Leaflet Municipios

This document provides examples of how to create interactive choropleth maps of Mexican municipios using the mxmaps and leaflet packages. The examples show how to visualize data for all municipios, as well as how to create focused maps of specific areas, such as cities or metropolitan areas, by subsetting the data.

library(mxmaps)
library(leaflet) # for colorNumeric

df_mxmunicipio_2020$value <- df_mxmunicipio_2020$indigenous_language /
  df_mxmunicipio_2020$pop
#Viridis color scheme
magma <- c("#000004FF", "#1D1146FF", "#50127CFF", "#822681FF", "#B63779FF", 
           "#E65163FF", "#FB8761FF", "#FEC387FF", "#FCFDBFFF")
pal <- colorNumeric(magma, domain = df_mxmunicipio_2020$value)
mxmunicipio_leaflet(df_mxmunicipio_2020,
                    pal,
                    ~ pal(value),
                    ~ sprintf("State: %s<br/>Municipio : %s<br/>Percent Indigenous: %s%%",
                              state_name, municipio_name, round(value * 100, 1))) %>%
  addLegend(position = "bottomright", 
            pal = pal, 
            values = df_mxmunicipio_2020$value,
            title = "Percent<br>Indigenous<br>Speaking",
            labFormat = labelFormat(suffix = "%",
                                    transform = function(x) {100 * x})) %>%
  addProviderTiles("CartoDB.Positron")

City maps

You can also subset the data to only show certain municipios

library("dplyr")
library("geojsonio")
library("jsonlite")
library("sf")
library("RColorBrewer")
library("leaflet")

df <- df_mxmunicipio_2020 %>%
  as.data.frame() %>%
  filter(metro_area %in% c("Valle de México", "Toluca", "Puebla-Tlaxcala"))

df$value <- df$indigenous /df$pop

Reds <- c("white", brewer.pal(4, "RdYlBu"))
pal <- colorNumeric(Reds, domain = df$value)
mxmunicipio_leaflet(df,
                    pal,
                    ~ pal(value),
                    opacity = 0.8,
                    fillOpacity = 0.8,
                    zoom = df$region,
                    popup = sprintf("State: %s<br/>Municipio : %s<br/>Value: %s%%",
                                    df$state_name,
                                    df$municipio_name,
                                    round(df$value * 100, 1))) %>%
  addLegend(position = "bottomright", pal = pal,
            values = df$value) %>%
  addProviderTiles("CartoDB.Positron") 

or you can subset the topoJSON directly

# Convert the topoJSON to spatial object
tmpdir <- tempdir()
# have to use RJSONIO or else the topojson isn't valid
write(RJSONIO::toJSON(mxmunicipio.topoJSON), file.path(tmpdir, "mun.topojson"))
muns <- topojson_read(file.path(tmpdir, "mun.topojson"))

# municipios that make up Monterrey
monterrey <- muns[muns$id %in% 
                    df_mxmunicipio_2020$region[df_mxmunicipio_2020$metro_area == "Monterrey"], ]
# Convert to SpatialDataFrame
monterrey <- as_Spatial(monterrey)
# made-up data
monterrey@data$rand <- 1:nrow(monterrey@data)

# Create a continuous palette function
pal <- colorNumeric(
  palette = "Blues",
  domain = monterrey@data$rand
)

leaflet(monterrey) %>%
  addPolygons(stroke = FALSE, smoothFactor = 0.2, fillOpacity = 1,
              color = ~pal(monterrey@data$rand)
  )%>%
  addProviderTiles("CartoDB.Positron")