What is the numpy.histogram() Method in Python?

NumPy is a very powerful Python library that is used to support calculations performed for large, multi-dimensional arrays and matrices. Along with support for arrays, there are a lot of high-level mathematical functions to operate on these arrays.

Apart from functions regarding arrays, there is a lot of support for plotting functions in NumPy. NumPy has a built-in function called NumPy histogram(), which helps us to create histogram plots using NumPy in Python.

In this article, we will learn about the NumPy histogram() function, along with its syntax, parameters, and some examples.

Creating NumPy Histogram

The NumPy histogram() function displays the frequency of data distribution in a numerical form. Rectangles with varied heights and identical horizontal sizes represent frequency and a class interval called a bin, respectively.

Output

Syntax for NumPy histogram()

The syntax for NumPy histogram() is:

Parameters for NumPy histogram()

The parameters for NumPy histogram() are:

• arr: This mandatory parameter defines the array over which the histogram is generated.
• bins: This optional parameter is a set of ranges which define the number of equal-width bins/containers.
• range: This optional parameter defines the upper and lower ranges of the bins mentioned above.
• density: This optional parameter takes in boolean values. If the value is set to True, then the number of samples in every bin will be displayed.

Return Type for NumPy histogram()

The NumPy histogram() functions return two values:

• hist: The set of values of the histogram as a list.
• bins: The edges of the bins are mentioned as a parameter.

Examples for NumPy histogram()

In this section, we will go over various examples and implementations of the NumPy histogram() function to get a better understanding of the function.

• Numerical and Graphical Representation

  As discussed above, the NumPy histogram() function returns the histogram values as an array and the bins. Since the graphical representation of the histogram is missing, we use the Matplotlib library to convert the numeric form of a histogram to its graphical form.

• Print Histogram with Bin Arrays

  In this example, we will utilize the NumPy histogram() function to generate a histogram and its respective bin array and print it.

  Output

• Print histogram based on the density argument

  As discussed above, the density argument, if set to True, makes sure that the number of samples is displayed with every histogram value. In this example, we will display a histogram with density set as False, and then set as True.

  Output

• Generating a bar chart using NumPy histogram()

Using NumPy histogram(), we were able to generate histogram values, as well as their respective bin values. To present our values graphically, we need to use Matplotlib.

Matplotlib is a plotting library in Python, which is used to plot graphs like bar charts, violin plots, etc.

Read More:

• upper() method in Python.