Matplotlib.axes.Axes.set_xlabel() in Python

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.set_xlabel() Function

The Axes.set_xlabel() function in axes module of matplotlib library is used to set the label for the x-axis.

Syntax: Axes.set_xlabel(self, xlabel, fontdict=None, labelpad=None, **kwargs)

Parameters: This method accepts the following parameters.

  • xlabel : This parameter is the label text.
  • labelpad : This parameter is the spacing in points from the axes bounding box including ticks and tick labels.

Returns:This method does not returns any value.



Below examples illustrate the matplotlib.axes.Axes.set_xlabel() function in matplotlib.axes:

Example 1:

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import matplotlib.pyplot as plt
import numpy as np
  
t = np.arange(0.01, 5.0, 0.01)
s = np.exp(-t)
  
fig, ax = plt.subplots()
  
ax.plot(t, s)
ax.set_xlim(5, 0)
ax.set_xlabel('Display X-axis Label'
               fontweight ='bold')
ax.grid(True)
  
ax.set_title('matplotlib.axes.Axes.set_xlabel()\
 Examples\n', fontsize = 14, fontweight ='bold')
plt.show()

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Output:

Example 2:

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# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
  
with cbook.get_sample_data('goog.npz') as datafile:
    price_data = np.load(datafile)['price_data'].view(np.recarray)
      
# get the most recent 250
# trading days
price_data = price_data[-250:]  
  
delta1 = np.diff(price_data.adj_close)/price_data.adj_close[:-1]
  
volume = (25 * price_data.volume[:-2] / price_data.volume[0])**3
close = (0.03 * price_data.close[:-2] / 0.03 * price_data.open[:-2])**2
  
fig, ax = plt.subplots()
ax.scatter(delta1[:-1], delta1[1:],
           c = close, s = volume,
           alpha = 0.5)
  
ax.set_xlabel(r'X-axis contains $\Delta_i$ values',
              fontweight ='bold')
ax.grid(True)
fig.suptitle('matplotlib.axes.Axes.set_xlabel() Examples\n',
             fontsize = 14, fontweight ='bold')
  
plt.show()

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Output:




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