Matplotlib.axes.Axes.get_title() in Python
Last Updated :
19 Apr, 2020
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:
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()
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Output:
Example 2:
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()
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Output:
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