Data Wrangling: Code Style

Day 09

Prof Amanda Luby

Carleton College
Stat 220 - Winter 2026

Which is easier to read?

Option A
Option B

group_by(colleges,region) %>% mutate(z_cost=(cost - mean(cost, na.rm=TRUE)) / sd(cost,na.rm = TRUE)) %>% ungroup()

# A tibble: 187 × 14
   unitid school  type  city  state region admission_rate   act undergrads  cost
    <dbl> <chr>   <chr> <chr> <chr> <chr>           <dbl> <dbl>      <dbl> <dbl>
 1 228343 Southw… priv… Geor… TX    South…          0.490    26       1507 55886
 2 177719 Barnes… priv… Sain… MO    Plains         NA        NA        569    NA
 3 367884 Hodges… priv… Fort… FL    South…          0.612    NA        832 27425
 4 149781 Wheato… priv… Whea… IL    Great…          0.848    29       2358 49214
 5 135364 Luther… priv… Lith… GA    South…          0.5      NA        235    NA
 6 212601 Gannon… priv… Erie  PA    Mid E…          0.755    23       2866 44896
 7 133979 Florid… priv… Miam… FL    South…          0.400    NA       1049 27460
 8 117140 Univer… priv… La V… CA    Far W…          0.548    22       4516 58014
 9 152567 Trine … priv… Ango… IN    Great…          0.816    25       2120 46440
10 237057 Whitma… priv… Wall… WA    Far W…          0.559    31       1545 68082
# ℹ 177 more rows
# ℹ 4 more variables: grad_rate <dbl>, fy_retention <dbl>, fedloan <dbl>,
#   z_cost <dbl>

colleges %>%
  group_by(region) %>%
  mutate(z_cost = (cost - mean(cost, na.rm = TRUE)) / sd(cost, na.rm = TRUE)) %>%
  ungroup()

# A tibble: 187 × 14
   unitid school  type  city  state region admission_rate   act undergrads  cost
    <dbl> <chr>   <chr> <chr> <chr> <chr>           <dbl> <dbl>      <dbl> <dbl>
 1 228343 Southw… priv… Geor… TX    South…          0.490    26       1507 55886
 2 177719 Barnes… priv… Sain… MO    Plains         NA        NA        569    NA
 3 367884 Hodges… priv… Fort… FL    South…          0.612    NA        832 27425
 4 149781 Wheato… priv… Whea… IL    Great…          0.848    29       2358 49214
 5 135364 Luther… priv… Lith… GA    South…          0.5      NA        235    NA
 6 212601 Gannon… priv… Erie  PA    Mid E…          0.755    23       2866 44896
 7 133979 Florid… priv… Miam… FL    South…          0.400    NA       1049 27460
 8 117140 Univer… priv… La V… CA    Far W…          0.548    22       4516 58014
 9 152567 Trine … priv… Ango… IN    Great…          0.816    25       2120 46440
10 237057 Whitma… priv… Wall… WA    Far W…          0.559    31       1545 68082
# ℹ 177 more rows
# ℹ 4 more variables: grad_rate <dbl>, fy_retention <dbl>, fedloan <dbl>,
#   z_cost <dbl>

Which is easier to read?

Option A
Option B

palmerpenguins::penguins |>
  filter(species == "Adelie") |>
  ggplot(aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point() + 
  scale_color_viridis_d(option = "magma",end = .75) + 
  theme_bw(base_family = "Times") + 
  theme(legend.position = "none",
        panel.grid.minor = element_blank(),
        panel.grid.major.x = element_blank(),
        axis.title.x = element_text(color = "darkred"))

palmerpenguins::penguins |> filter(species=="Adelie") |> ggplot(aes(x =bill_length_mm, y= bill_depth_mm)) + geom_point() + scale_color_viridis_d(option = "magma",end = .75) + 
  theme_bw(base_family = "Times") + 
  theme(legend.position = "none", panel.grid.minor=element_blank(), panel.grid.major.x = element_blank(),
        axis.title.x = element_text(color="darkred"))

https://style.tidyverse.org

Example: Pipes and whitespace

|> should always have a space before it, and should usually be followed by a new line. After the first step, each line should be indented by two spaces.

Good:

iris |>
  summarize(across(where(is.numeric), mean), .by = Species) |>
  pivot_longer(!Species, names_to = "measure", values_to = "value") |>
  arrange(value)

Bad:

iris|> summarize(across(where(is.numeric), mean), .by = Species) |>
pivot_longer(!Species, names_to = "measure", values_to = "value")|>
arrange(value)

Example: long lines

If the arguments to a function don’t all fit on one line, put each argument on its own line and indent:

Good:

iris |>
  summarise(
    Sepal.Length = mean(Sepal.Length, na.rm = TRUE),
    Sepal.Width = mean(Sepal.Width, na.rm = TRUE),
    .by = Species
  )

Bad:

iris |>
  summarise(Sepal.Length = mean(Sepal.Length, na.rm = TRUE), Sepal.Width = mean(Sepal.Width, na.rm = TRUE), .by = Species)

ggplot2 whitespace and indenting

+ should always have a space before it, and should be followed by a new line. After the first step, each line should be indented by two spaces.

If you are creating a ggplot off of a dplyr pipeline, there should only be one level of indentation.

Good:

iris |>
  filter(Species == "setosa") |>
  ggplot(aes(x = Sepal.Width, y = Sepal.Length)) +
  geom_point()

Bad:

iris |>
  filter(Species == "setosa") |>
  ggplot(aes(x = Sepal.Width, y = Sepal.Length)) +
    geom_point()

Bad:

iris |>
  filter(Species == "setosa") |>
  ggplot(aes(x = Sepal.Width, y = Sepal.Length)) + geom_point()

ggplot2 long lines

If the arguments to a ggplot2 layer don’t all fit on one line, put each argument on its own line and indent:

Good:

iris |>
  ggplot(aes(x = Sepal.Width, y = Sepal.Length, color = Species)) +
  geom_point() +
  labs(
    x = "Sepal width, in cm",
    y = "Sepal length, in cm",
    title = "Sepal length vs. width of irises"
  )

Bad:

iris |>
  ggplot(aes(x = Sepal.Width, y = Sepal.Length, color = Species)) +
  geom_point() +
  labs(x = "Sepal width, in cm", y = "Sepal length, in cm", title = "Sepal length vs. width of irises")

Code style summary

All code style guides are opinionated and subjective
Using consistent style makes it easier for collaborators (including future you!) to read and understand your code
Try to follow the tidyverse style guide in this class

A shortcut

In RStudio,

Highlight the code that you want to reformat
Go to “code –> reformat code”
Marvel in wonder

Try it

Reformat your code from an activity this week according to the tidyverse style guide