Matplotlib.figure.Figure.subplots() in Python

Last Updated : 03 May, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The figure module provides the top-level Artist, the Figure, which contains all the plot elements. This module is used to control the default spacing of the subplots and top level container for all plot elements.

matplotlib.figure.Figure.subplots() method

The subplots() method figure module of matplotlib library is used to display the figure window.

Syntax: subplots(self, nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True, subplot_kw=None, gridspec_kw=None)

Parameters: This method accept the following parameters that are described below:

nrows, ncols : These parameter are the number of rows/columns of the subplot grid.

sharex, sharey : These parameter controls sharing of properties among x (sharex) or y (sharey) axes.

squeeze : This parameter is an optional parameter and it contains boolean value with default as True.

num: This parameter is the pyplot.figure keyword that sets the figure number or label.

subplot_kwd: This parameter is the dict with keywords passed to the add_subplot call used to create each subplot.

gridspec_kw: This parameter is the dict with keywords passed to the GridSpec constructor used to create the grid the subplots are placed on.

Returns: This method return the following values.

ax : This method return the axes.Axes object or array of Axes objects.

Below examples illustrate the matplotlib.figure.Figure.subplots() function in matplotlib.figure:

Example 1:

   # Implementation of matplotlib function 
import numpy as np 
import matplotlib.pyplot as plt 
   
x = np.linspace(0, 2 * np.pi, 400) 
y = np.sin(x**2) 
   
fig = plt.figure() 
ax = fig.subplots() 
  
ax.plot(x, y) 
  
fig.suptitle("""matplotlib.figure.Figure.subplots() 
function Example\n\n""", fontweight ="bold")  
  
fig.show()

Output:

Example 2:

   # Implementation of matplotlib function 
import numpy as np 
import matplotlib.pyplot as plt 
   
  
x = np.linspace(0, 1.5 * np.pi, 100) 
y = np.sin(x**2)+np.cos(x**2) 
   
fig = plt.figure() 
axs = fig.subplots(2, 2, subplot_kw = dict(polar = True)) 
  
axs[0, 0].plot(x, y) 
axs[1, 1].scatter(x, y) 
  
fig.suptitle("""matplotlib.figure.Figure.subplots() 
function Example\n\n""", fontweight ="bold")  
  
fig.show()  
 
  