Python Visualization Tools

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In this Lesson, we cover Python Visualization Libraries and Tools, focusing particularly on Marplot and the Seaborn plotting library. You will learn how to use these to visualize your data using Python in a clear and effective way. We will go into depth particularly on Seaborn and you'll learn about the different plot available including regression plots, pairplots, and heat maps.

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Learning Objectives

  • Use Marplot to create plots to epresent data, and format the plots
  • Add information to plots such as labels, titles, legends, etc.
  • Get acquainted with the Seaborn plotting library
  • Learn how to plot data using Seaborn in a variety of different plots

Intended Audience

This Lesson is intended for data scientists, data engineers, or anybody interested in learning how to use Python tools to visualize data.

Prerequisites

To get the most out of this lesson, you should be familiar with the basics of programming: variables, scope, functions.

Resources

The dataset(s) used in this lesson can be found in the following GitHub repository: https://github.com/cloudacademy/practical-data-science-python 

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Thomas Holmes, opens in a new tab
Data Science Trainer at QA Ltd.
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