What you'll learn
- Explain what aesthetic mappings are
- Explain the inheritance of aesthetic mappings
- Create any plot in ggplot2 on your own
- Solve common problems in creating plots in ggplot2
- Dodge bar charts and be able to explain how it can be done
- Explain the aesthetics of geom_point
- Order bar charts
- Use scales to adjust the mapping between aesthetics and variables
- Use facets to create multiple plots at once
- Use summary statistics to do calculations on your data on they fly with ggplot2 (e.g. error bars, means, confidence intervals)
- Make your plot look beautiful with custom themes
- Use annotations to spice up your plots
- Add mathematical notations to your plot
- Combine multiple plots with patchwork
- Adding significance bars to barplots
- Adding regression lines to scatterplots
- Export plots to high quality
- Use various apps from ggplot2tor to work with scales, theme and aesthetics in ggplot2
- Basic knowledge of R and R-Studio
- Basic knowledge of the tidyverse package
- Ability to run scripts in R-Studio
My goal with this course is for you to learn ggplot2 from the ground up. ggplot2 has a huge community and endless resources, but here's why I think this course might be for you:
Creating data visualizations in ggplot2 is tough for beginners. You need to know about data types, geometric objects, aesthetics, aesthetic mappings, dozens of functions, faceting, scales, themes and much more. You'll find many resources on the internet that teach you this content. Finding these resources takes time, and often they don't teach the fundamentals you need to know to become an independent data visualization specialist in ggplot2. I want to get you up to speed with ggplot2. While creating this course I not only created the videos, but also a comprehensive package of educational materials. Here is what you will get from this course:
More than 11 hours of videos
8 brand-new cheat sheets on the most fundamental concepts of ggplot2 which you won't find anywhere else on the internet
3 educational web apps on three of the most fundamentals problems: findings aesthetics of geometric objects, finding scales, and designing your theme
A repository with all the R-code for the course
In this course we will start with the most important concept of ggplot2, aesthetic mappings. We will then learn how to create the most basic plots. Once you are able to create these plots, we will discuss common pitfalls that beginners to ggplot2 often run into. In the next modules, we will learn how to customize aesthetic mappings with scales, how to create multiple plots by faceting, how to calculate summary statistics, and how to change the theme of your plots. Finally, we will give you some tips and tricks that everyone learning ggplot2 should know. Along the way, we will also create four best practice visualizations that cover all of the fundamental concepts we learn in this course.
I am confident that you won't find similar material anywhere else on the internet and that you will truly understand ggplot2 from the ground up if you take this course.
Disclaimer: We will cover version 3.3.4 of ggplot2.
Who this course is for:
- Any person who wants to learn ggplot2 from the ground up
- Data scientist interested in learning how to create visualizations in ggplot2 fast and effectively
- Data journalists who want to create print-ready visualizations
- Students interested in creating visualizations for their theses
- Scientists and researchers whose daily bread is to plot data
Hi, I am Christian!
I am an Instructional Designer by training and a Data Scientist by passion. I currently live in Munich, Germany, and work as a Senior Instructional Designer for an artificial intelligence company.
My journey to data and programming began in my Bachelor studies. Early on I was passionate about R and had a knack for working with data. Over the years, I became particularly passionate in data visualization and the ggplot2 package. During my PhD ggplot2, the tidyverse and web development became my bread and butter and I gained extensive experience in the R environment.
I am here to teach you what I have learned. ggplot2 and the tidyverse are fascinating packages that allow you to think with data. My goal is to make you a better data scientist. See you around!