Using branded themes in hdatools

hdatools ships four branded ggplot2 themes — one per client brand — each pairing a theme_*() with matching scale_color_*()/scale_fill_*() color scales. This article builds the same chart in all four so you can see the brands side by side.

Let’s get some data. This is median household income for three Richmond-area localities, from the 2017-2021 5-year American Community Survey (variable B19013_001) — bundled here as a static table so this article builds without a Census API key or network access:

library(ggplot2)
library(scales)
library(hdatools)

rva_inc <- data.frame(
  NAME     = c("Chesterfield County", "Henrico County", "Richmond city"),
  estimate = c(88315, 76345, 54795)
)

Each plot below differs only in its scale_fill_*() and theme_*() call — everything else is identical.

First, an HDAdvisors-branded plot:

ggplot(rva_inc, aes(x = estimate, y = reorder(NAME, estimate), fill = NAME)) +
  geom_col() +
  scale_fill_hda() +
  scale_x_continuous(labels = label_dollar()) +
  theme_hda(flip_gridlines = TRUE) +
  add_zero_line("x") +
  labs(
    title = "Median household income",
    subtitle = "Richmond-area localities",
    caption = "**Source:** American Community Survey, 2017-2021 5-year estimates.<br>**Note:** Incomes adjusted to 2021 dollars."
  )

The same chart with HousingForward Virginia branding:

ggplot(rva_inc, aes(x = estimate, y = reorder(NAME, estimate), fill = NAME)) +
  geom_col() +
  scale_fill_hfv() +
  scale_x_continuous(labels = label_dollar()) +
  theme_hfv(flip_gridlines = TRUE) +
  add_zero_line("x") +
  labs(
    title = "Median household income",
    subtitle = "Richmond-area localities",
    caption = "**Source:** American Community Survey, 2017-2021 5-year estimates.<br>**Note:** Incomes adjusted to 2021 dollars."
  )

With PHA branding:

ggplot(rva_inc, aes(x = estimate, y = reorder(NAME, estimate), fill = NAME)) +
  geom_col() +
  scale_fill_pha() +
  scale_x_continuous(labels = label_dollar()) +
  theme_pha(flip_gridlines = TRUE) +
  add_zero_line("x") +
  labs(
    title = "Median household income",
    subtitle = "Richmond-area localities",
    caption = "**Source:** American Community Survey, 2017-2021 5-year estimates.<br>**Note:** Incomes adjusted to 2021 dollars."
  )

And with VHA branding:

ggplot(rva_inc, aes(x = estimate, y = reorder(NAME, estimate), fill = NAME)) +
  geom_col() +
  scale_fill_vha() +
  scale_x_continuous(labels = label_dollar()) +
  theme_vha(flip_gridlines = TRUE) +
  add_zero_line("x") +
  labs(
    title = "Median household income",
    subtitle = "Richmond-area localities",
    caption = "**Source:** American Community Survey, 2017-2021 5-year estimates.<br>**Note:** Incomes adjusted to 2021 dollars."
  )

Under ggplot2 >= 4.0, a bare theme_*() with no scale_*() call also brands the plot, via the theme-carried palette — the scale_fill_*() line above is optional when the brand’s default palette order is what you want:

ggplot(rva_inc, aes(x = estimate, y = reorder(NAME, estimate), fill = NAME)) +
  geom_col() +
  scale_x_continuous(labels = label_dollar()) +
  theme_hda(flip_gridlines = TRUE) +
  add_zero_line("x") +
  labs(
    title = "Median household income",
    subtitle = "No scale_fill_*() call — theme_hda() alone brands the fills"
  )