I've been trying to plot a map of the world on ggplot2. I followed the threads of emails: ggplot map with l but I do run into the same error message and I don't understand the author comments on how to fix it.
library(rgdal)
library(ggplot2)
library(maptools)
library(sp)
gpclibPermit()
world.map <- readOGR(dsn="data", layer="TM_WORLD_BORDERS_SIMPL-0.3")
world.ggmap <- fortify(world.map, region = "NAME")
> world.ggmap <- fortify(world.map, region = "NAME")
Error in nchar(ID) : invalid multibyte string 1
So, I followed the instructions here, more or less, to create this world map:
library(ggplot2)
library(cshapes)
world <- cshp(date=as.Date("2008-1-1"))
world.points <- fortify(world, region='COWCODE')
p <- ggplot(world.points, aes(long,lat,group=group)) + geom_polygon()
p
It looks like it takes some more work to combine this with data, e.g. for a thematic map, but the post above goes through this in detail.
Not sure if you still need an answer to this, but I hope it's helpful to someone in any case.
Related
I am using similar to code to other scripts with different shape files from Statistics Canada. However, I can't get a simple script to work with a provincial map. I think the problem is simple but I can't see it.
setwd("D:\\OneDrive\\lfs_stuff")
project_folder<-getwd()
data_folder<-project_folder
library(tidyverse)
#now start the map
library(rgeos)
library(rgdal)
library(maptools)
library(sp)
library(mapproj)
library(ggplot2)
#get test data
mydata<-read_csv("map_data.csv",col_types=list(col_character(),col_double()))
print(mydata)
# shape file came from this link for a digital shape file
# http://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/files-fichiers/2016/lpr_000a16a_e.zip
target_url<-"http://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/files-fichiers/2016/lpr_000a16a_e.zip"
url_file<-"lpr_000a16a_e.zip"
download_target<-paste0(project_folder,"/",url_file)
download.file(target_url,download_target,mode="wb",quiet=FALSE)
unzip(download_target,overwrite=TRUE,exdir=data_folder)
provincial_shape_file<-gsub(".zip",".shp",download_target)
provincial_shp<-readOGR(dsn=provincial_shape_file,layer="lpr_000a16a_e")
#convert it to the reqired data structure. the id vbl will contain the provincial codes
prov_base_map<-fortify(provincial_shp,region="PRUID")
map_data_1<-merge(prov_base_map,as_data_frame(mydata),by="id")
map1<-ggplot()+
geom_map(data=map_data_1,map=map_data_1,stat="identity",
aes(map_id=id,x=long,y=lat,fill=(pch),group=group),
colour="black",size=0.3)+
coord_map()
print(map1)
The download for the shape file is in the script. The mydata file is shown below
"id","pch"
"10",0.667259786476859
"11",5.63186813186813
"12",2.12053571428572
"13",-0.563697857948142
"24",0.150669774230772
"35",1.15309092428315
"46",0.479282622139765
"47",1.70242950877815
"48",1.84482533036765
"59",1.96197656978394
Here's one way with sf (though I think the ultimate issue is not having the id being identified correctly):
library(sf)
library(httr)
library(tidyverse)
read.csv(text='"id","pch"
"10",0.667259786476859
"11",5.63186813186813
"12",2.12053571428572
"13",-0.563697857948142
"24",0.150669774230772
"35",1.15309092428315
"46",0.479282622139765
"47",1.70242950877815
"48",1.84482533036765
"59",1.96197656978394',
stringsAsFactors=FALSE,
colClasses = c("character", "double")) -> xdf
# cross-platform-friendly d/l with caching built-in
try(httr::GET(
url = "http://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/files-fichiers/2016/lpr_000a16a_e.zip",
httr::write_disk("~/Data/lpr_00a16a_e.zip"),
httr::progress()
)) -> res
fils <- unzip("~/Data/lpr_00a16a_e.zip", exdir = "~/Data/lpr")
ca_map <- st_read(grep("shp$", fils, value=TRUE), stringsAsFactors = FALSE)
ca_map <- st_simplify(ca_map, TRUE, 10) # you don't need the coastlines to be that detailed
ca_map <- left_join(ca_map, xdf, by=c("PRUID"="id"))
ggplot(ca_map) +
geom_sf(aes(fill = pch)) +
viridis::scale_fill_viridis(direction=-1, option="magma") +
coord_sf()
As an aside, even though I simplified the shapefile (for faster plotting) I'd hunt around for a light[er]-weight GeoJSON version of the provinces since the one you grabbed has super fine-grained coastlines and you absolutely don't need that for a choropleth.
I'm trying to plot custom boundaries (dma's) into a google map.
library(ggmap)
library(ggplot2)
US <- get_map(location = c(-95.7129,37.0902),zoom = 3)
US_map <- ggmap(US)
then using the following CSV file with the coordinates groups and order
https://www.dropbox.com/s/3xv192k5401np4r/DMAs%20coordinates%20sample.csv?dl=0
Then I can plot the coordinates using dots:
smpl <- read.csv('DMAs coordinates sample.csv')
US_map + geom_point(data=smpl,aes(x=Longitude, y=Latitude),size=0.01)
But I would like to plot lines connected by these dots using the path from point_order and group each set of lines using dma_boundary.UniqueID I'm sure there's a way to do this. but I cannot find the right way.
I found a way to do this,
Using geom_path for each group represented by dma_boundaty.UniqueID
As the data is already sorted by sub_polygon_id and point_order we use geom_path to use the order set in data. Then,
library(ggplot2)
library(data.table)
library(ggmap)
dma_boundaty <- data.table(read.csv('.../path')
US <- get_map(location = c(-95.7129,37.0902),zoom = 3)
US_map <- ggmap(US)
dma_map <- US_map + lapply(0:205,function(i) {
geom_path(data=dma_boundary[dma_boundary.UniqueID == i,],aes(x=Longitude, y=Latitude))})
I am having trouble merging shapefiles in R. Here is my code thus far:
library(rgdal)
library(maptools)
library(gridExtra)
setwd("/Users/Cornelius/Dropbox/Cornelius_Sharedfolder")
#Load a geodatabase
fgdb = "/Users/Cornelius/Dropbox/Cornelius_Sharedfolder/RwandaGDB.gdb"
subset(ogrDrivers(), grepl("GDB", name))
fc_list = ogrListLayers(fgdb)
print(fc_list)
#Get the shapefiles from the geodatabase:
Residence=readOGR(dsn=fgdb, layer="Résidence")
Territoire = readOGR(dsn=fgdb,layer="Territoire")
Chefferie=readOGR(ds=fgdb, layer="Chefferie")
Sous_Chefferie=readOGR(ds=fgdb, layer="Sous_Chefferie")
RwandaPre2002=readOGR(ds=fgdb, layer="RwandaPre2002")
Country_Boundary2012=readOGR(ds=fgdb, layer="Country_Boundary2012")
Province_Boundary2012=readOGR(ds=fgdb, layer="Province_Boundary2012")
Sector_Boundary2012=readOGR(ds=fgdb, layer="Sector_Boundary2012")
District_Boundary2012=readOGR(ds=fgdb, layer="District_Boundary2012")
Cell_Boundary2012=readOGR(ds=fgdb, layer="Cell_Boundary2012")
x = list(Residence, Territoire, Sous_Chefferie, RwandaPre2002, Country_Boundary2012, Province_Boundary2012, Sector_Boundary2012, District_Boundary2012, Cell_Boundary2012)}
This all goes fine. However, when I try to merge two shapefiles - for example, Residence and Territoire, and use the following code, it gives me an error:
test_bind <-spRbind(Territoire, Residence)
The error says: "non-unique polygon IDs."
I'm not sure what this means. Could you please help?
I am trying to plot coordinate points on a map, but I get the plot.new error. Could you please help?
library(maptools)
library(ggmap)
library(mapproj)
table <- read.table("table.txt", header=TRUE, sep=",")
map <- get_map(location = 'France', zoom = 6, maptype = c("toner"))
points(table$LONG, table$LAT, pch=21, bg=color, cex=0.7, lwd=.4)
ggmap(map)
Here is an idea of what the table looks like:
CITY,LAT,LONG
Paris,48.856667,2.351944
Lyon,45.766944,4.834167
Bordeaux,44.838611,0.578334
Try geom_point:
library(maptools)
library(ggmap)
library(mapproj)
city <- c("Paris", "Lyon", "Bordeaux")
my.lat <- c(48.856667, 45.766944, 44.838611)
my.long <- c(2.351944, 4.834167, 0.578334)
points <- data.frame(lon=my.long, lat=my.lat)
map <- get_map(location = c(left = -5, bottom = 42, right=9, top = 51 ), source = 'stamen', maptype = 'toner')
france <- ggmap(map, extent = 'normal')
france + geom_point(data=points, col="red")
Try the command ?ggmap for a list of great examples. I think the manual has done a good job, because before I read your question, I didn't even know of any of these functions. Thanks! I've learned something new.
Learn to walk before you try and run.
The points function adds points to an existing graphic. You haven't got an existing graphic yet (unless you've already done something you've not showed us).
Hence if you do points before starting a plot, you'll get an error. eg:
points(1:10,1:10) # plot.new error
plot(1:10,1:10) # no error, starts a new plot
points(10:1,1:10) # adds extra points, no error.
All your stuff with ggplot is irrelevant. Also, this is not about statistics, so you should have posted to StackOverflow. I've flagged this and it might get migrated...
library(sp)
library(spdep)
library(ggplot2)
library(ggmap)
library(rgdal)
Get and fiddle with data:
nc.sids <- readShapePoly(system.file("etc/shapes/sids.shp", package="spdep")[1],ID="FIPSNO", proj4string=CRS("+proj=longlat +ellps=clrk66"))
nc.sids=spTransform(nc.sids,CRS("+init=epsg:4326"))
Get background map from stamen.com, plot, looks nice:
ncmap = get_map(location=as.vector(bbox(nc.sids)),source="stamen",maptype="toner",zoom=7)
ggmap(ncmap)
Create a data frame with long,lat,Z, and plot over the map and a blank plot:
ncP = data.frame(coordinates(nc.sids),runif(nrow(nc.sids)))
colnames(ncP)=c("long","lat","Z")
ggmap(ncmap)+geom_point(aes(x=long,y=lat,col=Z),data=ncP)
ggplot()+geom_point(aes(x=long,y=lat,col=Z),data=ncP)
give it some unique ids called 'id' and fortify (with vitamins and iron?)
nc.sids#data[,1]=1:nrow(nc.sids)
names(nc.sids)[1]="id"
ncFort = fortify(nc.sids)
Now, my map and my limits, I want to plot the 74 birth rate:
myMap = geom_map(aes(fill=BIR74,map_id=id),map=ncFort,data=nc.sids#data)
Limits = expand_limits(x=ncFort$long,y=ncFort$lat)
and on a blank plot I can:
ggplot() + myMap + Limits
but on a ggmap I can't:
ggmap(ncmap) + myMap + Limits
# Error in eval(expr, envir, enclos) : object 'lon' not found
Some versions:
> packageDescription("ggplot2")$Version
[1] "0.9.0"
> packageDescription("ggmap")$Version
[1] "2.0"
I can add geom_polygon to ggplot or ggmap and it works as expected. So something is up with geom_map....
The error message is, I think, the result of an inheritance issue. Typically, it comes about when different data frames are used in subsequent layers.
In ggplot2, every layer inherits default aes mappings set globally in the initial call to ggplot. For instance, ggplot(data = data, aes(x = x, y = y)) sets x and y mappings globally so that all subsequent layers expect to see x and y in whatever data frame has been assigned to them. If x and y are not present, an error message similar to the one you got results. See here for a similar problem and a range of solutions.
In your case, it's not obvious because the first call is to ggmap - you can't see the mappings nor how they are set because ggmap is all nicely wrapped up. Nevertheless, ggmap calls ggplot somewhere, and so default aesthetic mappings must have been set somewhere in the initial call to ggmap. It follows then that ggmap followed by geom_map without taking account of inheritance issues results in the error.
So, Kohske's advice in the earlier post applies - "you need to nullify the lon aes in geom_map when you use a different dataset". Without knowing too much about what has been set or how they've been set, it's probably simplest to globber the lot by adding inherit.aes = FALSE to the second layer - the call to geom_map.
Note that you don't get the error message with ggplot() + myMap + Limits because no aesthetics have been set in the ggplot call.
In what follows, I'm using R version 2.15.0, ggplot2 version 0.9.1, and ggmap version 2.1. I use your code almost exactly, except for the addition of inherit.aes = FALSE in the call to geom_map. That one small change allows ggmap and geom_map to be superimposed:
library(sp)
library(spdep)
library(ggplot2)
library(ggmap)
library(rgdal)
#Get and fiddle with data:
nc.sids <- readShapePoly(system.file("etc/shapes/sids.shp", package="spdep")[1],ID="FIPSNO", proj4string=CRS("+proj=longlat +ellps=clrk66"))
nc.sids=spTransform(nc.sids,CRS("+init=epsg:4326"))
#Get background map from stamen.com, plot, looks nice:
ncmap = get_map(location=as.vector(bbox(nc.sids)),source="stamen",maptype="toner",zoom=7)
ggmap(ncmap)
#Create a data frame with long,lat,Z, and plot over the map and a blank plot:
ncP = data.frame(coordinates(nc.sids),runif(nrow(nc.sids)))
colnames(ncP)=c("long","lat","Z")
ggmap(ncmap)+geom_point(aes(x=long,y=lat,col=Z),data=ncP)
ggplot()+geom_point(aes(x=long,y=lat,col=Z),data=ncP)
#give it some unique ids called 'id' and fortify (with vitamins and iron?)
nc.sids#data[,1]=1:nrow(nc.sids)
names(nc.sids)[1]="id"
ncFort = fortify(nc.sids)
#Now, my map and my limits, I want to plot the 74 birth rate:
myMap = geom_map(inherit.aes = FALSE, aes(fill=BIR74,map_id=id), map=ncFort,data=nc.sids#data)
Limits = expand_limits(x=ncFort$long,y=ncFort$lat)
# and on a blank plot I can:
ggplot() + myMap + Limits
# but on a ggmap I cant:
ggmap(ncmap) + myMap + Limits
The result from the last line of code is: