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Data Visualization in Python

Now that you have loaded data, how do you gain insights into that data? In this module see how to use some of the libraries available with Python to examine our data set. In order to better understand the data, we will learn how to build visualizations such as charts, plots, and graphs.. We’ll use some common tools such as matplotlib and seaborn and gather some statistical insights into our data.

For the lab, you will be following these lab instructions


Scott D’Angelo

Developer Advocate

Scott D’Angelo is a Senior Software Engineer at IBM, where he focuses on delivering applications that showcase IBMs Cognitive, Data and Analytics portfolio. Previously, Scott was contributor to OpenStack, an open source project that provides Infrastructure-as-a-Service. He focused on its Block Storage service, code named Cinder, as a member of the Core Developer team.