# Matplotlib Histrograms – hist() Function

### What is Histogram?

Before diving into how to create histograms in matplotlib, let us first understand what is a histogram?

So a histogram is an accurate representation of the distribution of numerical data.

• So Histogram is a type of bar graph and it was invented by Karl Pearson
• The Histogram is mainly used to represent the data that is provided in some groups.
• Histograms usually consist of bins of data(consecutive and non-overlapping intervals of variables), where each bin consists of minimum and maximum values.
• To estimate the probability distribution of the continuous variable, histogram is used.

## Creating a Histogram

There are a few steps that should be kept in mind while creating a Histogram:

1. The first step is to create the bin of the ranges.
2. The second step is to distribute the whole range of the values into a corresponding series of intervals.
3. The third step is to count the values in each interval.

### `matplotlib.pyplot.hist()` Function

This function is used to create the histogram.

Let us discuss the parameters of the histogram and the detailed description is given below:

• xThis parameter indicates an array or sequence of arrays.
• binsThis parameter indicates an integer or sequences or any string.
• densityThis is an optional parameter that consists of boolean values.
• rangeThis is an optional parameter used to indicate upper and lower range of bins and it is also an optional parameter.
• labelThis is an optional parameter and is used to set the histogram axis on a log scale.
• colorThis is an optional parameter used to set the color.
• cumulativeIf the value of this option is set to true, then a histogram is computed where each bin gives the counts in that bin plus all bins for smaller values.
• histtypeThis is an optional parameter used to specify the type of histogram [that is barbarstackedstepstepfilled]. The default value of this parameter is “bar“.
• alignThis is an optional parameter that controls the plotting of histogram having values [leftrightmid].

Let us take a look at a few examples to understand the concept of the histogram.

### Simple Histogram Plot Example:

Below we have a simple example to create a histogram:

``````import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt

x = [21,22,23,4,5,6,77,8,9,10,31,32,33,34,35,36,37,18,49,50,100]
num_bins = 5
n, bins, patches = plt.hist(x, num_bins, facecolor='orange', alpha=0.8)
plt.show()``````

The output in the form of histogram is as follows:

### Two Histogram in one Figure Example:

Let us try two plot with two histograms together. In the code snippet given below, we are trying to draw two histograms together:

### 2D Histogram Example:

Let us try to create a two-dimensional histogram. The code snippet for the 2D histogram is as follows:

``````import numpy as np
import matplotlib.pyplot as plt
mean = [0, 0]
cov = [[1, 1], [1, 2]]
x, y = np.random.multivariate_normal(mean, cov, 10000).T # x and y are array that are drawn from a multivariate Gaussian distribution

plt.hist2d(x, y, bins=30, cmap='CMRmap') #plt.hist2d is used to draw histogram for 2D
cb = plt.colorbar()
cb.set_label('counts in bin')
plt.show()``````

Output Histogram is as follows: