# Choropleth visualisation

## Introduction

This vignette shows how polygon data included in `spatialrisk` can be used to display aggregated values. The emphasis is on reporting and visualisation after a spatial aggregation step.

Choropleth maps are useful for showing variation across administrative areas. They should not be interpreted as a substitute for fixed-radius concentration analysis on point-level data.

## Data

    library(spatialrisk)
    library(sf)
    library(dplyr)

    data(nl_gemeente)

The object `nl_gemeente` contains municipal geometries for the Netherlands as a simple feature object. For illustration, we create a small table with one value per municipality. In applied work, this table would typically contain observed or modelled values aggregated at municipality level.

    set.seed(1)
    municipality_values <- nl_gemeente |>
      st_drop_geometry() |>
      select(id, code, areaname) |>
      mutate(value = runif(n(), min = 0, max = 100))

## Join values to geometries

The values are joined back to the municipal geometries before plotting.

    map_data <- nl_gemeente |>
      left_join(municipality_values, by = c("id", "code", "areaname"))

## Choropleth map

The `choropleth()` function uses `tmap`. The `id` argument identifies the column used for polygon labels in interactive maps.

    choropleth(
      map_data,
      value = "value",
      id = "areaname",
      legend_title = "Value"
    )

## Relation to concentration analysis

A choropleth map represents values attached to predefined polygons. Fixed-radius concentration analysis answers a different question: what is the total value within a circle of a specified radius around a possible centre?

In insurance applications, both views can be useful. The fixed-radius calculation identifies local accumulation of exposure, while the choropleth map can be used to communicate summaries by municipality, province, or another reporting unit.

## Summary

This vignette demonstrated how to:

- use an included simple feature object;
- join aggregated values to polygon geometries;
- create a choropleth map for reporting.