Treemap Visualization

Author

G. Balasanov

Treemap Visualization

# Install packages

# install.packages("tidyverse")
# install.packages("dslabs")
# install.packages("treemap")

# Load libraries

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.2.1     ✔ readr     2.2.0
✔ forcats   1.0.1     ✔ stringr   1.6.0
✔ ggplot2   4.0.3     ✔ tibble    3.3.1
✔ lubridate 1.9.5     ✔ tidyr     1.3.2
✔ purrr     1.2.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(dslabs)
library(treemap)

data(gapminder)

# Groupping and computing
# Also filtering to include only the year 2007
continent_pop <- gapminder %>%
  filter(year == 2007) %>%
  group_by(continent) %>%
  summarise(total_population = sum(population)) %>%
  as.data.frame() # Just looking at this as a data frame. It's convenient this way.

continent_pop

  continent total_population
1    Africa        948156290
2  Americas        911419886
3      Asia       3911346015
4    Europe        730984863
5   Oceania         34130212

# Treemap visualization 
# Area of each rectangle is total population

library(RColorBrewer)

treemap(continent_pop,
        index = "continent",
        vSize = "total_population",
        vColor="total_population", 
        palette="RdYlBu",  #Use RColorBrewer palette
        title = "World Population by Continent, 2007",
        title.legend = "Avg Arrival Delay (min)" )   # legend label