Description
Course info
Level
Beginner
Updated
Apr 16, 2020
Duration
1h 8m
Description

Matplotlib enables users to create clear and compelling data visualizations in Python. In this course, Build Your First Data Visualization with Matplotlib, you’ll learn how one of the most popular packages of Python can be used to create state of the art data visualizations. First, you’ll see how to get an optimal user interface which includes Python, Jupyter Notebook and the required libraries Matplotlib, Pandas and Numpy. Next, you’ll discover the standard code setup in Matplotlib Pyplot and how it can be adjusted. After that, you'll explore how different chart types are created and formatted. As far as formatting is concerned, you'll look at text elements, axes, legends, markers and ready made style sheets, as well as the optimal data preparation steps required for particular data visualization types. Finally, you’ll learn about shared axis plots and sheet layouts which are handy for reports and presentations.. When you’re finished with this course, you’ll have the knowledge to understand the general structure of the Matplotlib library and how it helps you in data analysis.

About the author
About the author

Martin is a trained biostatistician, programmer, consultant and data science enthusiast. His main objective: Explaining data science in a straightforward way. You can find his latest work over at: r-tutorials.com

More from the author
More courses by Martin Burger
Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
[Autogenerated] welcome to build your first data visualization with mad plot Lip. This is Martin Berger for Parasite. In this beginner level course, we're exploring an excellent Python data visualization tour in mad blood liver. You can create pretty much any data visualization. There are almost no limits thanks to the various models off the package. That is the reason why so many people use it. And there is a village developer community which makes Matt blood live even better. Now, in this course, I will show you how the package works with how standard charts are created. I'm going to demonstrate how to modify the charge in terms of labels, text elements, access, coloration and shapes. You're also going to see the subplot function for multiple plots on the same sheet. Fortunately, Matt, blood lip is consistent with the code sat up. Once you understand the general set up, you can pretty much create any charge Type this feature significantly reduces the time needed to master the talk. Now, to fully benefit from this course, you just need some basic understanding off Pattan. No prior knowledge of Matt blood lib or statistics is required. All right? I really hope you use this course to explore pattern data visualizations