Data Visualization with R

This tutorial provides an introduction to data visualization in the field of data science, specifically focusing on R and the ggplot2 software. The course covers the basics of creating meaningful and visually appealing data visualizations using the grammar of graphics plotting concepts. ggplot2 is widely recognized as the go-to tool for creating professional and flexible plots in R. The course emphasizes three main layers of a plot: Geometries, Data, and Aesthetics. By mastering these concepts, participants will gain the ability to create complex exploratory plots. This course overview serves as a valuable resource for those interested in delving into the world of data visualization and analytics within the realm of data science.

The ggplot2 course builds on the knowledge from the introductory course, and creates explanation plots. Statistics will automatically be calculated and you'll learn how Coordinates and Facets can help with communication. We will discuss best practices to help you understand data visualization using ggplot2. By the end of this course, you will be able create a custom plotting tool that allows for large data sets to be explored with great visuals and statistics.

This course will help you improve your data visualization skills beyond the basic level and make them an important part of your data science toolkit. Two different datasets will be used to illustrate different types of data (proportions, point-data, single distributions and multiple distributions). We will also discuss the advantages and disadvantages of common visualizations. We'll also be discussing lesser-known visualizations, and how to adjust default settings for ggplot so you can effectively communicate your message.