Right, but he just wanted to eliminate "BLUE" as far as I could see.
Your solution does more, of course.
On 21-Aug-09, at 3:33 PM, David Winsemius wrote:
On Aug 21, 2009, at 6:16 PM, Don McKenzie wrote:
dataset[dataset$Color != "BLUE",]
Will return a data.frame with Color still a factor with three levels.
On 21-Aug-09, at 3:08 PM, jlwoodard wrote:
I have a data set similar to the following:
Color Score
RED 10
RED 13
RED 12
WHITE 22
WHITE 27
WHITE 25
BLUE 18
BLUE 17
BLUE 16
and I am trying to to select just the values of Color that are
equal to RED
or WHITE, excluding the BLUE.
I've tried the following:
myComp1<-subset(dataset, Color =="RED" | Color == "WHITE")
myComp1<-subset(dataset, Color != "BLUE")
myComp1<-dataset[which(dataset$Color != "BLUE"),]
Each of the above lines successfully excludes the BLUE subjects,
but the
"BLUE" category is still present in my data set; that is, if I try
table(Color) I get
RED WHITE BLUE
82 151 0
If I try to do a t-test (since I've presumably gone from three
groups to two
groups), I get:
Error in if (stderr < 10 * .Machine$double.eps * max(abs(mx), abs
(my)))
stop("data are essentially constant") :
missing value where TRUE/FALSE needed
In addition: Warning message:
In mean.default(y) : argument is not numeric or logical:
returning NA
and describe.by(score,Color) gives me descriptives for RED and
WHITE, and
BLUE also shows up as NULL.
How can I eliminate the BLUE category completely so I can do a t-
test using
Color (with just the RED and WHITE subjects)?
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
Don McKenzie, Research Ecologist
Pacific WIldland Fire Sciences Lab
US Forest Service
Affiliate Professor
School of Forest Resources, College of the Environment
CSES Climate Impacts Group
University of Washington
desk: 206-732-7824
cell: 206-321-5966
d...@u.washington.edu
donaldmcken...@fs.fed.us
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