Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame

library(reshape2)
# Construct data/ add column of row numbers
set.seed(42)
mydf <- data.frame(t(replicate(100, sample(c("red", "blue",

mydf <- data.frame(rows=1:100, mydf)
colnames(mydf) <- c("row", "rank1", "rank2", "rank3", "rank4")
head(mydf)

# Reshape
mymelt <- melt(mydf, id.vars=1, measure.vars=2:5, 

# Convert rank to numeric
mymelt$rank <- as.numeric(mymelt$rank)
mycast <- dcast(mymelt, row~color, value.var="rank", fill=0)
head(mycast)

set.seed(42)
mydf <- data.frame(t(replicate(100, sample(c("red", "blue",

colnames(mydf) <- c("rank1", "rank2", "rank3", "rank4")
head(mydf)

lvls <- levels(mydf$rank1)
# convert color factors to numeric
for (i in seq_along(mydf)) mydf[,i] <- as.numeric(mydf[,i]) 
# stack the columns
mydf2 <- stack(mydf)
# convert rank factor to numeric
mydf2$ind <- as.numeric(mydf2$ind)
# add row numbers
mydf2 <- data.frame(rows=1:100, mydf2)
# Create table
mytbl <- xtabs(ind~rows+values, mydf2)
# convert to data frame
mydf3 <- data.frame(unclass(mytbl))
colnames(mydf3) <- lvls
head(mydf3)

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