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Matplotlib.pyplot.ylim() in Python

Last Updated : 13 Apr, 2020
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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.ylim() Function

The ylim() function in pyplot module of matplotlib library is used to get or set the y-limits of the current axes.

Syntax: matplotlib.pyplot.ylim(*args, **kwargs)

Parameters: This method accept the following parameters that are described below:

  • bottom: This parameter is used to set the ylim to bottom.
  • top: This parameter is used to set the ylim to top.
  • **kwargs: This parameter is Text properties that is used to control the appearance of the labels.

Returns: This returns the following:

  • bottom, top :This returns the tuple of the new y-axis limits.

Below examples illustrate the matplotlib.pyplot.ylim() function in matplotlib.pyplot:

Example #1:




# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
  
ax = plt.subplot(111)
  
t = np.arange(0.0, 5.0, 0.01)
s = np.cos(2 * np.pi * t)
line, = plt.plot(t, s, lw = 2)
  
plt.annotate('local max', xy =(2, 1),
             xytext =(3, 1.5),
             arrowprops = dict(facecolor ='black',
                               shrink = 0.05), )
  
plt.ylim(-2, 2)
plt.title(" matplotlib.pyplot.ylim() Example")
plt.show()


Output:

Example #2:




# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
  
np.random.seed(9680801)
  
mu, sigma = 50, 13
x = mu + sigma * np.random.randn(10000)
  
# the histogram of the data
n, bins, patches = plt.hist(x, 50
                            density = True,
                            facecolor ='g',
                            alpha = 0.75)
  
  
plt.xlabel('No of Users in K')
plt.title('Histogram of IQ')
plt.text(50, .035, r'$\mu = 50,\
\ \sigma = 13$')
  
plt.xlim(-10, 110)
plt.ylim(0, 0.04)
  
plt.grid(True)
plt.title(" matplotlib.pyplot.ylim() Example")
  
plt.show()


Output:



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