BLACK FRIDAY BLOWOUT! Mega 5-Day Sale - 35% Off ALL Certs and Diplomas!

Claim My Discount!

Data Visualization with Python and Matplotlib

In this free online course, learn how to use data visualization with Python and Matplotlib to enhance your data analysis

Publisher: Stone River eLearning
Discover the value of using Python and Matplotlib to create graphs that can help your clients or organization visualize data and make informed business decisions with this free online course. You will be taught how to create different types of Matplotlib charts and plots along with the many platform customization options and everything from adding legends to a chart and creating moving averages to using stack plots.
  • Duration

    4-5 Hours
  • Students

  • Accreditation






View course modules


Are you looking to become an expert in data visualization with Python using one of its most important modules named Matplotlib?  This course makes Python Data Visualisation easy and introduces you to Matplotlib and all its tools for creating graphs. The first section of this data visualization course includes learning about the options and possible customizations in Matplotlib. You will study the basics of working with Matplotlib, creating a graph and its essential elements such as labels, legends and titles, loading data from an external file, and the different types of plots and graphs available. The key differences between a histogram and a bar chart along with when to use each one is then discussed. 

The second part of this free online course teaches you how to plot items geographically on maps using the Basemap extension and the process involved in feeding latitudinal and longitudinal coordinates to your graph in Matplotlib. These techniques are then demonstrated to plot on various map types, such as globes and flat maps. The next discussion covers the value of using three-dimensional graphs and how the addition of another axis gives you the ability to compare three types of features and project the relationship between these three variables. The final content covered analyzes basic subplot additions, moving averages, Basemap customization options, and basic 3D graph examples using the Matplotlib wireframe. 

Data is more valuable when it is easily understood and being able to visualize complex data goes a long way in simplifying data and identifying trends. You should enrol in this course if you work with data on a daily basis or are a data scientist looking to improve your skills because this critical skill can add value across many business functions.

Start Course Now