[R-sig-Geo] Merging regions in a map & plotting values

[Joshua Onyango]

Hi Bob
Thanks for the help, merging region appear to work now.  However still stuck on the other bit on merging data with spatial object, ("regions") in this case to be able to plot the data points. I mainly want to plot information such as % disease prevalence in every region, temperature, flock size etc
Thanks advance
Josh 

    On Wednesday, 20 January 2016, 1:49, boB Rudis <bob at rudis.net> wrote:
 

 I think this might help you out a bit (it's probably worth taking the
time to look it over as it removes much of the redundant code you
had).

library(sp)
library(maptools)
library(rgeos)
library(rgdal)
library(dplyr)
library(ggplot2)
library(ggthemes)
library(ggalt)

URL <- "http://census.edina.ac.uk/ukborders/easy_download/prebuilt/shape/England_gor_2011.zip"
fil <- basename(URL)
if (!file.exists(fil)) download.file(URL, fil)

fils <- unzip(fil)
shp <- grep("shp$", fils, value=TRUE)

region <- readOGR(shp, ogrListLayers(shp)[1], stringsAsFactors=FALSE)

# define new regions
region at data$Region <- c("East", "South &S.E", "North", "North", "Midlands",
                        "North", "SouthWest", "Midlands", "South & S.E")
colnames(region at data) <- c("code", "name","Region")

# dissolve polygons and simplify the shapes
regions <- unionSpatialPolygons(region, region at data$Region)
regions <- gSimplify(regions, 100, topologyPreserve=TRUE)
regions <- gBuffer(regions, byid=TRUE, width=0)

# coord_map and coord_proj will eventually work but this transformation
# will absolutely speed up the calculations

regions <- SpatialPolygonsDataFrame(spTransform(regions,
                                                CRS("+proj=longlat
+ellps=sphere +no_defs")),
                                    data.frame(Region=names(regions),
                                              row.names=names(regions),
                                              stringsAsFactors=FALSE))

eng_map <- fortify(regions, region="Region")

# new projection (good for the UK)
eng_proj <- "+proj=aea +lat_0=54.55635146083455 +lon_0=-3.076171875"

ggplot() +
  # base map
  geom_map(data=eng_map, map=eng_map,
          aes(x=long, y=lat, map_id=id),
          color=NA, fill=NA, size=0.5) +
  # sample fill of the regions
  geom_map(data=data.frame(id=unique(eng_map$id)), map=eng_map,
          aes(map_id=id, fill=id),
          color="white", size=0.15) +
  scale_fill_brewer(palette="Set2") +
  coord_proj(eng_proj) +
  theme_map()

NOTE: this requires the new ggplot2 (2.0)

On Tue, Jan 19, 2016 at 3:04 PM, Joshua Onyango via R-sig-Geo
<r-sig-geo at r-project.org> wrote:
> HelloI'm new into creating maps in R so any help would be great.I have read a few articles on the internet - mainly blogs on mapping in R which I have tried to follow with no much success. Basically I want to merge merge some English regions from 8 to 5 then show information that relates to disease prevalence, temperature etc
> Here is what I have tried but sound like this cant run due to computer memory or must be doing following a wrong approach.
>
>
>> #Getting theshapefile into working directory
>
>> download.file("http://census.edina.ac.uk/ukborders/easy_download/prebuilt/shape/England_gor_2011.zip",
>
>                destfile ="lad-region-lookup.zip")> #inzipping theshapefile folder
>
>>unzip("lad-region-lookup.zip", exdir = ".")
>
>> #reading theshapefile in r
>
>> region <-readOGR(".", "England_gor_2011")
>
> OGR data source withdriver: ESRI Shapefile
>
> Source:".", layer: "England_gor_2011"
>
> with 9 features
>
> It has 2 fields
>
>> # Check theshapefile has loaded correctly
>
>> plot(region)
>
>>
>
>> lu <-data.frame()
>
>> lu <-rbind(lu, region at data)
>
>> lu$CODE <-as.character(lu$CODE)
>
>> lu$NAME <-as.character(lu$NAME)
>
>> lu$Region <-NA
>
>> name=c("East", "South &S.E","North","North","Midlands","North","SouthWest","Midlands","South & S.E")
>
>> lu$Region <-name
>
>> # Merge lu(LookUp) into polygons,
>
>> region at data$CODE<- as.character(region at data$CODE)
>
>> region at data<- full_join(region at data, lu, by = "CODE")
>
>> # Tidy mergeddata
>
>> region at data<- select(region at data, -NAME.x)
>
>>colnames(region at data) <- c("code", "name","Region")
>
>>
>
>> # Ensureshapefile row.names and polygon IDs are sensible
>
>>row.names(region) <- row.names(region at data)
>
>> region <-spChFIDs(region, row.names(region))
>
>>
>
>> # Now thedissolve
>
>> region <-gUnaryUnion(region, id = region at data$Region)
>
>>
>
>> # If you want torecreate an object with a data frame
>
>> # make sure row namesmatch
>
>>row.names(region) <- as.character(1:length(region))
>
>>
>
>> # Extract thedata you want (the larger geography)
>
>> lu <-unique(lu$Region)
>
>> lu <-as.data.frame(lu)
>
>> colnames(lu)<- "Region"  # your datawill probably have more than 1 row!
>
>>
>
>> # And add thedata back in
>
>> region <-SpatialPolygonsDataFrame(region, lu)
>
>> region2 <-merge(region at data, data, by="Region")
>
>> dat2=fortify(region,region="Region")
>
>>names(dat2)[names(dat2)=="id"]<-"Region"
>
>> dat <-merge(dat2, region2, by="Region")
>
> Error: cannotallocate vector of size 904.9 Mb
>
> In addition:Warning messages:
>
> 1: In`[.data.frame`(x, c(m$xi, if (all.x) m$x.alone), c(by.x,seq_len(ncx)[-by.x]),  :
>
>  Reached total allocation of 4016Mb: seehelp(memory.size)
>
>
>
>
> Any simpler approach will be highly appreciated.
> Thanks
> Josh
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