How does numpy.histogram2d works in Python

In this tutorial, we will understand what numpy.histogram2d is and how it works in Python. The Numpy library contains many functions which perform mathematical operations with arrays in Python. The histogram2d method generates a bi-directional histogram of two data samples.

Numpy.histogram2d() method

Syntax:

numpy.histogram2d(x, y, bins=10, range=None, normed=None, weights=None, density=None)

Parameters:

x: an array having the x coordinates of the points
y: an array having the y coordinates of the points
bins: defines the number of bins or bin edges
range: gives leftmost and rightmost edges of the bins
density: if true returns the probability density function at the bin, if false returns the number of samples in each bin
normed: similar to density argument
weights: an array of weights

Returns:

H: Bi-dimensional histogram of x and y.
xedges: Bin edges along the first dimension.
yedges: Bin edges along the second dimension.

Example:

Importing required libraries,

import matplotlib.pyplot as plt
import numpy as np

Define the bin edges,

xedges = [0, 2, 3, 6]
yedges = [0, 1, 3, 5, 7]

Create a histogram H,

x = np.random.normal(2, 1, 100)
y = np.random.normal(1, 1, 100)
H, xedges, yedges = np.histogram2d(x, y, bins=(xedges, yedges))
H = H.T

Histogram does not follow Cartesian convention, so we transpose H for displaying. We are using ‘imshow‘ for displaying histograms using square bins,

fig = plt.figure(figsize=(7, 4))
ax = fig.add_subplot(131, title='imshow: square bins')
plt.imshow(H, origin='lower')

Output:

You may also learn,

Python numpy.histogram() method with example