AE 03: Tidying Stat Sci majors

Application exercise
Answers
Important

These are suggested answers. This document should be used as reference only, it’s not designed to be an exhaustive key.

Data

The data come from the Office of the University Registrar.

library(tidyverse)

majors <- read_csv("data/majors.csv")

statsci_majors <- majors |>
  filter(
    department == "Statistical Science",
    academic_plan != "Minor"
  )

And let’s take a look at the data.

statsci_majors
# A tibble: 4 × 17
  department      academic_plan `2026` `2025` `2024` `2023` `2022` `2021` `2020`
  <chr>           <chr>          <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
1 Statistical Sc… BS                49     45     39     54     32     35     27
2 Statistical Sc… BS2               28     23     20     27     16     17     17
3 Statistical Sc… BA                 2     NA      1      2     NA     NA      1
4 Statistical Sc… BA2                1     NA     NA     NA     NA      2      1
# ℹ 8 more variables: `2019` <dbl>, `2018` <dbl>, `2017` <dbl>, `2016` <dbl>,
#   `2015` <dbl>, `2014` <dbl>, `2013` <dbl>, `2012` <dbl>

Pivoting

  • Demo: Pivot the statsci data frame longer such that:

    • Each row represents a degree type / year combination
    • year and number of graduates for that year are columns in the data frame
    • The resulting year column is numeric
statsci_majors |>
  pivot_longer(
    cols = !c(department, academic_plan),
    names_to = "year",
    values_to = "n",
    names_transform = as.numeric
  )
# A tibble: 60 × 4
   department          academic_plan  year     n
   <chr>               <chr>         <dbl> <dbl>
 1 Statistical Science BS             2026    49
 2 Statistical Science BS             2025    45
 3 Statistical Science BS             2024    39
 4 Statistical Science BS             2023    54
 5 Statistical Science BS             2022    32
 6 Statistical Science BS             2021    35
 7 Statistical Science BS             2020    27
 8 Statistical Science BS             2019    26
 9 Statistical Science BS             2018    21
10 Statistical Science BS             2017    24
# ℹ 50 more rows
  • Your Turn: Now, repeat your code from above, but this time save the result to a new variable name.
statsci_majors_longer <- statsci_majors |>
  pivot_longer(
    cols = !c(department, academic_plan),
    names_to = "year",
    names_transform = as.numeric,
    values_to = "n"
  )

Plotting

  • Your turn: Now we will start making our plot, but let’s not get too fancy right away. Just get the geoms right for now and use default colors for different academic plans.
statsci_majors_longer |>
  ggplot(aes(x = year, y = n, color = academic_plan)) +
  geom_point() +
  geom_line()
Warning: Removed 12 rows containing missing values or values outside the scale range
(`geom_point()`).

  • Question: Why was the pivot necessary in order to create this plot?

Add your response here!

  • Question: What aspects of the plot need to be updated still?

Add your response here.

  • Demo: Update statsci_majors_longer to fix the discontinuities.
statsci_majors_longer <- statsci_majors_longer |>
  mutate(n = if_else(is.na(n), 0, n))
  • Demo: Update x-axis scale such that the years displayed go from 2011 to 2025 in increments of 2 years. Do this by adding on to your pipeline from earlier.
statsci_majors_longer |>
  ggplot(aes(x = year, y = n, color = academic_plan)) +
  geom_point() +
  geom_line() +
  scale_x_continuous(breaks = seq(2011, 2025, 2))

  • Demo: Update line colors using the following level / color assignments. Once again, do this by adding on to your pipeline from earlier.

    • “BS” = “cadetblue4”

    • “BS2” = “cadetblue3”

    • “BA” = “lightgoldenrod4”

    • “BA2” = “lightgoldenrod3”

statsci_majors_longer |>
  ggplot(aes(x = year, y = n, color = academic_plan)) +
  geom_point() +
  geom_line() +
  scale_x_continuous(breaks = seq(2011, 2025, 2)) +
  scale_color_manual(
    values = c(
      "BS" = "cadetblue4",
      "BS2" = "cadetblue3",
      "BA" = "lightgoldenrod4",
      "BA2" = "lightgoldenrod3"
    )
  )

  • Your turn: Update the plot labels (title, subtitle, x, y, and caption) and use theme_minimal(). Once again, do this by adding on to your pipeline from earlier.
statsci_majors_longer |>
  ggplot(aes(x = year, y = n, color = academic_plan)) +
  geom_point() +
  geom_line() +
  scale_x_continuous(breaks = seq(2011, 2025, 2)) +
  scale_color_manual(
    values = c(
      "BS" = "cadetblue4",
      "BS2" = "cadetblue3",
      "BA" = "lightgoldenrod4",
      "BA2" = "lightgoldenrod3"
    )
  ) +
  labs(
    x = "Graduation year",
    y = "Number of majors graduating",
    color = "Degree type",
    title = "Statistical Science majors over the years",
    subtitle = "Academic years 2012 - 2026",
    caption = "Source: Office of the University Registrar\nhttps://registrar.duke.edu/registration/enrollment-statistics"
  ) +
  theme_minimal()

  • Demo: Move the legend into the plot, make its background white, and its border gray.
statsci_majors_longer |>
  ggplot(aes(x = year, y = n, color = academic_plan)) +
  geom_point() +
  geom_line() +
  scale_x_continuous(breaks = seq(2011, 2025, 2)) +
  scale_color_manual(
    values = c(
      "BS" = "cadetblue4",
      "BS2" = "cadetblue3",
      "BA" = "lightgoldenrod4",
      "BA2" = "lightgoldenrod3"
    )
  ) +
  labs(
    x = "Graduation year",
    y = "Number of majors graduating",
    color = "Degree type",
    title = "Statistical Science majors over the years",
    subtitle = "Academic years 2012 - 2026",
    caption = "Source: Office of the University Registrar\nhttps://registrar.duke.edu/registration/enrollment-statistics"
  ) +
  theme_minimal() +
  theme(
    legend.position = "inside",
    legend.position.inside = c(0.1, 0.7),
    legend.background = element_rect(fill = "white", color = "grey")
  )

  • Demo: Finally, set fig-width: 8 and fig-height: 5 for your plot in the chunk options.
statsci_majors_longer |>
  ggplot(aes(x = year, y = n, color = academic_plan)) +
  geom_point() +
  geom_line() +
  scale_x_continuous(breaks = seq(2011, 2025, 2)) +
  scale_color_manual(
    values = c(
      "BS" = "cadetblue4",
      "BS2" = "cadetblue3",
      "BA" = "lightgoldenrod4",
      "BA2" = "lightgoldenrod3"
    )
  ) +
  labs(
    x = "Graduation year",
    y = "Number of majors graduating",
    color = "Degree type",
    title = "Statistical Science majors over the years",
    subtitle = "Academic years 2012 - 2026",
    caption = "Source: Office of the University Registrar\nhttps://registrar.duke.edu/registration/enrollment-statistics"
  ) +
  theme_minimal() +
  theme(
    legend.position = "inside",
    legend.position.inside = c(0.1, 0.7),
    legend.background = element_rect(fill = "white", color = "grey")
  )