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:

Python3

  
# 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:

Python3

# 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()