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Matplotlib.axes.Axes.hist2d() in Python
  • Last Updated : 13 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.hist2d() Function

The Axes.hist2d() function in axes module of matplotlib library is used to make a 2D histogram plot.

Syntax: Axes.hist2d(self, x, y, bins=10, range=None, density=False, weights=None, cmin=None, cmax=None, *, data=None, **kwargs)

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

  • x, y : These parameter are the sequence of data.
  • bins : This parameter is an optional parameter and it contains the integer or sequence or string.
  • range : This parameter is an optional parameter and it the lower and upper range of the bins.
  • density : This parameter is an optional parameter and it contains the boolean values.
  • weights : This parameter is an optional parameter and it is an array of weights, of the same shape as x.
  • cmin : This parameter has all bins that has count less than cmin will not be displayed.
  • cmax : This parameter has all bins that has count more than cmax will not be displayed.

Returns: This returns the following:



  • h :This returns the bi-dimensional histogram of samples x and y.
  • xedges :This returns the bin edges along the x axis.
  • yedges :This returns the bin edges along the y axis.
  • image :This returns the QuadMesh.

Below examples illustrate the matplotlib.axes.Axes.hist2d() function in matplotlib.axes:

Example-1:




    
# Implementation of matplotlib function
from matplotlib import colors
from matplotlib.ticker import PercentFormatter
import numpy as np
import matplotlib.pyplot as plt
  
N_points = 100000
x = np.random.randn(N_points)
y = .4 * x + np.random.randn(100000) + 5
  
fig, ax = plt.subplots()
ax.hist2d(x, y, bins = 100
          norm = colors.LogNorm(),
          cmap ="Greens")
  
ax.set_title('matplotlib.axes.Axes.\
hist2d() Example')
  
plt.show()

Output:

Example-2:




# Implementation of matplotlib function
from matplotlib import colors
import numpy as np
from numpy.random import multivariate_normal
import matplotlib.pyplot as plt
  
result = np.vstack([
    multivariate_normal([10, 10],
            [[3, 2], [2, 3]], size = 100000),
    multivariate_normal([30, 20],
            [[2, 3], [1, 3]], size = 1000)
])
  
fig, [axes, axes1] = plt.subplots(nrows = 2
                                  ncols = 1,
                                  sharex = True)
  
axes.hist2d(result[:, 0], result[:, 1],
            bins = 100, cmap ="GnBu",
            norm = colors.LogNorm())
  
axes1.hist2d(result[:, 0], result[:, 1],
             bins = 100, norm = colors.LogNorm())
  
axes.set_title('matplotlib.axes.Axes.\
hist2d() Example')
  
plt.show()

Output:

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