Matplotlib.pyplot.annotate() in Python (original) (raw)

Last Updated : 12 Apr, 2020

Matplotlib is a library in Python and it is numerical - mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface.

matplotlib.pyplot.annotate() Function

The annotate() function in pyplot module of matplotlib library is used to annotate the point xy with text s.

Syntax: angle_spectrum(x, Fs=2, Fc=0, window=mlab.window_hanning, pad_to=None, sides='default', **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.pyplot.annotate() function in matplotlib.pyplot:Example #1:

Python3 1== `

Implementation of matplotlib.pyplot.annotate()

function

import matplotlib.pyplot as plt import numpy as np

fig, geeeks = plt.subplots()

t = np.arange(0.0, 5.0, 0.001) s = np.cos(3 * np.pi * t) line = geeeks.plot(t, s, lw = 2)

Annotation

geeeks.annotate('Local Max', xy =(3.3, 1), xytext =(3, 1.8), arrowprops = dict(facecolor ='green', shrink = 0.05),)

geeeks.set_ylim(-2, 2)

Plot the Annotation in the graph

plt.show()

`

Output: Example #2:

Python3 1== `

Implementation of matplotlib.pyplot.annotate()

function

import numpy as np import matplotlib.pyplot as plt

x = np.arange(0, 10, 0.005) y = np.exp(-x / 3.) * np.sin(3 * np.pi * x)

fig, ax = plt.subplots() ax.plot(x, y) ax.set_xlim(0, 10) ax.set_ylim(-1, 1)

Setting up the parameters

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)

disp = ax.annotate('display = (%.1f, %.1f)'%(xdisplay, ydisplay), (xdisplay, ydisplay), xytext =(0.5 * offset, -offset), xycoords ='figure pixels', textcoords ='offset points', bbox = bbox, arrowprops = arrowprops)

To display the annotation

plt.show()

`

Output: