Most basic bubble chart with geom_point()
This post follows the previous step by step description of building bubble chart with ggplot2.
The idea is to turn the chart interactive:
- You can zoom by selecting an area of interest
- Hover a circle to get information about it
- Export to png
- Slide axis
- Double click to re-initialize.
This is done thanks to the ggplotly() function of the plotly package that turn any ggplot2 chart object interactive. Note the little trick to custom the tooltip content.
# Libraries
library(ggplot2)
library(dplyr)
library(plotly)
library(viridis)
library(hrbrthemes)
# The dataset is provided in the gapminder library
library(gapminder)
data <- gapminder %>% filter(year=="2007") %>% dplyr::select(-year)
# Interactive version
p <- data %>%
mutate(gdpPercap=round(gdpPercap,0)) %>%
mutate(pop=round(pop/1000000,2)) %>%
mutate(lifeExp=round(lifeExp,1)) %>%
# Reorder countries to having big bubbles on top
arrange(desc(pop)) %>%
mutate(country = factor(country, country)) %>%
# prepare text for tooltip
mutate(text = paste("Country: ", country, "\nPopulation (M): ", pop, "\nLife Expectancy: ", lifeExp, "\nGdp per capita: ", gdpPercap, sep="")) %>%
# Classic ggplot
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")
# turn ggplot interactive with plotly
pp <- ggplotly(p, tooltip="text")
pp
# save the widget
# library(htmlwidgets)
# saveWidget(pp, file=paste0( getwd(), "/HtmlWidget/ggplotlyBubblechart.html"))Related chart types
Scatter
Heatmap
Correlogram
Bubble
Connected scatter
Density 2d