Gapminder analysis
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Libraries

Let’s load some libraries needed

# Libraries
library(tidyverse)   # includes ggplot2
library(hrbrthemes)  # better chart appearance
library(viridis)     # better color palette
library(plotly)      # interactive charts
#library(gridExtra)

# The dataset is provided in the gapminder library
library(gapminder)

Data wrangling

Let’s keep data for 2007 only

data <- gapminder %>% filter(year=="2007") %>% select(-year)

Let’s build a chart

Build the chart with ggplot2, make it interactive with plotly.

# Interactive version
p <- data %>%
  mutate(gdpPercap=round(gdpPercap,0)) %>%
  mutate(pop=round(pop/1000000,2)) %>%
  mutate(lifeExp=round(lifeExp,1)) %>%
  arrange(desc(pop)) %>%
  mutate(country = factor(country, country)) %>%
  mutate(text = paste("Country: ", country, "\nPopulation (M): ", pop, "\nLife Expectancy: ", lifeExp, "\nGdp per capita: ", gdpPercap, sep="")) %>%
  ggplot( aes(x=gdpPercap, y=lifeExp, size = pop, color = continent, text=text)) +
    geom_point(alpha=0.7) +
    scale_size(range = c(1.4, 19), name="Population (M)") +
    scale_color_viridis(discrete=TRUE, guide=FALSE) +
    theme_ipsum() +
    theme(legend.position="none")

ggplotly(p, tooltip="text")
 



A work by Yan Holtz