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:

Python3 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:

Python3 1==

#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()