Simon Kiss
2014-Jul-25 19:34 UTC
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