Matplotlib.pyplot.hist2d() in Python

Last Updated : 21 Apr, 2020

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.hist2d() Function

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

Syntax:matplotlib.pyplot.hist2d(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.pyplot.hist2d() function in matplotlib.pyplot:

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) + 50
   
plt.hist2d(x, y, 
           bins = 100,  
           norm = colors.LogNorm(),  
           cmap ="gray") 
  
plt.title('matplotlib.pyplot.hist2d() function \ 
Example\n\n', fontweight ="bold") 
  
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=1000000), 
    multivariate_normal([30, 20], 
            [[2, 3], [1, 3]], size=100000) 
]) 
  
plt.hist2d(result[:, 0], 
           result[:, 1], 
           bins = 100,  
           cmap = "Greens", 
           norm = colors.LogNorm()) 
plt.title('matplotlib.pyplot.hist2d function \ 
Example') 
plt.show() 
  
plt.hist2d(result[:, 0],  
           result[:, 1], 
           bins = 100,  
           cmap = "RdYlGn_r", 
           norm = colors.LogNorm()) 
plt.show() 
 
  