Take a sad plot, and make it better

Application exercise

Modified

September 17, 2026

Note

This application exercise is completed in class and submitted via a worksheet.

library(tidyverse)
library(scales)

Take a sad plot, and make it better

The American Association of University Professors (AAUP) is a nonprofit membership association of faculty and other academic professionals. This report by the AAUP shows trends in instructional staff employees between 1975 and 2011, and contains an image very similar to the one given below.

The data series has been extended through 2023.¹

Each row in this dataset represents a faculty type, and the columns are the years for which we have data. The values are percentage of hires of that type of faculty for each year.

staff <- read_csv("data/instructional-staff-extended.csv")
staff

# A tibble: 5 × 24
  faculty_type    `1975` `1989` `1993` `1995` `1999` `2001` `2003` `2005` `2007`
  <chr>            <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
1 Full-Time Tenu…   29     27.6   25     24.8   21.8   20.3   19.3   17.8   17.2
2 Full-Time Tenu…   16.1   11.4   10.2    9.6    8.9    9.2    8.8    8.2    8  
3 Full-Time Non-…   10.3   14.1   13.6   13.6   15.2   15.5   15     14.8   14.9
4 Part-Time Facu…   24     30.4   33.1   33.2   35.5   36     37     39.3   40.5
5 Graduate Stude…   20.5   16.5   18.1   18.8   18.7   19     20     19.9   19.5
# ℹ 14 more variables: `2009` <dbl>, `2011` <dbl>, `2012` <dbl>, `2013` <dbl>,
#   `2014` <dbl>, `2015` <dbl>, `2016` <dbl>, `2017` <dbl>, `2018` <dbl>,
#   `2019` <dbl>, `2020` <dbl>, `2021` <dbl>, `2022` <dbl>, `2023` <dbl>

Let’s make it better

Colleges and universities have come to rely more heavily on non-tenure track faculty members over time. Prior to the early 2010s, this was driven heavily by an increase in part-time faculty (e.g. contingent faculty, adjuncts). More recently, there has been a shift towards full-time non-tenure track faculty (e.g. lecturers, instructors, teaching professors). The original plot does not make it easy to see these trends.

Your turn: Sketch a chart that highlights the decline in tenure-track faculty.

What type of geom would you use?
Scales? Guides?
Labels?

Include sufficient level of detail to communicate your design choices for implementation.

Your turn: Swap with a peer and critique their design choices. Apply at least two of Cairo’s qualities of great visualizations.

Truthful
Functional
Beautiful
Insightful
Enlightening

Your turn: Sketch a revised version of your chart based on the feedback you received. Have you changed the geom(s)? Modified your scales/guides? Added improved labels or colors?

Additionally, define the chart’s core grammar of graphics. What are the variables and aesthetic mappings? What geoms would you use? What scales and guides would you include?

Your turn: Finally, implement your design in R using {ggplot2}. Pay careful attention to any data tidying/wrangling necessary to implement your design.

Data set structure

Remember you can only map a single column to an aesthetic channel for a given geom. So your data must be structured such that each variable is in its own column. This is often referred to as tidy data.

If the source data is not tidy, then reshape it before creating your chart.

Tip

{forcats} contains many functions for defining and adjusting the order of levels for factor variables. Factors are often used to enforce specific ordering of categorical variables in charts.

Tip

When you render the document, your plot images are automatically saved as PNG files in the sad-plot_files/figure-html directory. You can use these images to post your chart to the discussion thread, or use the ggsave() function to directly save your plot as an image file. For example,

ggsave(
  filename = "images/tt-faculty.png",
  plot = last_plot(),
  width = 8, height = 6, bg = "white"
)

saves the last generated plot to a file named tt-faculty.png in the images directory. It has a defined height and width (in “inches”) with a white background.

# add code here

Acknowledgments

Exercise derived from Data Science in a Box and licensed under CC BY-SA 4.0.

Footnotes

Data sources: IPEDS and Digest of Education Statistics. Downloaded February 10, 2025.↩︎