Bubble Maps in ggplot2

How to make Bubble Maps in ggplot2 with Plotly.

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Basic scatterplot map

library(plotly)
library(ggplot2)
library(dplyr)
library(maps)

UK <- map_data("world") %>% filter(region=="UK")
data <- world.cities %>% filter(country.etc=="UK")

p <- ggplot() +
  geom_polygon(data = UK, aes(x=long, y = lat, group = group), fill="grey", alpha=0.3) +
  geom_point( data=data, aes(x=long, y=lat)) +
  theme_void() + ylim(50,59) + coord_map() 


ggplotly(p)

Now let's highlight the 10 largest cities.

library(plotly)
library(ggplot2)
library(dplyr)
library(maps)
library(ggrepel)

UK <- map_data("world") %>% filter(region=="UK")
data <- world.cities %>% filter(country.etc=="UK")


p <- ggplot() +
  geom_polygon(data = UK, aes(x=long, y = lat, group = group), fill="grey", alpha=0.3) +
  geom_point( data=data, aes(x=long, y=lat, alpha=pop)) +
  geom_text_repel( data=data %>% arrange(pop) %>% tail(10), aes(x=long, y=lat, label=name), size=5) +
  geom_point( data=data %>% arrange(pop) %>% tail(10), aes(x=long, y=lat), color="red", size=3) +
  theme_void() + ylim(50,59) + coord_map() +
  theme(legend.position="none")

ggplotly(p)

Basic bubble map

Now we want to add another information. The number of inhabitant per city will be mapped to the colour and the size of the bubbles. Note that the order of city matters! It is advised to show the most important information on top (center). This can been done sorting your dataset before making the plot.

library(plotly)
library(ggplot2)
library(dplyr)
library(maps)
library(viridis)

UK <- map_data("world") %>% filter(region=="UK")
data <- world.cities %>% filter(country.etc=="UK")

p <- ggplot() +
  geom_polygon(data = UK, aes(x=long, y = lat, group = group), fill="grey", alpha=0.3) +
  geom_point( data=data, aes(x=long, y=lat, size=pop, color=pop)) +
  scale_size_continuous(range=c(1,12)) +
  scale_color_viridis(trans="log") +
  theme_void() + ylim(50,59) + coord_map() 

ggplotly(p)

What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at https://dashr.plot.ly/installation.

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:

library(plotly)

fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 

library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)

app <- Dash$new()
app$layout(
    htmlDiv(
        list(
            dccGraph(figure=fig) 
        )
     )
)

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)