Updated data vis slides

[mfiorina]

Changes made:

• Added suggested use_course() slide structure. Attempt to address Evaluate the option of using use_course #120.
• Changed language for exercise 1. Closes March 2023 - Data vis #117.
• Changed inclusion of the latam variable to occur prior to plot creation. Closes May 2022 - Data Visualization #96.
• flair package from CRAN doesn't work with r 4.3.2. Updated .Rmd to pull from GitHub. Hopefully this doesn't cause issues, although if it does, the package use isn't crucial, just nice.

[ramarty]

1. On slide 24, maybe add +geom_point(), just so its similar structure to next one and previous code.
2. On slide 26, maybe simplify this: mutate(latam = ifelse(region == "Latin America and Caribbean", TRUE, FALSE)) to just mutate(region == "Latin America and Caribbean"). Although maybe a reason not to simplify?
3. Not sure if there's a good way to fit this, but for changing scales, one thing that may be kinda common is to have a variable that is a proportion that you want to represent as a percent. Not sure if we can fit using this into an example: scale_y_continuous(labels = scales::percent) (or more simply could link to this as a resource maybe? https://thomasadventure.blog/posts/ggplot2-percentage-scale/)
4. Maybe on additional thing that could be helpful to include is using scale_[x/y]_continuous to change breaks, labels, and range? For example, if data shows something from 0 to 70%, may want to change plot to show up to 100%. Also may want to reduce/increase number of labels. Although realize there's about 453,273 different things we can teach about ggplot so we need to limit -- but this potentially may be common-ish enough to reference?

[mfiorina]

Thank you @ramarty! I've implemented the following changes:

• Corrected lack of geom_point() in slide 26
• Implemented suggested change in slide 36
• Could find a good use case with the current dataset for scales::percent, but something I'll keep in mind. Changed use of scale_log_10() to scale_x_continuous() which I agree is more commonly used and useful