Learn Data Visualization with Python

Learn how to present data graphically with Python, Matplotlib, and Seaborn.

### 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.

• Introduction to Matplotlib: Master a commonly used Python graphing module, Matplotlib. Soon, you will be producing high-quality plots to visualize your data.
• Line Graphs in Matplotlib
• Line Graphs Concepts
• Sublime Limes' Line Graphs
• Different Plot Types
• Plot Types
• How to Select a Meaningful Visualization
• Recreate Graphs using Matplotlib!


• Introduction to Seaborn: Use Seaborn, a Python data visualization library, to create bar charts for statistical analysis.
• Learn Seaborn Introduction
• Learn Seaborn: Distributions
• Introduction To Seaborn
• Seaborn Styling, Part 1: Figure Style and Scale
• Seaborn Styling, Part 2: Color
• Visualizing World Cup Data With Seaborn