CODEWITHSUNDEEP
rggplot2grid-layoutcowplotrworldmap
CodeNoob
CodeNoob

Reputation: 1840

ggplot2 in combination with rworldmap

I make the following rworldplot:

library(rworldmap)
#> Loading required package: sp
#> ### Welcome to rworldmap ###
#> For a short introduction type :   vignette('rworldmap')
library(RColorBrewer)
test.data <- data.frame(
  country = c('USA','Denmark','Australia','Germany'),
  value = c(4000,1000,2300,100)
)
sPDF <- joinCountryData2Map(test.data,joinCode = "NAME",nameJoinColumn = "country")
#> 4 codes from your data successfully matched countries in the map
#> 0 codes from your data failed to match with a country code in the map
#> 239 codes from the map weren't represented in your data
colourPalette <- brewer.pal(4,'Reds')
mapParams <- mapCountryData(sPDF, nameColumnToPlot="value", colourPalette=colourPalette, catMethod=c(0,500,1000,2300,5000), addLegend=FALSE, mapTitle = 'TEST')
do.call( addMapLegend, c( mapParams
                          , legendLabels="all"
                          , legendWidth=0.5 ))

For clarity I want to add a barplot as well:

library(ggplot2)
barplot <- ggplot(test.data, aes(x=reorder(country,-value), y = value)) +
  geom_bar(stat='identity', fill = 'darkred') + 
  theme_classic()
barplot

Ideally I want to combine the rworldmap plot and the ggplot in one figure using e.g. grid.arrange or the cowplot package. I know this is easy for different ggplot objects however the do.call plots the rworldmap directly, hence I don't know how I can get it to word like grid.arrange(<rworlddmapplot>, barplot).

Upvotes: 2

Views: 555

Answers (1)

Claus Wilke
Claus Wilke

Reputation: 17810

The plot_grid() function from cowplot can take a function argument that draws the plot you want to show.

library(rworldmap)
#> Loading required package: sp
#> ### Welcome to rworldmap ###
#> For a short introduction type :   vignette('rworldmap')
library(RColorBrewer)

test.data <- data.frame(
  country = c('USA','Denmark','Australia','Germany'),
  value = c(4000,1000,2300,100)
)

draw_map <- function(test.data) {
  function() {
    sPDF <- joinCountryData2Map(test.data,joinCode = "NAME",nameJoinColumn = "country")
    colourPalette <- brewer.pal(4,'Reds')
    mapParams <- mapCountryData(sPDF, nameColumnToPlot="value", colourPalette=colourPalette, catMethod=c(0,500,1000,2300,5000), addLegend=FALSE, mapTitle = 'TEST')
    do.call( addMapLegend, c( mapParams
                          , legendLabels="all"
                          , legendWidth=0.5 ))
  }
}

library(ggplot2)
barplot <- ggplot(test.data, aes(x=reorder(country,-value), y = value)) +
  geom_bar(stat='identity', fill = 'darkred') + 
  theme_classic()

library(cowplot)
#> 
#> ********************************************************
#> Note: As of version 1.0.0, cowplot does not change the
#>   default ggplot2 theme anymore. To recover the previous
#>   behavior, execute:
#>   theme_set(theme_cowplot())
#> ********************************************************

plot_grid(barplot, draw_map(test.data))
#> 4 codes from your data successfully matched countries in the map
#> 0 codes from your data failed to match with a country code in the map
#> 239 codes from the map weren't represented in your data

Created on 2019-08-26 by the reprex package (v0.3.0)

Upvotes: 2

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