Matplotlib.axes.Axes.set_label() 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_label() Function

The Axes.set_label() function in axes module of matplotlib library is used to set the label that will be displayed in the legend.

Syntax: Axes.set_label(self, s)

Parameters: This method accepts only one parameters.

• s: This parameter is converted to a string by calling str.

Returns: This method does not return any value.

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

Example 1:

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.collections import EllipseCollection


x = np.arange(10)
y = np.arange(15)
X, Y = np.meshgrid(x, y)

XY = np.column_stack((X.ravel(), Y.ravel()))

fig, ax = plt.subplots()

ec = EllipseCollection(10, 10, 5, units ='y',
                       offsets = XY * 0.5,
                       transOffset = ax.transData,
                       cmap ="inferno")

ec.set_array((X * Y + X * X).ravel())

ax.add_collection(ec)
ax.autoscale_view()

ax.set_xlabel('X')
ax.set_ylabel('y')

cbar = plt.colorbar(ec)
cbar.set_label('X + Y')

fig.suptitle('matplotlib.axes.Axes.set_label() function \
Example\n', fontweight ="bold")

fig.canvas.draw()

plt.show()

Output:

Example 2:

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np


np.random.seed(19680801)

n = 100000
x = np.random.standard_normal(n)
y = 2 * np.random.standard_normal(n)
z =[1, 2, 3, 4]

xmin = x.min()
xmax = x.max()
ymin = y.min()
ymax = y.max()

fig, ax = plt.subplots()
hb = ax.hexbin(x, y, gridsize = 50, bins ='log', cmap ='BuGn')
ax.set(xlim =(xmin, xmax), ylim =(ymin, ymax))

cb = fig.colorbar(hb, ax = ax)
cb.set_label('log')

fig.suptitle('matplotlib.axes.Axes.set_label() function\
 Example\n', fontweight ="bold")

fig.canvas.draw()

plt.show()

Output: