Matplotlib: Visualization with Python

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK. There is also a procedural “pylab” interface based on a state machine (like OpenGL), designed to closely resemble that of MATLAB, though its use is discouraged. SciPy makes use of Matplotlib.

Toolkits :

Several toolkits are available which extend Matplotlib functionality. Some are separate downloads, others ship with the Matplotlib source code but have external dependencies.

• Basemap: map plotting with various map projections, coastlines, and political boundaries
• Cartopy: a mapping library featuring object-oriented map projection definitions, and arbitrary point, line, polygonand image transformation capabilities. (Matplotlib v1.2 and above)
• Excel tools: utilities for exchanging data with Microsoft Excel
• GTK tools: interface to the GTK library
• Qt interface
• Mplot3d: 3-D plots
• Natgrid: interface to the natgrid library for gridding irregularly spaced data.
• matplotlib2tikz: export to Pgfplots for smooth integration into LaTeXdocuments
• Seaborn: provides an API on top of Matplotlib that offers sane choices for plot style and color defaults, defines simple high-level functions for common statistical plot types, and integrates with the functionality provided by Pandas

The hour-long course starts off with an introduction to Matplotlib, including how to install and import it in Python. We will then move on to learn how you can create and customize basic 2D charts in order to best tell your story. Furthermore, you will also learn what subplots are and how you can create as well as customize them with the help of the Matplotlib library.

We will explore the full spectrum of interactive and explorable graphic representations including various plots such as Scatter, Line, Bar, Stacked Bar, Histogram, Pie, and much more. The course also walks you through the basics of creating a 3D plot in Matplotlib and how you can start plotting images using the Python visualization library.

And, once you are done with this course, you will be able to create almost any kind of plot that you need with Matplotlib and Python.

Why you should take this course?

• Updated 2021 course content: All our course content is updated as per the latest version of the Matplotlib library.
• Practical hands-on knowledge: This course is oriented to providing a step-by-step implementation guide for making amazing data visualization plots rather than just sticking to the theory.
• Guided support: We are always there to guide you through the Q/As so feel free to ask us your queries

Thanks to Mr.Abbosjon Madiev, Coumputer Scientist

Source : www.udemey.com