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

[boB Rudis]

(just noticed this)

You should probably fix the ""South &S.E" & ""South & S.E" (there's a
space missing in the former), too.

On Tue, Jan 19, 2016 at 8:48 PM, 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
>>         [[alternative HTML version deleted]]
>>
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