Matplotlib.axes.Axes.annotate() in Python

Last Updated : 13 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.annotate() Function

The Axes.annotate() function in axes module of matplotlib library is also used to annotate the point xy with text text.In other word, it i used to placed the text at xy.

Syntax:
Axes.annotate(self, s, xy, *args, **kwargs)
Parameters: This method accept the following parameters that are described below:

s: This parameter is the text of the annotation.

xy: This parameter is the point (x, y) to annotate.

xytext: This parameter is an optional parameter. It is The position (x, y) to place the text at.

xycoords: This parameter is also an optional parameter and contains the string value.

textcoords: This parameter contains the string value.Coordinate system that xytext is given, which may be different than the coordinate system used for xy

arrowprops : This parameter is also an optional parameter and contains dict type.Its default value is None.

annotation_clip : This parameter is also an optional parameter and contains boolean value.Its default value is None which behaves as True.

Returns: This method returns the annotation.

Below examples illustrate the matplotlib.axes.Axes.annotate() function in matplotlib.axes:

Example-1:

# Implementation of matplotlib function 
import matplotlib.pyplot as plt 
import numpy as np 
   
fig, ax1 = plt.subplots() 
   
t = np.arange(4, 50., 1) 
s = np.cos(np.pi * t)**3- np.sin(3 * np.pi * t)**2
  
ax1.plot(t, s, lw = 2) 
ax1.annotate('Starting', xy =(3.3, 1), 
             xytext =(3, 1.8), 
             arrowprops = dict(facecolor ='green', 
                               shrink = 0.05),   ) 
  
ax1.set_ylim(-2, 2) 
ax1.set_title('matplotlib.axes.Axes.annotate() Example') 
plt.show() 

Output:

Example-2:

# Implementation of matplotlib function 
import numpy as np 
import matplotlib.pyplot as plt 
   
x = np.arange(0, 20, 0.005) 
y = 3.5 * np.exp(-x / 3.) * np.sin(2 * np.pi * x) 
   
fig, ax = plt.subplots() 
ax.plot(x, y, color ="green") 
ax.set_xlim(0, 20) 
ax.set_ylim(-4, 4) 
   
xdata, ydata = 5, 0
xdisplay, ydisplay = ax.transData.transform((xdata,  
                                             ydata)) 
   
bbox = dict(boxstyle ="round", fc ="0.8") 
arrowprops = dict( 
    arrowstyle = "->", 
    connectionstyle = "angle, angleA = 0, \ 
    angleB = 90, rad = 10") 
   
offset = 72
   
# Annotation 
ax.annotate('data = (%.1f, %.1f)'%(xdata, ydata), 
            (xdata, ydata), xytext =(-2 * offset, 
                                     offset),  
            textcoords ='offset points', 
            bbox = bbox, arrowprops = arrowprops) 
   
   
ax.annotate('display = (%.1f, %.1f)'%(xdisplay, ydisplay), 
            (xdisplay, ydisplay), xytext =(0.5 * offset, 
                                           -offset), 
            xycoords ='figure pixels', 
            textcoords ='offset points', 
            bbox = bbox, arrowprops = arrowprops) 
  
ax.set_title('matplotlib.axes.Axes.annotate() Example') 
plt.show() 