Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.
matplotlib.axes.Axes.get_title() Function
The Axes.get_title() function in axes module of matplotlib library is used to Get an axes title.
Syntax: Axes.get_title(self, loc=’center’)
Parameters: This method accepts the following parameters.
- loc : This parameter is an optional parameter and it is used for Which title to get.
Return: This function return the title text string.
Below examples illustrate the matplotlib.axes.Axes.get_title() function in matplotlib.axes:
Example 1:
# Implementation of matplotlib function import os from matplotlib import font_manager as fm, rcParams import matplotlib.pyplot as plt fig, ax = plt.subplots() fpath = os.path.join(rcParams["datapath"], "fonts / ttf / cmr10.ttf") prop = fm.FontProperties(fname = fpath) fname = os.path.split(fpath)[1] ax.set_title('Title with special font: {}'.format(fname), fontproperties = prop, fontsize = 14) w = ax.get_title() ax.text(0.2, 0.6, "Previously assigned title : \n\n"+str(w), fontsize = 14) ax.set_title("matplotlib.axes.Axes.get_title() \ function Example\n", fontweight ="bold") plt.show() |
Output:
Example 2:
# Implementation of matplotlib function import numpy as np import matplotlib.pyplot as plt x = np.arange(0.1, 5, 0.1) y = np.exp(-x) yerr = 0.1 + 0.1 * np.sqrt(x) fig, (ax, ax1) = plt.subplots(nrows = 1, ncols = 2, sharex = True) ax.errorbar(x, y, yerr = yerr, color ="green") ax.set_title('Title of Axes 1', fontweight ="bold") ax1.errorbar(x, y, yerr = yerr, errorevery = 5, color ="green") ax1.set_title('Title of Axes 2', fontweight ="bold") w = ax.get_title() ww = ax1.get_title() ax.set_title("") ax1.set_title("") ax.set_xlabel(w) ax1.set_xlabel(ww) fig.suptitle("Previously assigned title of each Axes is\ used at labels\n", fontweight ="bold") plt.show() |
Output:
