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A choropleth tells readers where values are high or low, but not how much the area they are looking at differs from the rest. maplore adds components to mapgl maps that answer that as readers pan and zoom.

This page builds a map of Argentina’s projected population growth, one component at a time. Every map here is live: pan, zoom and hover over it.

library(mapgl)
library(maplore)

The data

ar_departments comes with maplore: the 528 Argentine departments with their estimated population in 2022 and 2035 and the projected growth between both years, in percent.

head(sf::st_drop_geometry(ar_departments))
#>      id department                        province pop_2022 pop_2035 growth
#> 1 02007   Comuna 1 Ciudad Autónoma de Buenos Aires   250490   251915   0.57
#> 2 02014   Comuna 2 Ciudad Autónoma de Buenos Aires   154123   142387  -7.61
#> 3 02021   Comuna 3 Ciudad Autónoma de Buenos Aires   190296   170489 -10.41
#> 4 02028   Comuna 4 Ciudad Autónoma de Buenos Aires   244077   229894  -5.81
#> 5 02035   Comuna 5 Ciudad Autónoma de Buenos Aires   189214   174772  -7.63
#> 6 02042   Comuna 6 Ciudad Autónoma de Buenos Aires   186039   170806  -8.19

A summary of what is in view

Start with a regular mapgl map: a fill layer colored by growth. Then add add_view_summary() with the layer’s ID and the column to summarise.

colors <- interpolate(
  column = "growth",
  values = c(-10, 0, 10),
  stops = c("#b2182b", "#f7f7f7", "#2166ac")
)

map <- maplibre(style = carto_style("positron"), center = c(-64, -38.5), zoom = 3.4) |>
  add_fill_layer(
    id = "departments",
    source = ar_departments,
    fill_color = colors,
    fill_opacity = 0.85
  ) |>
  add_view_summary(
    layer_id = "departments",
    column = "growth",
    label = "Population growth 2022-2035",
    name_column = "department",
    weight = "pop_2022",
    weight_label = "population",
    unit = "departments",
    suffix = "%"
  )

Zoom into Buenos Aires: the panel shows how many departments are in view, their average growth weighted by population, how it compares with the whole country, the highest and lowest departments, and a histogram of the values in view over all values. The histogram uses the map’s colors, so it works as a legend too:

• hover over a bar to outline the departments in that range;
• click on the highest or lowest name to go there.

More components

All the components can be used together. Add a ranking of the departments in view, a tooltip that puts each value in context and a search box:

map |>
  add_view_ranking(
    layer_id = "departments",
    column = "growth",
    name_column = "department",
    label = "Population growth",
    unit = "departments",
    suffix = "%"
  ) |>
  add_context_tooltip(
    layer_id = "departments",
    column = "growth",
    name_column = "department",
    label = "Population growth",
    weight = "pop_2022",
    unit = "departments",
    suffix = "%"
  ) |>
  add_feature_search(
    layer_id = "departments",
    search_column = "department",
    detail_column = "province"
  )

In other languages

Numbers are formatted for any locale, and every text can be changed. The package includes English and Spanish texts:

add_view_summary(
  ...,
  locale = "es-AR",               # 1.234,5 instead of 1,234.5
  labels = context_labels("es")   # Spanish texts
)

context_labels("en", title = "Visible now")  # change any text

Where it works

Everything runs in the browser. The components work in any place where a mapgl map works: the RStudio and Positron viewers, HTML files saved with htmlwidgets::saveWidget(), R Markdown and Quarto documents, and Quarto dashboards, with no Shiny server.

Next, see the components in detail.