This is really cool, Jim - thanks a lot!
On Thu, Apr 2, 2015 at 6:18 PM, Jim Lemon <drjimlemon at gmail.com> wrote:
Hi Dimitri,
You can also try the color.scale function in plotrix, which allows you to
specify the NA color in the call.
newcol<-color.scale(mydata.final$Mean.Wait,extremes=c("yellow","red"),na.color="white")
Jim
On Fri, Apr 3, 2015 at 8:08 AM, Dimitri Liakhovitski
<dimitri.liakhovitski at gmail.com> wrote:
Jean, I think I fixed it:
newpal <- colorRamp(c("yellow", "red"))
missing <- is.na(mydata.final$Mean.Wait)
newcol <- ifelse(missing, "white",
rgb(newpal(mydata.final$Mean.Wait[!is.na(mydata.final$Mean.Wait)]/
max(mydata.final$Mean.Wait,
na.rm=T)), maxColorValue=255))
map('county', fill=TRUE, col=newcol,
resolution=0, lty=0, bg="transparent")
map('state', lwd=1, add=TRUE)
One understanding question: what exactly does this rgb line do and why
do we have to say "maxColorValue=255"?
Thank you!
On Thu, Apr 2, 2015 at 5:02 PM, Dimitri Liakhovitski
<dimitri.liakhovitski at gmail.com> wrote:
Thank you, Jean, but I think this newcol line is not working. I am
running:
newcol <- ifelse(missing, "white",
rgb(newpal(mydata.final$Mean.Wait/max(mydata.final$Mean.Wait,
na.rm=T)),
maxColorValue=255))
# And I am getting:
Error in rgb(newpal(mydata.final$Mean.Wait/max(mydata.final$Mean.Wait,
:
color intensity NA, not in 0:255
I think it's not liking the NAs - despite the ifelse...
On Thu, Apr 2, 2015 at 4:26 PM, Adams, Jean <jvadams at usgs.gov> wrote:
Dimitri,
You could use colorRamp() and rgb() to get more continuous colors.
For example
newpal <- colorRamp(c("yellow", "red"))
missing <- is.na(mydata.final$Mean.Wait)
newcol <- ifelse(missing, "white",
rgb(newpal(mydat$Mean.Wait/max(mydat$Mean.Wait)),
map('county', fill=TRUE, col=newcol,
resolution=0, lty=0, bg="transparent")
map('state', lwd=1, add=TRUE)
Jean
On Thu, Apr 2, 2015 at 12:03 PM, Dimitri Liakhovitski
<dimitri.liakhovitski at gmail.com> wrote:
I have a data frame 'mydata.final' (see below) that contains US
counties and a continuous numeric variable 'Mean.Wait' that ranges
from zero to 10 or so. I also created variable 'wait' that is based
the 'Mean.Wait' and takes on discrete values from 1 (lowest values
'Mean.Wait') to 5 (highest values on 'Mean.Wait').
I can create a map of the US with the counties colored based on the
values of 'wait' using R package 'maps':
#################################################################
### Generating an artificial data file:
#################################################################
library(maps)
mydata.final <- data.frame(county = (map('county', plot =
FALSE)$names),
stringsAsFactors = F)
### My numeric variable:
set.seed(123)
mydata.final$Mean.Wait <- runif(nrow(mydata.final)) * 10
### Introducing NAs to mimic my real data set:
set.seed(1234)
mydata.final$Mean.Wait[sample(1:nrow(mydata.final), 1500)] <- NA
### Cutting the original numeric variable into categories
### because I don't know how to color based on 'Mean.Wait':
mydata.final$wait <- cut(mydata.final$Mean.Wait, breaks = 5)
levels(mydata.final$wait) <- 1:5
mydata.final$wait <- as.numeric(as.character(mydata.final$wait))
####################################################################
Building a US map based on 'wait' (5 categories)
#################################################################
### Creating my 5 colors:
pal <- colorRampPalette(c("yellow", "red"))
allcolors <- pal(5)
### Looking at my 5 colors:
barplot(1:5, rep(1,5), col = allcolors, horiz = T)
### Builiding the US map using 5 categories in 'wait':
map('county', fill = TRUE, col = allcolors[mydata.final$wait],
resolution = 0, lty = 0, bg = "transparent")
map('state', lwd=1, add=TRUE)
My goal is: instead of splitting 'Mean.Wait' into 5 ordered
('wait'), I'd like to color the counties on the map based on the
intensity of my (continuous) 'Mean.Wait'. What would be the way to
it and maybe even to add a legend?
Thanks a lot!
--
Dimitri Liakhovitski