geom_pop()

geom_pop() draws icon-based population grids. Add an icon column to your data, then map icon and color in aes(). Do not map x or y – layout is computed internally.

Basic usage


df_raw <- data.frame(
  activity = c("Running", "Cycling", "Swimming", "Walking"),
  n        = c(28, 22, 18, 32)
)

df_plot <- process_data(
  data        = df_raw,
  group_var   = activity,
  sum_var     = n,
  sample_size = 30
) %>%
  mutate(icon = case_when(
    type == "Running"  ~ "person-running",
    type == "Cycling"  ~ "person-biking",
    type == "Swimming" ~ "person-swimming",
    type == "Walking"  ~ "person-walking"
  ))

ggplot() +
  geom_pop(
    data = df_plot,
    aes(icon = icon, color = type),
    size = 3, dpi = 72
  ) +
  scale_color_manual(values = c(
    Running  = "#e76f51",
    Cycling  = "#2a9d8f",
    Swimming = "#457b9d",
    Walking  = "#e9c46a"
  )) +
  theme_pop() +
  scale_legend_icon(size = 7) +
  labs(title = "Preferred physical activity", color = NULL)

Verify icon names with fa_icons(query = "biking") and fa_icons(query = "swimming") as Font Awesome naming can vary slightly by version.

Faceted chart

Use high_group_var for the facet panel variable and group_var for the color/icon variable within each panel. Icons from different groups scatter and mix across each panel by default (arrange = FALSE).

df_raw <- data.frame(
  region    = c("North", "North", "North",
                "South", "South", "South",
                "East",  "East",  "East",
                "West",  "West",  "West"),
  work_type = c("Office", "Remote", "Hybrid",
                "Office", "Remote", "Freelance",
                "Remote", "Hybrid", "Freelance",
                "Office", "Hybrid", "Freelance"),
  n         = c(40, 35, 25,
                20, 45, 35,
                50, 30, 20,
                30, 40, 30)
)

df_plot <- process_data(
  data           = df_raw,
  group_var      = work_type,
  sum_var        = n,
  sample_size    = 10,
  high_group_var = "region"
) %>%
  mutate(icon = case_when(
    type == "Office"    ~ "building",
    type == "Remote"    ~ "house",
    type == "Hybrid"    ~ "shuffle",
    type == "Freelance" ~ "mug-hot"
  ))

ggplot() +
  geom_pop(
    data = df_plot,
    aes(icon = icon, color = type),
    size = 2, dpi = 72, facet = group
  ) +
  facet_wrap(~ group, ncol = 2) +
  scale_color_manual(values = c(
    Office    = "#2a9d8f",
    Remote    = "#e76f51",
    Hybrid    = "#457b9d",
    Freelance = "#e9c46a"
  )) +
  theme_pop() +
  labs(title = "Work type by region", color = NULL)

Clustered layout

arrange = TRUE groups icons by category instead of scattering them.

df_browser <- data.frame(
  browser = c("Chrome", "Firefox", "Safari"),
  n       = c(45, 20, 25)
)

df_browser_plot <- process_data(
  data        = df_browser,
  group_var   = browser,
  sum_var     = n,
  sample_size = 20
) %>%
  mutate(icon = case_when(
    type == "Chrome"  ~ "chrome",
    type == "Firefox" ~ "firefox",
    type == "Safari"  ~ "safari",
    type == "Edge"    ~ "edge"
  ))

ggplot() +
  geom_pop(
    data    = df_browser_plot,
    aes(icon = icon, color = type),
    size    = 2, dpi = 72, arrange = TRUE
  ) +
  scale_color_manual(values = c(
    Chrome  = "#4285F4",
    Firefox = "#FF7139",
    Safari  = "#006CFF",
    Edge    = "#0078D7"
  )) +
  theme_pop() +
  theme(legend.position = "bottom") +
  labs(title = "Browser market share", color = NULL)

Key parameters

Parameter	Default	Description
`size`	`2`	Icon size
`dpi`	`100`	Render resolution
`arrange`	`FALSE`	Cluster icons by group
`legend_icons`	`FALSE`	Show icons in legend
`seed`	`NULL`	Fix random layout
`facet`	`NULL`	Column driving facet panels