Plotting A 2D-Histogram Using Matplotlib

Overview:

  • A 2D Histogram is very similar to the 1D Histogram.

 

  • In a 2D Histogram, class intervals are drawn in both X-axis and the Y-axis.

 

  • Unlike a 1D Histogram, 2D Histogram is plotted by counting the combination of values that occur in X and Y class intervals - and marking the densities.

 

  • A 2D Histogram is useful when there is lot of data in a bivariate distribution. 2D Histogram simplifies visualizing the areas where the frequency of variables is dense.

 

  • To plot a 2D histogram the length of X data and Y data should be equal.

 

  • Matplotlib provides hist2d() as part of the matplotlib.pyplot module which is used for plotting 2D Histograms.

 

Example:

import matplotlib.pyplot as plot

import numpy as np

 

# Data 1

x = (20, 30, 40, 50, 60, 70)

y = (10, 10, 10, 10, 10, 10)

 

# Plot frequency distribution using histogram

plot.hist2d(x, y)

plot.title("2D Histogram Construction")

plot.margins(0)

plot.colorbar()

# Display the histogram

plot.show()

 

Output:

By changing the data as the 2D-Histogram changes depicting the more number of 10s added in the x and y with increased density denoted by the yellow square, in the output below

New data is given by,

x = (20, 30, 40, 50, 60, 70,10,10,10)

y = (20, 10, 10, 10, 10, 10,10,10,10)

The color bar aids in decoding the density values.

Output:

Construction of 2D Histogram


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