Assignment 8

Data Visualization Using ggplot2

Please submit both the .Rmd and a .html file on Canvas.

Your assignment this week is to create data visualizations of your own data using ggplot2. It is okay to use additonal packages that extend ggplot2 functions, but please don’t use a package that makes the entire ggplot call for you. In other words, packages that give you more geoms are okay, but packages that create a ggplot for you without you having to add these geoms yourself are not okay.

1. First, help me understand these data. In a few sentences, describe the research design, structure of the data, and any quirks you think would be helpful for me to know about. If you are using the same data as last week, you can copy & paste your description.

2. Then, create at least 4 figures that help you understand and visualize your data. It’s okay to make the same figures as you did last week (but in ggplot2, as long as they meet the criteria below), but I encourage you do add some layers that would otherwise be more challenging in base R. You should include code to do the following at least once across your 4+ figures:

• Map aesthetics in addition to x and y
• Set aesthetics to certain feature(s) of your ggplots
• Create a plot with more than one geometry layer
• Modify the default scales
• Modify the default coordinate system
• Use theme() to modify features of your ggplot

3. At the end, use the patchwork package to combine your plots into whatever arrangement you would like

4. Then, create at least 4 figures that help you understand and visualize your data. Bonus if these figures complement each other to tell a story of your data, but this is not a requirement. You should include code to do the following at least once across your 4+ figures:

   • At least two of your figures should be a different type (e.g., do not plot 4 scatterplots)
   • Change the default point shape, line type, and/or line width
   • Change the default point, line, bar, etc. color
   • Depict different groups in your data using shape, color, and/or size
   • Include a legend when plotting multiple groups in your data
   • Change the default axes to get them closer to publication quality
   • Create multiple figures in the same window using par(mfrow = ...) or layout()
   • Add lines to your data using abline(), lines(), or matlines()
   • Change the default plot title and axis titles