If you want colors mapped to the _values_ in DF1$C, there are a number
of ways to do it:
Color_unq<-color.scale(DF1$C,c(1,0),c(0,0,c(0,1))
This will produce colors from the lowest values (red) through the
highest (blue). See the help page for color.scale to get different
colors. With this you can
values A and B have different ranges. Therefore you would want
horizontal error bars for the B mean. The dispersion function doesn't
do horizontal error bars, so you can use plotCI also in plotrix. Here
is an example with two databases:
DF2<-read.table(text="A B C
62 22 54
69 24 55
Thanks, Jim. The code works, but I don't understand why you use q1090 <-
quantile(DF1$B, probs=c()), rather than DF1$A? Also, how to add a legend
for both points DF1 and DF2?
On Wed, Jul 12, 2017 at 8:25 PM, Jim Lemon wrote:
> Hi lily,
> Here is the first plot:
>
> plot(DF1$A,DF1$B,pch=19,col="r
Hi lily,
Here is the first plot:
plot(DF1$A,DF1$B,pch=19,col="red")
meanA<-mean(DF1$A)
meanB<-mean(DF1$B)
points(meanA,meanB,pch=18,col="red")
q1090<-quantile(DF1$B,probs=c(0.1,0.9))
library(plotrix)
dispersion(meanA,meanB,q1090[2],q1090[1],
intervals=FALSE,col="red")
The same code will work for
Hi R users,
I have a question about plotting. There is the dataframe below, while each
row represents a record. If I want to plot on a A-B plot, i.e., x-axis
represents A, while y-axis represents B values. However, I want to plot the
mean value from records 1-10 as one point, while the 10th and 90
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