Introduction to Data Visualization in ggplot: Part 2 of 3
To Know
About this Class
This two hour in-person training builds on principles from Part 1. It introduces data visualization in R within the tidyverse ecosystem. Attendees learn the grammar of graphics framework. Attendees will use the possum dataset to create scatterplots and assign variables to color, shape, and size. The training concludes by saving plots in vector or raster formats using ggsave. Attendees should know basic R and RStudio and complete the prep work.
Attendees will receive an email with instructions for installing and verifying access to R, RStudio, and required packages before the training. If you register the day before, installing the software may take longer. If you do not install the software, the training will be a demo only.
By the end of this training, attendees will be able to:
- Identify the three fundamental components of a ggplot2 graph and explain the function of each in the context of data visualization.
- Explain the distinction between global aesthetic mappings in ggplot() and local mappings in geom_ (), and predict the impact of each on the structure of plot layers.
- Apply the layered grammar of ggplot2 to construct a scatterplot that displays variables on the x- and y-axes, incorporating an additional aesthetic to represent a third variable.
- Explain the distinctions between raster and vector file formats, and select the appropriate format, resolution, and dimensions for a given application.
- Create a customized ggplot2 scatterplot utilizing multiple aesthetics, export it in a publication-ready format, and provide a rationale for the design choices made.