Introduction to ggplot2 (Part One): Data Visualisation in R and the Grammar of Graphics

In this video we'll talk about data visualisation and why the ggplot2 package in R is the perfect choice. We'll also go over the general principles underlining ggplot2 and talk about the three key elements: data, aesthetics, and geometry.

Watch more of our videos on an Introduction to R here:

More information can be found in the accompanying document available at:

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Useful links referenced in this series:

Statistics for Sustainable Development is a not-for-profit, social enterprise that provides:
• Statistical and data management expertise
• Support on research designs and methodology
• Technical guidance related to collection and processing of data and information.

As a team of technicians and statisticians, we believe that our best work is done when supporting organisations and communities across the world that share our vision of a more sustainable future for all.

The videos on our channel aim to support students, researchers, and academics, and are accompanied by the free resources on our website.

This video was created and presented by Sam Dumble, a statistician at Stats4SD. Video production is by Emily Nevitt, a graphic and instructional designer at Stats4SD.

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Contents:
00:00 - Intro
00:18 - What is the Purpose of Data Visualisation?
01:24 - Exploratory Graphs
02:31 - Explanatory Graphs
03:52 - Software for Exploratory vs Explanatory Graphs
04:52 - Advantages of ggplot2
05:41 - What is ggplot2?
06:43 - What is the Tidyverse?
07:46 - Base Plotting Library in R vs ggplot2
11:37 - Getting Started with ggplot2
12:39 - The Grammar of Graphics (Elements of a Graph)
15:03 - Data, Aesthetics and Geometry in Practice
21:33 - Summary
22:40 - Further Resources

[osoriomatucurane]

Absolutely awesome tutorial on the foundations of ggplot2.
Beyond any reasonable dought, ggplot is powerful and stands high among competitor packages and it is worthy investing your time to get grip on it, but plotly shines when it comes to interactive side, specially when the task is exploratory analysis. Of course you can zoom in and out with ggplot by changing the axis limit with the ylim() or xlim().
Thank you professor for the amazing tutorial!

[torbjornstorli]

Well done. Great video. I am curious, what software did you use to generate the animated presentation? Perhaps you should make a video about how you did it!! Thanks again.