions, we create them using parameters (2, 3, 1), (2, 3, 2), and (2, 3, 3).

The bottom image is created using a 2-row, 1-column grid, just like the original case from earlier. This time, the image occupies the second position in the grid, so we create it using parameters (2, 1, 2).

See also

• Styling lines and markers with Matplotlib