Highcharts

library(usahex) 
library(tidyverse)
library(highcharter) 

library(rvest) 
library(jsonlite) 
library(rjson)

You can create responsive and interactive plots using Highcharts. I will be showing how to create a hex map highchart object using usahex and highchater.

Get Data

Data to Dispaly

Population Change for the US from 2010 to 2020, pulled from Wikipedia using this code

other_data <- read.csv("https://raw.githubusercontent.com/MarEichler/usahex/refs/heads/main/data-raw/us_population_change_2010_to_2020.csv")

Map Coordinates

highcharter only works with geojson/json so it’a easies to import the geojson file from github

link <- "https://raw.githubusercontent.com/MarEichler/usahex/refs/heads/main/data-raw/geojson/usa56.geojson"
hex_map <- fromJSON(file = link)
# need jsonlite AND rjson package for this code to work 

Highchart Hex Map

Prep for Map

Prep the display data.

values_to_plot <-other_data |> 
  # create new variables 
  mutate(
    category = cut(
      perc,
      breaks = c( -20, -10 , -5, 5, 10, 20),
      labels = c("less than -10%", "-10% to -5%", "-5% to 5%", "5% to 10%", "more than 10%"),
    ),
    # recreate perc_label so only 1 digit
    perc_label = scales::comma(perc, accuracy = 0.1, suffix = "%"),
    #  variable did population inc/decrease
    inc_dec = case_when(
      n == 0 ~ "did not change",
      n > 0 ~ "increased",
      n < 0 ~ "decreased"
    )
  ) |> 
  # join with geo abbr & info 
  right_join(
    sf::st_drop_geometry(usahex::get_coordinates("usa56")), 
    by = "name"
  ) |> 
  # create and style the tool tip
  mutate(
    tooltip = paste0(
      "<b>", name, "</b><br>", 
      "Population <b>",inc_dec, "</b> by ", scales::comma(abs(n)), 
      " people (", 
       scales::comma(abs(perc), accuracy = 0.1, suffix = "%"), 
      ") from 2010 to 2020"
    )
  )

Prep for highchart object

map_theme <- hc_theme(
  chart = list(style = list(fontFamily = "Arial", color = "#666666")),
  title = list(
    style = list(
      fontFamily = "Arial",
      fontWeight = "bold",
      color = "black",
      fontSize   = "30px"
      )
    )
  )

color_scale <- c("#D01C8B", "#F1B6DA", "#F7F7F7", "#B8E186","#4DAC26")

min_map <- min(values_to_plot$perc, na.rm = TRUE)
max_map <- max(values_to_plot$perc, na.rm = TRUE)

Hex Map: Continous Variable

highchart() |> 
  hc_add_series_map(
    map = hex_map,
    df = values_to_plot, 
    joinBy = "name",
    value = "perc", 
    dataLabels = list(
      enabled = TRUE,
      useHTML = TRUE,
      formatter = JS(
      "function() {return '<div style=\"text-align:center;\">' +
      '<span style=\"font-weight:bold;\">' + this.point.abbr_gpo + 
      '</span><br>' +
      '<span style=\"font-weight:normal;font-size: 0.85em;\">' + 
      this.point.perc_label + '</span>' +
      '</div>';}"
      )
    ),
    nullColor = "#e8e8e8",
    accessibility = list(
      point = list(
        valueDescriptionFormat = 
          "geography: {point.name}, value of interest: {point.pop_change:.1f}"
      )
    )
  ) |>
  # style hc object
  hc_colorAxis(
    min = min_map,
    max =  max_map,
    stops = color_stops(5, color_scale),
    labels = list(format = "{value}%")
    ) |>
  hc_legend(
    align = "right",
    layout = "vertical",
    verticalAlign = "bottom"
  ) |>
  # add title and tool tips
  hc_title(text = "Population Change, 2010 to 2020") |>
  hc_tooltip(
    formatter = JS("function(){return(this.point.tooltip)}"),
    outside = TRUE
  ) |>
  # add theme
  hc_add_theme(map_theme)

Hex Map: Discrete Variable

Highcharter does not work automatically with discrete variables in the same way as ggplot. In order to plot discrete variables on a highchater hex map, you need to section off the data and add each category individually.

add_cat_to_hex_map <- function(hc, df, cat, color){

hc |> 
  hc_add_series(
    name = cat, 
    data = filter(df, category == cat), 
    dataLabels = list(
      enabled = TRUE,
      useHTML = TRUE,
      formatter = JS("function() {return '<div style=\"text-align:center;\">' +
        '<span style=\"font-weight:bold;\">' + this.point.abbr_gpo + 
        '</span><br>' +
        '<span style=\"font-weight:normal;font-size: 0.85em;\">' + 
        this.point.perc_label + '</span>' +
        '</div>';}")
    ),
    color = color, 
    accessibility = list(
      point = list(
        valueDescriptionFormat = "geography: {point.name}, value of interest: {point.pop_change:.1f}"
      )
    )
  )
  
}

highchart(type = "map") |> 
  hc_plotOptions(map = list(
    allAreas = FALSE,
    joinBy = c("name"),
    mapData = hex_map
  )) |> 
  add_cat_to_hex_map(values_to_plot, "less than -10%", color = color_scale[1]) |> 
  add_cat_to_hex_map(values_to_plot, "-10% to 5%"    , color = color_scale[2]) |> 
  add_cat_to_hex_map(values_to_plot, "-5% to 5%"     , color = color_scale[3]) |> 
  add_cat_to_hex_map(values_to_plot, "5% to 10%"     , color = color_scale[4]) |> 
  add_cat_to_hex_map(values_to_plot, "more than 10%" , color = color_scale[5]) |> 
  hc_legend(
    align = "right",
    layout = "horizontal",
    verticalAlign = "bottom"
  ) |> 
  # add title and tool tips 
  hc_title(text = "Population Change, 2010 to 2020") |> 
  hc_tooltip(
    formatter = JS("function(){return(this.point.tooltip)}"),
    outside = TRUE
  ) |> 
  # add theme
  hc_add_theme(map_theme)