Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
Both the suggestions I got work very well, but what I didn't realize is that NA values would cause serious problems. Where there is a missing value, using the argument na.last=NA to order just returns the the order of the factor levels, but excludes the missing values, but I have no idea where those occur in the or rather which of those variables were actually missing. Have I explained this problem sufficiently? I didn't think it would cause such a problem so I didn't include it in the original problem definition. Yours, Simon
On Jul 25, 2014, at 4:58 PM, David L Carlson <dcarlson at tamu.edu> wrote:
I think this gets what you want. But your data are not reproducible since they are randomly drawn without setting a seed and the two data sets have no relationship to one another.
set.seed(42)
mydf <- data.frame(t(replicate(100, sample(c("red", "blue",
+ "green", "yellow")))))
colnames(mydf) <- c("rank1", "rank2", "rank3", "rank4")
mydf2 <- data.frame(t(apply(mydf, 1, order)))
colnames(mydf2) <- levels(mydf$rank1)
head(mydf)
rank1 rank2 rank3 rank4 1 yellow green red blue 2 green blue yellow red 3 green yellow red blue 4 yellow red green blue 5 yellow red green blue 6 yellow red blue green
head(mydf2)
blue green red yellow
1 4 2 3 1
2 2 1 4 3
3 4 1 3 2
4 4 3 2 1
5 4 3 2 1
6 3 4 2 1
-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Simon Kiss
Sent: Friday, July 25, 2014 2:34 PM
To: r-help at r-project.org
Subject: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
Hello:
I have data that looks like mydf, below. It is the results of a survey where participants were to put a number of statements (in this case colours) in their order of preference. In this case, the rank number is the variable, and the factor level for each respondent is which colour they assigned to that rank. I would like to find a way to effectively transpose the data frame so that it looks like mydf2, also below, where the colours the participants were able to choose are the variables and the variable score is what that person ranked that variable.
Ultimately what I would like to do is a factor analysis on these items, so I'd like to be able to see if people ranked red and yellow higher together but ranked green and blue together lower, that sort of thing.
I have played around with different variations of t(), melt(), ifelse() and if() but can't find a solution.
Thank you
Simon
#Reproducible code
mydf<-data.frame(rank1=sample(c('red', 'blue', 'green', 'yellow'), replace=TRUE, size=100), rank2=sample(c('red', 'blue', 'green', 'yellow'), replace=TRUE, size=100), rank3=sample(c('red', 'blue', 'green', 'yellow'), replace=TRUE, size=100), rank4=sample(c('red', 'blue', 'green', 'yellow'), replace=TRUE, size=100))
mydf2<-data.frame(red=sample(c(1,2,3,4), replace=TRUE,size=100),blue=sample(c(1,2,3,4), replace=TRUE,size=100),green=sample(c(1,2,3,4), replace=TRUE,size=100) ,yellow=sample(c(1,2,3,4), replace=TRUE,size=100))
*********************************
Simon J. Kiss, PhD
Assistant Professor, Wilfrid Laurier University
73 George Street
Brantford, Ontario, Canada
N3T 2C9
______________________________________________ R-help at r-project.org mailing list 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.
********************************* Simon J. Kiss, PhD Assistant Professor, Wilfrid Laurier University 73 George Street Brantford, Ontario, Canada N3T 2C9 Cell: +1 905 746 7606