Bill Poling
2018-Sep-14 07:57 UTC
[R] [R-sig-Geo] Help with simple Map of US states with predefined regions Version 2 (Solved)
Good morning Don, I cannot thank you enough for your support and the trouble you
went to.
I am novice useR and the only analyst in the shop asked to learn R and the
demands are growing faster than my knowledge intake, lots of laughs!
Best regards
WHP
From: MacQueen, Don <macqueen1 at llnl.gov>
Sent: Thursday, September 13, 2018 4:41 PM
To: Bill Poling <Bill.Poling at zelis.com>; r-sig-geo at r-project.org
Subject: Re: [R-sig-Geo] Help with simple Map of US states with predefined
regions Version 2
I know this is not a complete solution -- and it's a very different approach
-- but it should at least show you a way to reliably get states colored by
region.
(I also left out Alaska and Hawaii, since the point here is how to color the
regions)
require(sp)
require(rgdal)
## US Census Bureau Tiger file -- polygons of each US State
## try this URL for download
##
https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2017&layergroup=States+%28and+equivalent%29<https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2017&layergroup=States+%28and+equivalent%29>
## unzip to working directory ( '.' )
ustf <- readOGR('.', 'tl_2017_us_state',
stringsAsFactors=FALSE)
## note, the Tiger file includes 6 additional territories
dim(ustf)
## [1] 56 14
## get rid of the extra six territories (state.name<http://state.name>
comes with R)
cus <- subset(ustf, NAME %in% state.name<http://state.name>)
## cheap rename
cus$state <- cus$NAME
cus$abb <- cus$STUSPS
## invent ridiculous groupings of states
cus$grp <- 'a'
cus$grp[11:20] <- 'b'
cus$grp[21:30] <- 'c'
cus$grp[31:40] <- 'd'
cus$grp[41:50] <- 'e'
## assign colors to the groups
cus$color <- 'red'
cus$color[cus$grp=='b'] <- 'green'
cus$color[cus$grp=='c'] <- 'blue'
cus$color[cus$grp=='d'] <- 'brown'
cus$color[cus$grp=='e'] <- 'cyan'
## exclude Alaska, Hawaii
cus <- subset(cus, !(state %in% c('Alaska','Hawaii')))
## get rid of extraneous variables (optional)
cus <- cus[ , c('state','REGION','abb',
'grp') ]
## plot colored by regions as defined in the Census Bureau Tiger file
plot(cus, col=cus$REGION, usePolypath=FALSE)
## color "1" is black, looks bad, do this instead
plot(cus, col=as.numeric(cus$REGION)+1, usePolypath=FALSE)
text(coordinates(cus), cus$abb, col='white', cex=0.75)
## colors specified by a color variable in the data
plot(cus, col=cus$color, usePolypath=FALSE)
text(coordinates(cus), cus$abb, col='white', cex=0.75)
(my preferred graphics device does not support Polypath, but probably most
others do, so one can omit usePolypath=FALSE)
-Don
--
Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
925-423-1062
Lab cell 925-724-7509
?On 9/13/18, 5:17 AM, "R-sig-Geo on behalf of Bill Poling"
<r-sig-geo-bounces at r-project.org on behalf of Bill.Poling at
zelis.com<mailto:r-sig-geo-bounces at
r-project.org%20on%20behalf%20of%20Bill.Poling at zelis.com>> wrote:
Hi,
I hope someone can help me finalize this please.
I am coming close to what I need using variations from two ggplot2 tutorials.
This first gives me the map of the US with AK & HI but I cannot figure out
how to get my 5 regions colored
#https://stackoverflow.com/questions/38021188/how-to-draw-u-s-state-map-with-hi-and-ak-with-state-abbreviations-centered-us?rq=1<https://stackoverflow.com/questions/38021188/how-to-draw-u-s-state-map-with-hi-and-ak-with-state-abbreviations-centered-us?rq=1>
library(ggplot2)
install.packages("ggalt")
library(ggalt) # coord_proj
library(albersusa) # devtools::install_github("hrbrmstr/albersusa")
install.packages("ggthemes")
library(ggthemes) # theme_map
install.packages("rgeos")
library(rgeos) # centroids
library(dplyr)
# composite map with AK & HI
usa_map <- usa_composite()
# calculate the centroids for each state gCentroid(usa_map, byid=TRUE) %>%
as.data.frame() %>%
mutate(state=usa_map at data$iso_3166_2) -> centroids
# make it usable in ggplot2
usa_map <- fortify(usa_map)
View(usa_map)
t1 <- head(usa_map,n=5)
knitr::kable(t1, row.names=FALSE, align=c("l", "l",
"r", "r", "r"))
#
# |long |lat | group| order| region|subregion |
# |:---------|:--------|-----:|-----:|-------:|:---------|
# |-87.46201 |30.38968 | 1| 1| alabama|NA |
# |-87.48493 |30.37249 | 1| 2| alabama|NA |
# |-87.52503 |30.37249 | 1| 3| alabama|NA |
# |-87.53076 |30.33239 | 1| 4| alabama|NA |
# |-87.57087 |30.32665 | 1| 5| alabama|NA |
usa_map <- fortify(usa_map)
gg <- ggplot()
gg <- gg + geom_map(data=usa_map, map=usa_map,
aes(long, lat, map_id=id),
color="#2b2b2b", size=0.1, fill=NA)
gg <- gg + geom_text(data=centroids, aes(x, y, label=state), size=2) gg <-
gg + coord_proj(us_laea_proj) gg <- gg + theme_map() gg
#************************************************************************************************************************************************************************************/
This second is an alternative (however not liking AK&HI, not coming into the
map like scenario one above) but also ignoring new Mexico (because recognizing a
seventh field value) and I suspect it will do the same for new York and new
jersey etc.. when I add them to the list.
Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, :
line 12 did not have 6 elements
When I use newmexico (all one word) it appears white in the map like the other
states not in the table statement
#https://stackoverflow.com/questions/38777732/r-code-to-generating-map-of-us-states-with-specific-colors<https://stackoverflow.com/questions/38777732/r-code-to-generating-map-of-us-states-with-specific-colors>
library(ggplot2)
read.table(text="State.Code region St_Abbr Num_Estab colors
1 1 alaska Ak 13123 #f7931e
3 1 arizona AZ 18053 #f7931e
5 1 california CA 143937 #f7931e
2 1 hawaii HI 123456 #f7931e
4 1 nevada NV 654321 #f7931e
6 1 oregon OR 321456 #f7931e
7 1 washington WA 456123 #f7931e
8 2 colorado CO 987654 #787878
9 2 idaho ID 13549 #787878
10 2 kansas KS 94531 #787878
11 2 montana MT 456321 #787878
12 2 new mexico NM 582310 #787878 <---Not liking new mexico, saying not 6
13 2 oklahoma OK 214567 #787878
14 2 texas TX 675421 #787878
15 2 utah UT 754321 #787878
16 2 wyoming WY 543124 #787878 ",
stringsAsFactors=FALSE, header=TRUE, comment.char="") -> df
usa_map1 <- map_data("state")
t1 <- head(usa_map1,n=5)
knitr::kable(t1, row.names=FALSE, align=c("l", "l",
"r", "r", "r"))
View(usa_map1)
#
# |long |lat | group| order| region|subregion |
# |:---------|:--------|-----:|-----:|-------:|:---------|
# |-87.46201 |30.38968 | 1| 1| alabama|NA |
# |-87.48493 |30.37249 | 1| 2| alabama|NA |
# |-87.52503 |30.37249 | 1| 3| alabama|NA |
# |-87.53076 |30.33239 | 1| 4| alabama|NA |
# |-87.57087 |30.32665 | 1| 5| alabama|NA |
gg <- ggplot()
#View(gg)
gg <- gg + geom_map(data=usa_map1, map=usa_map1,
aes(long, lat, map_id=region),
color="#2b2b2b", size=0.15, fill=NA)
gg <- gg + geom_map(data=df, map=usa_map1,
aes(fill=colors, map_id=region),
color="#2b2b2b", size=0.15)
gg <- gg + geom_text(data=centroids, aes(x, y, label=state), size=2) gg <-
gg + coord_proj(us_laea_proj) gg <- gg + theme_map() gg
gg <- gg + scale_color_identity()
gg <- gg + coord_map("polyconic")
gg <- gg + ggthemes::theme_map()
gg
#c( "colorado", "idaho", "kansas",
"montana", "new mexico",
"oklahoma","texas", "utah", "wyoming") )
#c("alaska", "arizona", "california",
"hawaii", "nevada",
"oregon","washington"))
William H. Poling, Ph.D., MPH
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