The fmt_bins() function

Use the countrypops dataset to create a gt table. Before even getting to the gt() call, we use the cut() function in conjunction with the scales::breaks_log() function to create some highly customized bins. Consequently each country’s population in the 2021 year is assigned to a bin. These bins have a characteristic type of formatting that can be used as input to fmt_bins(), and using that formatting function allows us to customize the presentation of those ranges. For instance, here we are formatting the left and right values of the ranges with the fmt_integer() function (using formula syntax).

countrypops |>
  dplyr::filter(year == 2021) |>
  dplyr::select(country_code_2, population) |>
  dplyr::mutate(population_class = cut(
    population,
    breaks = scales::breaks_log(n = 20)(population)
    )
  ) |>
  dplyr::group_by(population_class) |>
  dplyr::summarize(
    count = dplyr::n(),
    countries = paste0(country_code_2, collapse = ",")
  ) |>
  dplyr::arrange(desc(population_class)) |>
  gt() |>
  fmt_flag(columns = countries) |>
  fmt_bins(
    columns = population_class,
    fmt = ~ fmt_integer(., suffixing = TRUE)
  ) |>
  cols_label(
    population_class = "Population Range",
    count = "",
    countries = "Countries"
  ) |>
  cols_width(
    population_class ~ px(150),
    count ~ px(50)
  ) |>
  tab_style(
    style = cell_text(style = "italic"),
    locations = cells_body(columns = count)
  )

Population Range		Countries
1B–2B	2
300M–500M	1
200M–300M	4
100M–200M	7
50M–100M	15
30M–50M	20
20M–30M	11
10M–20M	31
5M–10M	32
3M–5M	12
2M–3M	14
1M–2M	10
500K–1M	12
300K–500K	6
200K–300K	4
100K–200K	10
50K–100K	9
30K–50K	12
10K–20K	3