Task 1: Reflection

I used this visualization challenge as a way to explore the relationship between population and GDP per capita. I designed a graph which displays population and GDP per capita. I added tooltips that show you which country you’re hovering over, its exact population and GDP per capita. This allows one to compare countries at a glance, but also with pinpoint precision, if it’s necessary. Overall, this dataset provided an easy basis from which I could create a useful and understandable interactive visualization.

Task 2: Interactive plots

library(tidyverse)
library(plotly)

# Load data here
library(gapminder)

Do the following:

  1. Make a plot. Any kind of plot will do (though it might be easiest to work with geom_point()).
gapminder_2002 <- filter(gapminder,
                         year == 2002)
plot_one <- ggplot(
  data = gapminder_2002,
  mapping = aes(x = pop, y = gdpPercap,
                color = continent)) +
  geom_point(aes(text = paste(country, 
                              "<br>Population:", pop, 
                              "<br>GDP per capita:", gdpPercap))) +
  scale_x_log10() +
  theme_minimal()
## Warning in geom_point(aes(text = paste(country, "<br>Population:", pop, :
## Ignoring unknown aesthetics: text
plot_one

  1. Make the plot interactive with ggplotly().

  2. Make sure the hovering tooltip is more informative than the default.

interactive_plot_one <- ggplotly(
  plot_one, tooltip = "text"
)
interactive_plot_one

Good luck and have fun!

Task 3:

Install the {flexdashboard} package and create a new R Markdown file in your project by going to File > New File… > R Markdown… > From Template > Flexdashboard.

Using the documentation for {flexdashboard} online, create a basic dashboard that shows a plot (static or interactive) in at least three chart areas. Play with the layout if you’re feeling brave.