Introduction to Matplotlib in Python

In Python there are thousands of libraries and Matplotlib is one of the most popular and powerful libary which is used for Data Visualization. Visualization can help us in visual access of huge amounts of data in easily digestible visuals. 
It is a type of cross-platform library which can be used for making 2D plots from given data in an array.

It was originally written by John D. Hunter in 2002. Matplotlib has a module Pyplot which has a MATLAB-like interface. Matplotlib was designed to be as usable as MATLAB with the ability to use Python.

Matplotlib is capable of creating many kinds of charts, like graphs, scatter plots, bar charts, pie charts, stack plots, 3D graphs, and geographic map graphs, histogram , etc in just few lines of codes.

It also make use of NumPy, the numerical mathematical extension of Python. It has a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack. 
It’s often used in web application servers, shells, Jupyter notebook, and Python scripts.

Matplotlib provides an object-oriented API that helps us in embedding plots in application using Python GUI toolkits such as PyQt, WxPythonotTkinter.

Matplotlib library plays an important role in Data Analysis and Data Science.

Tue, 02/09/2021 - 06:38

Authored by

Devanshi, is working as a Data Scientist with iVagus. She has expertise in Python, NumPy, Pandas and other data science technologies.
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