Course
Communicating with Data in the Tidyverse
BasicSkill Level
Updated 03/2025RData Visualization4 hr15 videos53 Exercises4,350 XP33,818Statement of Accomplishment
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Prerequisites
Introduction to the Tidyverse1
Custom ggplot2 Themes
In this chapter, you will have a first look at the data you're going to work with throughout this course: the relationship between weekly working hours and monetary compensation in European countries, according to the International Labour Organization (ILO). After that, you'll dive right in and discover a stunning correlation by employing an exploratory visualization. You will then apply a custom look to that graphic – you'll turn an ordinary plot into an aesthetically pleasing and unique data visualization.
2
Creating a Custom and Unique Visualization
Barcharts, scatter plots, and histograms are probably the most common and effective data visualizations. Yet, sometimes, there are even better ways to visually highlight the finding you want to communicate to your audience. So-called "dot plots" make us better grasp and understand changes in data: development over time, for example. In this chapter, you'll build a custom and unique visualization that emphasizes and explains exactly one aspect of the story you want to tell.
3
Introduction to RMarkdown
Back in the old days, researchers and data analysts used to generate plots in R and then tediously copy them into their LaTeX or Word documents. Nowadays, whole reports can be produced and reproduced from within R and RStudio, using the RMarkdown language – combining R chunks, formatted prose, tables and plots. In this chapter, you'll take your previous findings, results, and graphics and integrate them into such a report to tell the story that needs to be told.
4
Customizing Your RMarkdown Report
Your boss, your client, or your professor usually expects your results to be accurate and presented in a clear and concise structure. However, coming up with a nicely formatted and unique report on top of that is certainly a plus and RMarkdown can be customized to accomplish this. In this last chapter, you'll take your report from the last chapter and brand it with your own custom and unique style.
Communicating with Data in the Tidyverse
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FAQs
What real-world data is used throughout this course?
You will work with International Labour Organization data on the relationship between weekly working hours and monetary compensation across European countries.
What will I learn beyond basic ggplot2 plotting?
You will learn to create custom ggplot2 themes, build unconventional visualizations like dot plots, and produce styled reports using RMarkdown with custom CSS.
Does the course teach how to create reports in RMarkdown?
Yes. Chapters 3 and 4 cover integrating your ggplot2 visualizations into RMarkdown reports and customizing them with your own branding and CSS styles.
What is the only prerequisite for this course?
You need to have completed Introduction to the Tidyverse, which provides the foundational dplyr and ggplot2 skills this course builds upon.
Who would benefit most from taking this course?
Anyone who needs to communicate data findings to stakeholders through polished, publication-quality graphics and branded reports will find this course directly applicable.
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