Learn Data Visualization with Python

Why Learn Data Visualization?

When we present data graphically, we can see the patterns and insights we’re looking for. It becomes easier to grasp difficult concepts or identify new trends we may have missed. We can use data visualizations to make an argument, or to support a hypothesis, or to explore our world in different ways.

Python allows us to create visualizations easily and quickly using Matplotlib and Seaborn.

Take-Away Skills:

Matplotlib is the most commonly used graphing tool in Python. You will learn how to:

Create line graphs
Create bar charts
Create pie graphs
Add error bars to graphs
Add labels and styling to graphs

Seaborn is an add-on to Matplotlib that allows us to style our graphs more professionally and create sleeker graphics. You will learn how to choose color schemes for your graphs and take them to the next level.

Notes on Prerequisites:

You should know basic Python, including how to write functions, use lists and loops, and call methods on objects.

Codecademy courses have been taken by employees at

1
Introduction to Matplotlib
Master a commonly used Python graphing module, Matplotlib. Soon, you will be producing high-quality plots to visualize your data.
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2
Introduction to Seaborn
Use Seaborn, a Python data visualization library, to create bar charts for statistical analysis.
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What you'll create

Portfolio projects that showcase your new skills

How you'll master it

Stress-test your knowledge with quizzes that help commit syntax to memory

— Madelyn, Pinterest

I know from first-hand experience that you can go in knowing zero, nothing, and just get a grasp on everything as you go and start building right away.