Scatterplot with the 3rd dimension = color?
Can someone please help me out with this? The ggplot2 suggestion works great but I've spent a few days trying to figure out how to plot 2 variables with it and I'm stuck. Here's my example code: library(ggplot2) #Here's the 1st plot x<-rnorm(100) y<-rnorm(100) z<-rnorm(100) d <- data.frame(x,y,z) dg<-qplot(x,y,colour=z,data=d) dg + scale_colour_gradient(low="red", high="blue") #Here's the 2nd plot which will delete the 1st plot above but I'd like them to be plotted together x1<-rnorm(100) y2<-rnorm(100) z3<-rnorm(100) d1 <- data.frame(x1,y1,z1) dg1 <-qplot(x1,y1,colour=z1,data=d1) dg1 + scale_colour_gradient(low="green", high="yellow") I've been trying to get long format working but it just doesn't make any sense to me. Thanks, kb
On Oct 17, 3:10?pm, Kerry <kbro... at gmail.com> wrote:
Yes, the qplot works great, but do you know how to allow for multiple plots? I want one variable to be plotted say from blue to red and another say from yellow to green but in the same graph, each having there own separate legends. I've tried print() and arrange() but no luck. Thanks again, kb On Oct 2, 10:42?pm, Ben Bolker <bbol... at gmail.com> wrote:
Duncan Murdoch <murdoch.duncan <at> gmail.com> writes:
On 11-10-02 1:11 PM, Kerry wrote:
I have 3 columns of data and want to plot each row as a point in a scatter plot and want one column to be represented as a color gradient (e.g. larger ?values being more red). Anyone know the command or package for this?
It's not a particularly effective display, but here's how to do it. ?Use rainbow(101) in place of rev(heat.colors(101)) if you like.
x <- rnorm(10) y <- rnorm(10) z <- rnorm(10) colors <- rev(heat.colors(101)) zcolor <- colors[(z - min(z))/diff(range(z))*100 + 1] plot(x,y,col=zcolor)
? or
d <- data.frame(x,y,z) library(ggplot2) qplot(x,y,colour=z,data=d)
? I agree about the "not particularly effective display" comment, but if you have two continuous predictors and a continuous response you've got a tough display problem -- your choices are:
? 1. use color, size, or some other graphical characteristic (pretty far down on the "Cleveland hierarchy") ? 2. use a perspective plot (hard to get the right viewing angle, often confusing) ? 3. use coplots/small multiples/faceting (requires discretizing one dimension)
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______________________________________________ R-h... at r-project.org mailing listhttps://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.