Dataviz and Interactive Tools

Introduction

We’re going to learn how to make a variety of static and interactive plots in R. Vizualizing data is an essential skill in science and knowing at least one tool well will serve you in the future. For static graphics, I prefer and recommend ggplot2. For interactive graphics, I’d like to introduce you to Shiny.

These two packages will be taught in their own submodules:

• ggplot2
• Shiny

And if we have time I want to introduce some really awesome R packages:

• Trelliscope (explore data quick)
• htmlwidgets (advanced visualizations)
  • Example: https://github.com/amoeba/bristol_bay_permit_viz
• plotly (easy interactive plots)
• dygraph (easy interactive timeseries plots)

Learning outcomes

After completing this module, students should:

• Be able to make simple to intermediate plots in R using ggplot2
• Be able to a simple Shiny app
• Have an increased awareness of plotting options in R

and students should have an awareness of the great number of visualization tools provided in R and what they’re useful for.

Lesson

See submodules 1 and 2 in this same folder.

Resources

• http://ggplot2.tidyverse.org/
• R for Data Science
• http://enhancedatascience.com/2017/07/06/pick-best-r-packages-interactive-plot-visualisation-22/
• http://enhancedatascience.com/2017/04/12/pick-best-r-packages-data-visualization/