Additional Resources:

• R for Data Science Chapter 13: Relational data
• R for Data Science Chapter 3: Data visualization
• R for Data Science Chapter 28: Graphics for communication
• R for Data Science Chapter 16: Dates and times

Run the code below to load the congress dataframe we will use in this quiz

library(tidyverse)
load(url('https://dssoc.github.io/datasets/congress.RData'))

Questions

1. Create a bar plot to show the average ages of democrat and republican congress members. Now do the same for M and F genders (this second part should include members of all parties).

2. Create two bar charts: one that shows the total number of social media accounts among democrats and republicans (Twitter, Facebook, YouTube), and one that shows the average number of accounts per-politician for each party. Which political party has more social media accounts? Which party has a higher per-politician average?

Note: there are several ways to accomplish this. You could use gather again and then group_by and summarise within politician and then within party, or you could use mutate to get counts for each politican and then average by party. Any other approach is also fine.

3. Use an inner join to combine the columns of the committees dataframe with the columns of congress, and create a plot showing the average number of committees that democrats and republicans belong to. Next create a plot showing the averages by gender (note: this second part should include members of other parties as well).

4. Create a bar plot showing the number of members that belong to the 10 largest congressional committees (i.e. committees with the largest number of members). The bars should be sorted based on committee sizes.

Note: Our standard for visualizations is that each plot should have axis labels, all labels must be readable, and we should easily be able to tell what your figure is showing. Failure to do this will result in point deductions.

5. Create a single bar plot that shows the average age of the committees with the 5 highest and lowest average ages. The bars should be sorted based on average committee ages. Which committees have the highest and lowest average ages?

6. Create a line graph showing the total number of politician births in each decade since the 1930’s, with separate lines for senate and house members (see the type column). The labels on your x-axis should look like “1930’s”, “1940’s”, and so on, and your legend should show values “Senator” and “Representative” (i.e. not rep and sen).

Note: The plotted lines may not be continuous if there were no births in some decades.

7. Create a bar chart showing the frequency of politician births by month and another bar chart showing politician births by weekday. The x-labels should be month names and weekday names, respectively, and appear in chronological order.

Note: you can use the lubridate package methods to get weekday and month names.

Thanks to Devin Cornell and Taylor Brown for helping to create these quizzes!