Different libraries in Python

https://realpython.com/python-statistics/

Python’s statistics is a built-in Python library for descriptive statistics. You     can use it if your datasets are not too large or if you can’t rely on importing    other libraries.

NumPy is a third-party library for numerical computing, optimized for working with single- and multi-dimensional arrays. Its primary type is the array type called ndarray. This library contains many routines for statistical analysis.

SciPy is a third-party library for scientific computing based on NumPy. It offers additional functionality compared to NumPy, including scipy.stats for statistical analysis.

Pandas is a third-party library for numerical computing based on NumPy. It excels in handling labeled one-dimensional (1D) data with Series objects and two-dimensional (2D) data with DataFrame objects.

Matplotlib is a third-party library for data visualization. It works well in combination with NumPy, SciPy, and Pandas.