Hi!

I posted a similar question a month ago. It helped me a lot. Maybe these
answers will help you too? The last answer gives a complete example of a
choropleth map.

http://r-sig-geo.2731867.n2.nabble.com/Choropleth-map-td7586627.html

Good luck with it!

Janka


2014-08-01 13:46 GMT+02:00 HallS <sam_l_cruickshank@hotmail.com>:

> as my data is confidential I've tried to make an anonymous data set. I
> started with a shp file, and csv with a matching ID column and further
> data,
> including "Col_2" which is a higher level region of an aggregate of the
> shapefile region. At first I merged these but it jumbled the data so I
> managed to do it via match() and then gUnionCascaded. I have now retrieved
> aggregated polygons without the internal boundaries, but I'm a bit lost as
> to how I begin to utilise these in a choropleth map. All the instructions I
> read seem out of context and being new to R I don't know how to start. I've
> had a few abortive efforts with ggplot2 but all failed. Any help or
> pointers
> to useful articles would be appreciated. Dummy code below.
>
> install.packages("sp")
> install.packages("rgdal")
> install.packages("maptools") #read in shape files
> install.packages("rgeos") # needed by maptools
> install.packages("RColorBrewer")
> install.packages("scales")
> install.packages("gridExtra")
>
> library("sp")
> library("rgdal")
> library("maptools")
> library("ggplot2")
> library("rgeos")
> library("RColorBrewer")
> library("scales")
> library("gridExtra")
>
> ##Shapefile from http://www.sharegeo.ac.uk/handle/10672/50
>
> ##Working matched code
> setwd("...")
> gc<-read.csv("...dummy.csv", header=TRUE)
> str(gc)
>
> ##'data.frame':  9 obs. of  3 variables:
> ##$ NAME : Factor w/ 9 levels "East Midlands",..: 4 5 3 8 9 7 1 6 2
> ##$ Col_2: int  1 1 1 1 3 3 3 3 3
> ##$ Data : int  8 7 6 5 2 0 1 5 0
>
> #Shape File and match file
> frame<-readOGR(dsn=".../Regions",
>                layer="Regions")
> str(frame)
> plot(frame)
>
> frame@data=gc[match(frame@data[,"NAME"], gc[,"NAME"]),]
>
> ##Successfully merged, now to concatenate by territory
>
> ##Region 1
> #With internal boundaries
> REGION1 <- frame[ which(frame$Col_2=='1'), ]
> plot(REGION1)
> #Joined so no internal boundaries
> REGIONA <- gUnionCascaded(frame[ which(frame$Col_2=='1'), ])
> plot(REGIONA)
>
> ##Region 3
> #With internal boundaries
> REGION3 <- frame[ which(frame$Col_2=='3'), ]
> plot(REGION3)
> #Joined so no internal boundaries
> REGIONC <- gUnionCascaded(frame[ which(frame$Col_2=='3'), ])
> plot(REGIONC)
>
>
>
> --
> View this message in context:
> http://r-sig-geo.2731867.n2.nabble.com/Choropleth-maps-using-matched-csv-shp-files-tp7586853.html
> Sent from the R-sig-geo mailing list archive at Nabble.com.
>
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