To create multiple plots use matplotlib.pyplot.subplots method which returns the figure along with Axes object or array of Axes object. nrows, ncols attributes of subplots() method determine the number of rows and columns of the subplot grid.
By default, it returns a figure with a single plot. For each axes object i.e plot we can set title (set via set_title()), an x-label (set via set_xlabel()), and a y-label set via set_ylabel()).
Let’s see how this works
- When we call the subplots() method by stacking only in one direction it returns a 1D array of axes object i.e subplots.
- We can access these axes objects using indices just like we access elements of the array. To create specific subplots, call matplotlib.pyplot.plot() on the corresponding index of the axes. Refer to the following figure for a better understanding
Example 1: 1-D array of subplots
Python3
# importing libraryimport matplotlib.pyplot as plt# Some data to displayx = [1, 2, 3]y = [0, 1, 0]z = [1, 0, 1]# Creating 2 subplotsfig, ax = plt.subplots(2)# Accessing each axes object to plot the data through returned arrayax[0].plot(x, y)ax[1].plot(x, z) |
Output :
subplots_fig1
Example2: Stacking in two directions returns a 2D array of axes objects.
Python3
# importing libraryimport matplotlib.pyplot as pltimport numpy as np# Data for plottingx = np.arange(0.0, 2.0, 0.01)y = 1 + np.sin(2 * np.pi * x)# Creating 6 subplots and unpacking the output array immediatelyfig, ((ax1, ax2), (ax3, ax4), (ax5, ax6)) = plt.subplots(3, 2)ax1.plot(x, y, color="orange")ax2.plot(x, y, color="green")ax3.plot(x, y, color="blue")ax4.plot(x, y, color="magenta")ax5.plot(x, y, color="black")ax6.plot(x, y, color="red") |
Output :
Subplots_fig2
