David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Don McKenzie
Sent: Thursday, February 26, 2015 3:12 PM
To: Kate Ignatius
Cc: r-help
Subject: Re: [R] Su
Use Jeff’s solution. This doesn’t account for ties.
> On Feb 26, 2015, at 1:11 PM, Don McKenzie wrote:
>
> Kate — here is a transparent solution (tested but without NA treatment).
> Doubtless there are cleverer faster ones, which later posters will present.
>
> HTH
>
> # example with four co
Kate — here is a transparent solution (tested but without NA treatment).
Doubtless there are cleverer faster ones, which later posters will present.
HTH
# example with four columns and 20 rows
nrows <- 20
A <- sample(c(1:100), nrows, replace=T)
B <- sample(c(1:100), nrows, replace=T)
C <- sampl
I guess the answer to your question is "yes".
dta <- read.table( text=
"A B C D
0 1 0 7
0 2 0 7
0 3 0 7
0 4 0 7
0 1 0 0
0 0 0 0
0 0 0 0
0 0 0 0
0 0 1 5
0 5 1 5
0 4 1 5
0 8 4 7
0 0 3 0
0 0 3 4
0 0 3 4
0 0 0 5
0 2 0 6
0 0 4 0
0 0 4 0
0 0 4 0
", header=TRUE )
dtacmax <- sapply( dta, max )
followed b
Hi,
Supposed I had a data frame like so:
A B C D
0 1 0 7
0 2 0 7
0 3 0 7
0 4 0 7
0 1 0 0
0 0 0 0
0 0 0 0
0 0 0 0
0 0 1 5
0 5 1 5
0 4 1 5
0 8 4 7
0 0 3 0
0 0 3 4
0 0 3 4
0 0 0 5
0 2 0 6
0 0 4 0
0 0 4 0
0 0 4 0
For each row, I want to count how many max column values appear to
adventurely get the
5 matches
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