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.xticks() Function
The annotate() function in pyplot module of matplotlib library is used to get and set the current tick locations and labels of the x-axis.
Syntax:
matplotlib.pyplot.xticks(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.xticks() function in matplotlib.pyplot:
Example #1:
# Implementation of matplotlib.pyplot.xticks()# function import numpy as npimport matplotlib.pyplot as plt x = [1, 2, 3, 4]y = [95, 38, 54, 35]labels = ['Geeks1', 'Geeks2', 'Geeks3', 'Geeks4'] plt.plot(x, y) # You can specify a rotation for the tick# labels in degrees or with keywords.plt.xticks(x, labels, rotation ='vertical') # Pad margins so that markers don't get # clipped by the axesplt.margins(0.2) # Tweak spacing to prevent clipping of tick-labelsplt.subplots_adjust(bottom = 0.15)plt.show() |
Output:
Example #2:
# Implementation of matplotlib.pyplot.xticks()# 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.xticks(visible = False)plt.show() |
Output:
