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.liakhovit...@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 <jvad...@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$Mean.Wait)), maxColorValue=255))
>> map('county', fill=TRUE, col=newcol,
>> resolution=0, lty=0, bg="transparent")
>> map('state', lwd=1, add=TRUE)
>>
>> Jean
>>
>>
>> On Thu, Apr 2, 2015 at 12:03 PM, Dimitri Liakhovitski
>> <dimitri.liakhovit...@gmail.com> wrote:
>>>
>>> I have a data frame 'mydata.final' (see below) that contains US
>>> counties and a continuous numeric variable 'Mean.Wait' that ranges
>>> from zero to 10 or so. I also created variable 'wait' that is based on
>>> the 'Mean.Wait' and takes on discrete values from 1 (lowest values on
>>> 'Mean.Wait') to 5 (highest values on 'Mean.Wait').
>>>
>>> I can create a map of the US with the counties colored based on the
>>> values of 'wait' using R package 'maps':
>>>
>>> #################################################################
>>> ### Generating an artificial data file:
>>> #################################################################
>>> library(maps)
>>> mydata.final <- data.frame(county = (map('county', plot = FALSE)$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 categories
>>> ('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 do
>>> it and maybe even to add a legend?
>>> Thanks a lot!
>>>
>>> --
>>> Dimitri Liakhovitski
>>>
>>> ______________________________________________
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
>
>
> --
> Dimitri Liakhovitski
--
Dimitri Liakhovitski
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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