Simply being able to produce a graph in Python isn’t always enough to get the point across. In this course, you will learn how to communicate insights and tell stories using data visualization.
You’ll start by learning how to create visually attractive plots using Seaborn, which is a Python data visualization library based on matplotlib. It is used for drawing appealing and informative statistical graphics. In addition, you will learn how to use basemap, a toolkit built on top of matplotlib that is primarily used to create 2D graphical representations in Python. Basemap is a popular choice for plotting and visualizing geographic data.
This course is all about learning how to tell a story using data, so you will also learn some design best practices for data visualization. We’ll cover what it means to be mindful of the data-ink ratio for plots, how to choose good colors, and how to lay out your data so that it’s easily readable. You will also learn how to add annotations to your visualization to provide additional context and add clarity to your presentations.
At the end of the course, to practice your data storytelling skills you’ll create a portfolio project that visualizes the gender gap in various college degrees. You’ll end up with a beautiful data storytelling project that you can show off to potential future employers.
By the end of this course, you'll be able to:
Learn to Tell a Story Using Data
Improving Plot Aesthetics
Learn how to improve how your plots look.
Color, Layout, and Annotations
Learn how to use color, layout, and annotations to improve the viewing experience.
Visualizing The Gender Gap In College Degrees
Learn how to create a presentation-ready visualization and export it.
Learn how to create attractive conditional plots using Seaborn.
Visualizing Geographic Data
Learn how to visualize geographic data through working with flight data.