What is the best way to location vs intensity?

[Rhelp]

Using R studio and preferably ggplot what is the best way to plot the following data.

I have a data-set containing UK postcodes and a corresponding number. Eg.
PC Number
XXX XXX 123456

I would like to create a plot of the UK with the postcodes plotted and the plot intensity corresponds to the number value.

What would be the easiest way to do this?

[jlacko]

UK post codes are somewhat tricky (they are not defined as polygons, but a set of addresses, not necessarily continuous).

You can download a shapefile of reconstructed boundaries - a good approximation for most use cases - from Open Door Logistics web pages.

The shapefile can be read in via {sf} package workflow; it will be a modified data.frame, so it should be easy to attach your data using one of the dplyr::*_join() family functions.

Recent versions of {ggplot2} support geom_sf(), which is a way to visualize sf objects, including polygons; just set the fill aesthetic to your value, and proceed like you would with an ordinary ggplot.

[Rhelp]

Will the shapefile automatically correctly join to the postcodes? Or will I have to manually join the reconstructed boundaries to the postcodes?

[jlacko]

This will of course depend on the way keys are set in your data, over which I have little control

Consider this example, built on leaflet (as I wanted to show the basemap):

library(sf)

data <- data.frame(name = "CB2 1") # Cambridge university - historic area

raw <- st_read("./src/Sectors.shp", # from https://www.opendoorlogistics.com/
               stringsAsFactors = F)

joined <- dplyr::inner_join(raw, data)

library(leaflet)

leaflet(joined) %>% 
  addProviderTiles("Stamen.Toner") %>% 
  addPolygons(color = "cornflowerblue")