Highcharter R Package Essentials for Easy Interactive Graphs

Prerequisites

# Load required R packages
library(tidyverse)
library(highcharter) 

# Set highcharter options
options(highcharter.theme = hc_theme_smpl(tooltip = list(valueDecimals = 2)))

Data preparation

Here, we’ll create world map colored according to the value of life expectancy at birth in 2015. The data is retrieved from the WHO (World Health Organozation) data base using the WHO R package.

# Retrieve life expectancy data for the year 2015
library("WHO")
library("dplyr")
life.exp <- get_data("WHOSIS_000001")             
life.exp <- life.exp %>%
  filter(year == 2015 & sex == "Both sexes") %>%
  select(country, value)  
life.exp

## # A tibble: 191 x 2
##   country                          value
##   <chr>                            <dbl>
## 1 Austria                           81.4
## 2 Benin                             60.7
## 3 Bahrain                           78.8
## 4 Bolivia (Plurinational State of)  71.2
## 5 Switzerland                       83  
## 6 Democratic Republic of the Congo  60.1
## # … with 185 more rows

# Load the world Map data
data(worldgeojson, package = "highcharter")

Create the choropleth map

hc <- highchart() %>%
  hc_add_series_map(
    worldgeojson, life.exp, value = "value", joinBy = c('name','country'),
    name = "LifeExpectancy"
    )  %>% 
  hc_colorAxis(stops = color_stops()) %>% 
  hc_title(text = "World Map") %>% 
  hc_subtitle(text = "Life Expectancy in 2015")

hc