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.add_subplot() function
The add_subplot() method figure module of matplotlib library is used to add an Axes to the figure as part of a subplot arrangement.
Syntax: add_subplot(self, *args, **kwargs)
Parameters: This accept the following parameters that are described below:
- projection : This parameter is the projection type of the Axes.
- sharex, sharey : These parameters share the x or y axis with sharex and/or sharey.
- label : This parameter is the label for the returned axes.
Returns: This method return the axes of the subplot.
Below examples illustrate the matplotlib.figure.Figure.add_subplot() function in matplotlib.figure:
Example 1:
# Implementation of matplotlib functionimport matplotlib.pyplot as pltfrom mpl_toolkits.axisartist.axislines import Subplot fig = plt.figure(figsize =(4, 4)) ax = Subplot(fig, 111)fig.add_subplot(ax) ax.axis["left"].set_visible(False)ax.axis["bottom"].set_visible(False) fig.suptitle('matplotlib.figure.Figure.add_subplot() \function Example\n\n', fontweight ="bold") plt.show() |
Output:
Example 2:
# Implementation of matplotlib functionimport matplotlib.pyplot as pltimport numpy as np np.random.seed(19680801) xdata = np.random.random([2, 10]) xdata1 = xdata[0, :]xdata2 = xdata[1, :] ydata1 = xdata1 ** 2ydata2 = 1 - xdata2 ** 3 fig = plt.figure()ax = fig.add_subplot(1, 1, 1)ax.plot(xdata1, ydata1, color ='tab:blue')ax.plot(xdata2, ydata2, color ='tab:orange') ax.set_xlim([0, 1])ax.set_ylim([0, 1])fig.suptitle('matplotlib.figure.Figure.add_subplot() \function Example\n\n', fontweight ="bold") plt.show() |
Output:
