Merging regions in a map & plotting values

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
       [[alternative HTML version deleted]]