Load packages

require(tidyverse)
require(ggplot2)
require(sf)
require(rworldmap)
require(ggthemes)
require(viridis)
require(plotly)

Import Dataset

This data set was published by the World Happiness Report and downloaded from kaggle. It uses information from the Gallup World Survey and bases scores off several different factors and the degree to which they contribute to the country’s happiness.

happiness <- read_csv("2022happinessReport.csv")

Now I convert my data to include Country codes.

world_sf <- st_as_sf(getMap(resolution = "low")) %>% 
  left_join(happiness, by = c("GEOUNIT"="Country"))

Plot Data

First I draw the world map on which to include my data. Then I add coloring by the happiness score. I also created a text field to be able to have a tooltip with the happiness score and country’s ranking.

crs_robin <- "+proj=robin +lat_0=0 +lon_0=0 +x0=0 +y0=0"

h_wm <- ggplot()+
  geom_sf(data=world_sf,
          mapping = aes(fill=`Happiness score`,
                        text=paste("Happiness Ranking:",RANK,"<br>Country:",
                                  GEOUNIT,"<br>Happiness Score:",`Happiness score`)),
          col="white", size =.1)

Then I adjust the themes and color schemes

h_wm <- h_wm +
  theme_classic(base_size = 12,base_family = "sans")+
  coord_sf(crs=crs_robin) +
  scale_fill_viridis() +
  theme(plot.title = element_text(hjust=.5),legend.position = "none")

Finally, I add a title and an interactive element

h_wm <- h_wm + ggtitle("2022 Happiness Score")


# add tooltips
h_wm <- ggplotly(h_wm,tooltip= "text")

The tooltips show where the country ranks as far as it’s happiness score, its name, and the happiness score itself.