Matplotlib.axes.Axes.has_data() in Python

Last Updated : 30 Apr, 2020

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.has_data() Function

The Axes.has_data() function in axes module of matplotlib library is used to check if any artists have been added to axes.

Syntax: Axes.has_data(self) Parameters: This method does not accepts any parameter. Returns: This method return True if any artists have been added to axes.

Below examples illustrate the matplotlib.axes.Axes.has_data() function in matplotlib.axes: Example 1:

Python3

# ImpleIn Reviewtation of matplotlib function  
import matplotlib.pyplot as plt
  
fig, ax1 = plt.subplots( )
ax1.set_xscale("log")
ax1.set_yscale("log")
ax1.set_adjustable("datalim")

ax1.plot([1, 3, 34, 4, 46, 3, 7, 45, 10],
         [1, 9, 27, 8, 29, 84, 78, 19, 48],
          "o-", color ="green")

ax1.set_xlim(1e-1, 1e2)
ax1.set_ylim(1, 1e2)

w = ax1.has_data()

print("Value Return by has_data() :", w)
 
fig.suptitle('matplotlib.axes.Axes.has_data()\
 function Example\n\n', fontweight ="bold")

fig.canvas.draw()

plt.show()

Output:

Value Return by has_data() : True

Example 2:

Python3

# ImpleIn Reviewtation of matplotlib function  
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
   
n_angles = 36
n_radii = 10
min_radius = 2
radii = np.linspace(min_radius, 0.95, n_radii)
   
angles = np.linspace(0, 2 * np.pi, n_angles,
                     endpoint = False)
angles = np.repeat(angles[..., np.newaxis], 
                   n_radii, axis = 1)
angles[:, 1::2] += 2 * np.pi / n_angles
   
x = (radii * np.cos(angles)).flatten()
y = (radii * np.sin(angles)).flatten()
   
triang = tri.Triangulation(x, y)
   
triang.set_mask(np.hypot(x[triang.triangles].mean(axis = 1),
                         y[triang.triangles].mean(axis = 1))
                < min_radius)
fig, ax = plt.subplots()
   
ax.triplot(triang, 'bo-', lw = 1, color = "green")

w = ax.has_data()

print("Value Return by has_data() :", w)
 
fig.suptitle('matplotlib.axes.Axes.has_data() function\
 Example\n\n', fontweight ="bold")

fig.canvas.draw()

plt.show()