# Compute the histogram of a set of data in Python

In the tutorial, you will learn how to compute the histogram of a set of data. By using the NumPy module to show the data in the histogram, from picture view using the matplotlib module that will compute the histogram of a set of data.

For a better knowledge view of the huge data set, the histograms will be helpful.

## Uses of Histogram:

- To see any variations in the consider data set.
- To easily see the distribution of data.
- The large data values will be relatively in simple chart form.

### NumPy.histogram():

The NumPy module considers a lot of inbuilt functions one of it’s will be histograms consider two values bins and data set.

Let’s have a look at the general attributes of an array. They are as follows.

- An array can hold many values based on a single name.
- Access the elements based on the index number.
- We can slice the elements in the array [start: end] based on the start and end position -1 elements display the results.

### Importing module:

import matplotlib.pyplot as p import numpy

From the above to modules NumPy will be used to the histogram representation and matplotlib will be used to picture view of data set.

### Program to display the histogram:

From the below code you get an idea about the histogram of a data set.

import matplotlib.pyplot as p import numpy x=[1,2,3,999] print(numpy.histogram(x)) p.hist(x) p.show()

Output:

(array([3, 0, 0, 0, 0, 0, 0, 0, 0, 1], dtype=int32), array([ 1. , 100.8, 200.6, 300.4, 400.2, 500. , 599.8, 699.6, 799.4, 899.2, 999. ]))

The histogram image will be as below:

##### Explanation:

- From the above code, we consider a data set x consider three values [1,2,3].
- By using the NumPy module histogram function display the output.
- For the picture view, we consider the Mathplotlib module displays the picture view of the histogram by hist() function.

Also read: Plot a histogram for an Image in PIL in Python and Plotting a Histogram in Python using Seaborn

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