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.
Author Name: Martin Burger
Author Description:
Martin studied biostatistics and worked for several pharmaceutical companies before he became a data science consultant and author. He published over 15 courses on R, Tableau 9 and other data science related subjects. His main focus lies on analytics software like R and SPSS but he is also interested in modern data visualization tools like Tableau. If he is not busy coding, blogging or working out new teaching concepts you may find him skiing or hiking in the Alps.

Table of Contents

• Course Overview
  1min
• Exploring the Matplotlib Data Visualization Package
  28mins
• Modifying a Matplotlib Visualization
  38mins