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Matplotlib.axes.Axes.annotate() in Python

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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()

Output:


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Last Updated : 13 Apr, 2020
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