Matplotlib.pyplot.yticks() in Python

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.yticks() Function

The annotate() function in pyplot module of matplotlib library is used to get and set the current tick locations and labels of the y-axis.

Syntax: matplotlib.pyplot.yticks(ticks=None, labels=None, **kwargs)

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

  • ticks: This parameter is the list of xtick locations. and an optional parameter. If an empty list is passed as an argument then it will removes all xticks
  • labels: This parameter contains labels to place at the given ticks locations. And it is an optional parameter.
  • **kwargs: This parameter is Text properties that is used to control the appearance of the labels.

Returns: This returns the following:



  • locs :This returns the list of ytick locations.
  • labels :This returns the list of ylabel Text objects.

The resultant is (locs, labels)

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

Example #1:

filter_none

edit
close

play_arrow

link
brightness_4
code

# Implementation of matplotlib.pyplot.yticks()
# function
  
import numpy as np
import matplotlib.pyplot as plt
    
# values of x and y axes 
valx = [30, 35, 50, 5, 10, 40, 45, 15, 20, 25
valy = [1, 4, 3, 2, 7, 6, 9, 8, 10, 5
    
plt.plot(valx, valy) 
plt.xlabel('X-axis'
plt.ylabel('Y-axis'
    
plt.xticks(np.arange(0, 60, 5)) 
plt.yticks(np.arange(0, 15, 1)) 
plt.show() 

chevron_right


Output:

Example #2:

filter_none

edit
close

play_arrow

link
brightness_4
code

#Implementation of matplotlib.pyplot.yticks() 
# function
   
import matplotlib.pyplot as plt
   
from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_axes
   
   
def get_demo_image():
    from matplotlib.cbook import get_sample_data
    import numpy as np
    f = get_sample_data("axes_grid/bivariate_normal.npy",
                        asfileobj=False)
    z = np.load(f)
    # z is a numpy array of 15x15
    return z, (3, 19, 4, 13)
   
   
fig, ax = plt.subplots(figsize=[5, 4])
   
Z, extent = get_demo_image()
   
ax.set(aspect=1,
       xlim=(0, 65),
       ylim=(0, 50))
   
   
axins = zoomed_inset_axes(ax, zoom=2, loc='upper right')
im = axins.imshow(Z, extent=extent, interpolation="nearest",
                  origin="upper")
   
plt.xlabel('X-axis'
plt.ylabel('Y-axis')
   
plt.yticks(visible=False)
   
   
plt.show() 

chevron_right


Output:




My Personal Notes arrow_drop_up

Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.


Article Tags :

Be the First to upvote.


Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.