Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
HI, of course. The a mini-version of my data-set is below, stored in d2. Then the code I'm working follows. library(reshape2) #Create d2 structure(list(row = 1:50, rank1 = structure(c(3L, 3L, 3L, 4L, 3L, 3L, NA, NA, 3L, NA, 3L, 3L, 1L, NA, 2L, NA, 3L, NA, 2L, 1L, 1L, 3L, NA, 6L, NA, 1L, NA, 3L, 1L, NA, 1L, NA, NA, 6L, 3L, NA, 1L, 3L, 3L, 4L, 1L, NA, 3L, 3L, 3L, NA, 3L, 3L, NA, 1L), .Label = c(accessible, alternatives, information, responsive, social, technical, trade), class = factor), rank2 = structure(c(6L, 1L, 1L, 2L, 4L, 6L, NA, NA, 6L, NA, 6L, 4L, 2L, NA, 4L, NA, 6L, NA, 1L, 6L, 3L, 2L, NA, 3L, NA, 6L, NA, 6L, 6L, NA, 3L, NA, NA, 3L, 6L, NA, 6L, 6L, 6L, 7L, 3L, NA, 1L, 6L, 6L, NA, 2L, 6L, NA, 2L), .Label = c(accessible, alternatives, information, responsive, social, technical, trade), class = factor), rank3 = structure(c(1L, 6L, 4L, 3L, 2L, 4L, NA, NA, 4L, NA, 1L, 1L, 6L, NA, 1L, NA, 1L, NA, 7L, 3L, 6L, 1L, NA, 2L, NA, 4L, NA, 1L, 3L, NA, 6L, NA, NA, 4L, 2L, NA, 7L, 1L, 1L, 6L, 7L, NA, 6L, 1L, 1L, NA, 4L, 1L, NA, 3L), .Label = c(accessible, alternatives, information, responsive, social, technical, trade), class = factor), rank4 = structure(c(7L, 4L, 2L, 1L, 1L, 7L, NA, NA, 1L, NA, 7L, 2L, 7L, NA, 3L, NA, 2L, NA, 3L, 4L, 5L, 6L, NA, 4L, NA, 3L, NA, 4L, 4L, NA, 4L, NA, NA, 2L, 7L, NA, 2L, 2L, 2L, 3L, 6L, NA, 2L, 5L, 4L, NA, 1L, 2L, NA, 4L), .Label = c(accessible, alternatives, information, responsive, social, technical, trade), class = factor), rank5 = structure(c(2L, 7L, 6L, 7L, 7L, 2L, NA, NA, 2L, NA, 2L, 7L, 3L, NA, 6L, NA, 7L, NA, 6L, 7L, 4L, 7L, NA, 7L, NA, 7L, NA, 2L, 2L, NA, 2L, NA, NA, 7L, 1L, NA, 3L, 7L, 4L, 2L, 2L, NA, 4L, 2L, 2L, NA, 6L, 4L, NA, 5L), .Label = c(accessible, alternatives, information, responsive, social, technical, trade), class = factor), rank6 = structure(c(4L, 2L, 7L, 6L, 6L, 1L, NA, NA, 7L, NA, 4L, 5L, 4L, NA, 7L, NA, 4L, NA, 4L, 2L, 2L, 4L, NA, 1L, NA, 2L, NA, 7L, 7L, NA, 7L, NA, NA, 1L, 4L, NA, 4L, 4L, 7L, 1L, 4L, NA, 7L, 7L, 7L, NA, 7L, 7L, NA, 7L), .Label = c(accessible, alternatives, information, responsive, social, technical, trade), class = factor), rank7 = structure(c(5L, 5L, 5L, 5L, 5L, 5L, NA, NA, 5L, NA, 5L, 6L, 5L, NA, 5L, NA, 5L, NA, 5L, 5L, 7L, 5L, NA, 5L, NA, 5L, NA, 5L, 5L, NA, 5L, NA, NA, 5L, 5L, NA, 5L, NA, 5L, 5L, 5L, NA, 5L, 4L, 5L, NA, 5L, 5L, NA, 6L), .Label = c(accessible, alternatives, information, responsive, social, technical, trade), class = factor)), .Names = c(row, rank1, rank2, rank3, rank4, rank5, rank6, rank7), row.names = c(NA, 50L), class = data.frame) #This code is a replication of David Carlson's code (below) which works splendidly, but does not work on my data-set #Melt d2: Note, I've used value.name='color' to maximize comparability with David's suggestion d3 - melt(d2, id.vars=1, measure.vars=2:8, variable.name=rank,value.name=color) #Make Rank Variable Numeric d3$rank-as.numeric(d3$rank) #Recast d3 into d4 d4- dcast(d3, row~color,value.var=rank, fill=0) #Note that d4 appears to provide a binary variable for one if a respondent checked the option, but does not provide information as to which rank they assigned each option, but also seems to summarize the number of missing values #David Carlson's Code mydf - data.frame(t(replicate(100, sample(c(red, blue, green, yellow, NA), 4 mydf - data.frame(rows=1:100, mydf) colnames(mydf) - c(row, rank1, rank2, rank3, rank4) mymelt - melt(mydf, id.vars=1, measure.vars=2:5, variable.name=rank, value.name=color) mymelt$rank - as.numeric(mymelt$rank) mycast - dcast(mymelt, row~color, value.var=rank, fill=0) #Compare str(mydf) str(d2) head(mycast) head(d4) Again, I'm grateful for assistance. I can't understand what how my data-set differs from David's sample data-set. Simon Kiss On Sep 4, 2014, at 2:35 PM, David L Carlson dcarl...@tamu.edu wrote: I think we would need enough of the data you are using to figure out how to modify the process. Can you use dput() to send a small data set that fails to work? David C -Original Message- From: Simon Kiss [mailto:sjk...@gmail.com] Sent: Thursday, September 4, 2014 1:28 PM To: David L Carlson Cc: r-help@r-project.org Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame Hi David and list: This is working, except at this command mycast - dcast(mymelt, row~color, value.var=rank, fill=0) dcast is using length as the default aggregating function. This results in not accurate results. It tells me, for example how many choices were missing values and it tells me if a person selected any given option (value is reported as 1). When I try to run your reproducible research, it works great, but something with the aggregating function is not working properly with mine. Any other thoughts? Simon On Aug 18, 2014, at 10:44 AM, David L Carlson dcarl...@tamu.edu wrote: Another approach using reshape2: library(reshape2) #
Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
The big difference between the data sets is that many of your rows (16) have
all missing values. None of mine do. If you run my data and yours, you will see
that decast throws a warning Aggregation function missing: defaulting to
length with your data but not with mine. As a result, instead of using the
value of rank, dcast uses length(rank) which is always 1 except when there are
multiple missing values when it is the number of missing values. This problem
will occur whenever there is more than one missing value on a row. The simplest
way to handle this is to create a function that returns the first value of a
vector and use that with the fun.aggregate= argument:
first - function(x) {x[1]}
d4- dcast(d3, row~color, fun.aggregate=first, value.var=rank, fill=0)
The only drawback is that this will not warn you if a category was ranked twice
except that the NA column will be zero and one of the other columns will be
zero. The number of missing values is the number of zeroes in your category
columns (not including row or NA) and the value in NA is the lowest rank that
was missing.
David C
-Original Message-
From: Simon Kiss [mailto:sjk...@gmail.com]
Sent: Friday, September 5, 2014 10:22 AM
To: David L Carlson
Cc: r-help@r-project.org
Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data
Frame
HI, of course.
The a mini-version of my data-set is below, stored in d2. Then the code I'm
working follows.
library(reshape2)
#Create d2
structure(list(row = 1:50, rank1 = structure(c(3L, 3L, 3L, 4L,
3L, 3L, NA, NA, 3L, NA, 3L, 3L, 1L, NA, 2L, NA, 3L, NA, 2L, 1L,
1L, 3L, NA, 6L, NA, 1L, NA, 3L, 1L, NA, 1L, NA, NA, 6L, 3L, NA,
1L, 3L, 3L, 4L, 1L, NA, 3L, 3L, 3L, NA, 3L, 3L, NA, 1L), .Label =
c(accessible,
alternatives, information, responsive, social, technical,
trade), class = factor), rank2 = structure(c(6L, 1L, 1L,
2L, 4L, 6L, NA, NA, 6L, NA, 6L, 4L, 2L, NA, 4L, NA, 6L, NA, 1L,
6L, 3L, 2L, NA, 3L, NA, 6L, NA, 6L, 6L, NA, 3L, NA, NA, 3L, 6L,
NA, 6L, 6L, 6L, 7L, 3L, NA, 1L, 6L, 6L, NA, 2L, 6L, NA, 2L), .Label =
c(accessible,
alternatives, information, responsive, social, technical,
trade), class = factor), rank3 = structure(c(1L, 6L, 4L,
3L, 2L, 4L, NA, NA, 4L, NA, 1L, 1L, 6L, NA, 1L, NA, 1L, NA, 7L,
3L, 6L, 1L, NA, 2L, NA, 4L, NA, 1L, 3L, NA, 6L, NA, NA, 4L, 2L,
NA, 7L, 1L, 1L, 6L, 7L, NA, 6L, 1L, 1L, NA, 4L, 1L, NA, 3L), .Label =
c(accessible,
alternatives, information, responsive, social, technical,
trade), class = factor), rank4 = structure(c(7L, 4L, 2L,
1L, 1L, 7L, NA, NA, 1L, NA, 7L, 2L, 7L, NA, 3L, NA, 2L, NA, 3L,
4L, 5L, 6L, NA, 4L, NA, 3L, NA, 4L, 4L, NA, 4L, NA, NA, 2L, 7L,
NA, 2L, 2L, 2L, 3L, 6L, NA, 2L, 5L, 4L, NA, 1L, 2L, NA, 4L), .Label =
c(accessible,
alternatives, information, responsive, social, technical,
trade), class = factor), rank5 = structure(c(2L, 7L, 6L,
7L, 7L, 2L, NA, NA, 2L, NA, 2L, 7L, 3L, NA, 6L, NA, 7L, NA, 6L,
7L, 4L, 7L, NA, 7L, NA, 7L, NA, 2L, 2L, NA, 2L, NA, NA, 7L, 1L,
NA, 3L, 7L, 4L, 2L, 2L, NA, 4L, 2L, 2L, NA, 6L, 4L, NA, 5L), .Label =
c(accessible,
alternatives, information, responsive, social, technical,
trade), class = factor), rank6 = structure(c(4L, 2L, 7L,
6L, 6L, 1L, NA, NA, 7L, NA, 4L, 5L, 4L, NA, 7L, NA, 4L, NA, 4L,
2L, 2L, 4L, NA, 1L, NA, 2L, NA, 7L, 7L, NA, 7L, NA, NA, 1L, 4L,
NA, 4L, 4L, 7L, 1L, 4L, NA, 7L, 7L, 7L, NA, 7L, 7L, NA, 7L), .Label =
c(accessible,
alternatives, information, responsive, social, technical,
trade), class = factor), rank7 = structure(c(5L, 5L, 5L,
5L, 5L, 5L, NA, NA, 5L, NA, 5L, 6L, 5L, NA, 5L, NA, 5L, NA, 5L,
5L, 7L, 5L, NA, 5L, NA, 5L, NA, 5L, 5L, NA, 5L, NA, NA, 5L, 5L,
NA, 5L, NA, 5L, 5L, 5L, NA, 5L, 4L, 5L, NA, 5L, 5L, NA, 6L), .Label =
c(accessible,
alternatives, information, responsive, social, technical,
trade), class = factor)), .Names = c(row, rank1, rank2,
rank3, rank4, rank5, rank6, rank7), row.names = c(NA,
50L), class = data.frame)
#This code is a replication of David Carlson's code (below) which works
splendidly, but does not work on my data-set
#Melt d2: Note, I've used value.name='color' to maximize comparability with
David's suggestion
d3 - melt(d2, id.vars=1, measure.vars=2:8,
variable.name=rank,value.name=color)
#Make Rank Variable Numeric
d3$rank-as.numeric(d3$rank)
#Recast d3 into d4
d4- dcast(d3, row~color,value.var=rank, fill=0)
#Note that d4 appears to provide a binary variable for one if a respondent
checked the option, but does not provide information as to which rank they
assigned each option, but also seems to summarize the number of missing values
#David Carlson's Code
mydf - data.frame(t(replicate(100, sample(c(red, blue, green, yellow,
NA), 4
mydf - data.frame(rows=1:100, mydf)
colnames(mydf) - c(row, rank1, rank2, rank3, rank4)
mymelt - melt(mydf, id.vars=1, measure.vars=2:5, variable.name=rank,
value.name=color)
mymelt$rank - as.numeric(mymelt$rank)
mycast - dcast(mymelt, row~color, value.var=rank,
Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
Hi David and list: This is working, except at this command mycast - dcast(mymelt, row~color, value.var=rank, fill=0) dcast is using length as the default aggregating function. This results in not accurate results. It tells me, for example how many choices were missing values and it tells me if a person selected any given option (value is reported as 1). When I try to run your reproducible research, it works great, but something with the aggregating function is not working properly with mine. Any other thoughts? Simon On Aug 18, 2014, at 10:44 AM, David L Carlson dcarl...@tamu.edu wrote: Another approach using reshape2: library(reshape2) # Construct data/ add column of row numbers set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow, NA), 4 mydf - data.frame(rows=1:100, mydf) colnames(mydf) - c(row, rank1, rank2, rank3, rank4) head(mydf) row rank1 rank2 rank3 rank4 1 1 NA yellowred blue 2 2 yellow green NA red 3 3 yellow green blue NA 4 4 NA blue yellow green 5 5 NAred blue green 6 6 NAred green blue # Reshape mymelt - melt(mydf, id.vars=1, measure.vars=2:5, + variable.name=rank, value.name=color) # Convert rank to numeric mymelt$rank - as.numeric(mymelt$rank) mycast - dcast(mymelt, row~color, value.var=rank, fill=0) head(mycast) row blue green red yellow NA 1 14 0 3 2 1 2 20 2 4 1 3 3 33 2 0 1 4 4 42 4 0 3 1 5 53 4 2 0 1 6 64 3 2 0 1 David C -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of David L Carlson Sent: Sunday, August 17, 2014 6:32 PM To: Simon Kiss; r-help@r-project.org Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame There is probably an easier way to do this, but set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow, NA), 4 colnames(mydf) - c(rank1, rank2, rank3, rank4) head(mydf) rank1 rank2 rank3 rank4 1 NA yellowred blue 2 yellow green NA red 3 yellow green blue NA 4 NA blue yellow green 5 NAred blue green 6 NAred green blue 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$ind) # add row numbers mydf2 - data.frame(rows=1:100, mydf2) # Create table mytbl - xtabs(ind~rows+values, mydf2) # convert to data frame mydf3 - data.frame(unclass(mytbl)) colnames(mydf3) - lvls head(mydf3) blue green red yellow 14 0 3 2 20 2 4 1 33 2 0 1 42 4 0 3 53 4 2 0 64 3 2 0 David C -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Simon Kiss Sent: Friday, August 15, 2014 3:58 PM To: r-help@r-project.org Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame Both the suggestions I got work very well, but what I didn't realize is that NA values would cause serious problems. Where there is a missing value, using the argument na.last=NA to order just returns the the order of the factor levels, but excludes the missing values, but I have no idea where those occur in the or rather which of those variables were actually missing. Have I explained this problem sufficiently? I didn't think it would cause such a problem so I didn't include it in the original problem definition. Yours, Simon On Jul 25, 2014, at 4:58 PM, David L Carlson dcarl...@tamu.edu wrote: I think this gets what you want. But your data are not reproducible since they are randomly drawn without setting a seed and the two data sets have no relationship to one another. set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow) colnames(mydf) - c(rank1, rank2, rank3, rank4) mydf2 - data.frame(t(apply(mydf, 1, order))) colnames(mydf2) - levels(mydf$rank1) head(mydf) rank1 rank2 rank3 rank4 1 yellow greenred blue 2 green blue yellow red 3 green yellowred blue 4 yellowred green blue 5 yellowred green blue 6 yellowred blue green head(mydf2) blue green red yellow 14 2 3 1 22 1 4 3 34 1 3 2 44 3 2 1 54 3 2 1 63 4 2 1 - David L Carlson Department of Anthropology Texas AM University College Station, TX 77840-4352 -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Simon Kiss Sent: Friday, July 25, 2014 2:34 PM To:
Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
I think we would need enough of the data you are using to figure out how to modify the process. Can you use dput() to send a small data set that fails to work? David C -Original Message- From: Simon Kiss [mailto:sjk...@gmail.com] Sent: Thursday, September 4, 2014 1:28 PM To: David L Carlson Cc: r-help@r-project.org Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame Hi David and list: This is working, except at this command mycast - dcast(mymelt, row~color, value.var=rank, fill=0) dcast is using length as the default aggregating function. This results in not accurate results. It tells me, for example how many choices were missing values and it tells me if a person selected any given option (value is reported as 1). When I try to run your reproducible research, it works great, but something with the aggregating function is not working properly with mine. Any other thoughts? Simon On Aug 18, 2014, at 10:44 AM, David L Carlson dcarl...@tamu.edu wrote: Another approach using reshape2: library(reshape2) # Construct data/ add column of row numbers set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow, NA), 4 mydf - data.frame(rows=1:100, mydf) colnames(mydf) - c(row, rank1, rank2, rank3, rank4) head(mydf) row rank1 rank2 rank3 rank4 1 1 NA yellowred blue 2 2 yellow green NA red 3 3 yellow green blue NA 4 4 NA blue yellow green 5 5 NAred blue green 6 6 NAred green blue # Reshape mymelt - melt(mydf, id.vars=1, measure.vars=2:5, + variable.name=rank, value.name=color) # Convert rank to numeric mymelt$rank - as.numeric(mymelt$rank) mycast - dcast(mymelt, row~color, value.var=rank, fill=0) head(mycast) row blue green red yellow NA 1 14 0 3 2 1 2 20 2 4 1 3 3 33 2 0 1 4 4 42 4 0 3 1 5 53 4 2 0 1 6 64 3 2 0 1 David C -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of David L Carlson Sent: Sunday, August 17, 2014 6:32 PM To: Simon Kiss; r-help@r-project.org Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame There is probably an easier way to do this, but set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow, NA), 4 colnames(mydf) - c(rank1, rank2, rank3, rank4) head(mydf) rank1 rank2 rank3 rank4 1 NA yellowred blue 2 yellow green NA red 3 yellow green blue NA 4 NA blue yellow green 5 NAred blue green 6 NAred green blue 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$ind) # add row numbers mydf2 - data.frame(rows=1:100, mydf2) # Create table mytbl - xtabs(ind~rows+values, mydf2) # convert to data frame mydf3 - data.frame(unclass(mytbl)) colnames(mydf3) - lvls head(mydf3) blue green red yellow 14 0 3 2 20 2 4 1 33 2 0 1 42 4 0 3 53 4 2 0 64 3 2 0 David C -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Simon Kiss Sent: Friday, August 15, 2014 3:58 PM To: r-help@r-project.org Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame Both the suggestions I got work very well, but what I didn't realize is that NA values would cause serious problems. Where there is a missing value, using the argument na.last=NA to order just returns the the order of the factor levels, but excludes the missing values, but I have no idea where those occur in the or rather which of those variables were actually missing. Have I explained this problem sufficiently? I didn't think it would cause such a problem so I didn't include it in the original problem definition. Yours, Simon On Jul 25, 2014, at 4:58 PM, David L Carlson dcarl...@tamu.edu wrote: I think this gets what you want. But your data are not reproducible since they are randomly drawn without setting a seed and the two data sets have no relationship to one another. set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow) colnames(mydf) - c(rank1, rank2, rank3, rank4) mydf2 - data.frame(t(apply(mydf, 1, order))) colnames(mydf2) - levels(mydf$rank1) head(mydf) rank1 rank2 rank3 rank4 1 yellow greenred blue 2 green blue yellow red 3 green yellowred blue 4 yellowred green blue 5 yellowred green blue 6 yellowred blue green head(mydf2) blue green red yellow 14 2 3 1 22 1 4 3
Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
Another approach using reshape2: library(reshape2) # Construct data/ add column of row numbers set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow, NA), 4 mydf - data.frame(rows=1:100, mydf) colnames(mydf) - c(row, rank1, rank2, rank3, rank4) head(mydf) row rank1 rank2 rank3 rank4 1 1 NA yellowred blue 2 2 yellow green NA red 3 3 yellow green blue NA 4 4 NA blue yellow green 5 5 NAred blue green 6 6 NAred green blue # Reshape mymelt - melt(mydf, id.vars=1, measure.vars=2:5, + variable.name=rank, value.name=color) # Convert rank to numeric mymelt$rank - as.numeric(mymelt$rank) mycast - dcast(mymelt, row~color, value.var=rank, fill=0) head(mycast) row blue green red yellow NA 1 14 0 3 2 1 2 20 2 4 1 3 3 33 2 0 1 4 4 42 4 0 3 1 5 53 4 2 0 1 6 64 3 2 0 1 David C -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of David L Carlson Sent: Sunday, August 17, 2014 6:32 PM To: Simon Kiss; r-help@r-project.org Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame There is probably an easier way to do this, but set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow, NA), 4 colnames(mydf) - c(rank1, rank2, rank3, rank4) head(mydf) rank1 rank2 rank3 rank4 1 NA yellowred blue 2 yellow green NA red 3 yellow green blue NA 4 NA blue yellow green 5 NAred blue green 6 NAred green blue 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$ind) # add row numbers mydf2 - data.frame(rows=1:100, mydf2) # Create table mytbl - xtabs(ind~rows+values, mydf2) # convert to data frame mydf3 - data.frame(unclass(mytbl)) colnames(mydf3) - lvls head(mydf3) blue green red yellow 14 0 3 2 20 2 4 1 33 2 0 1 42 4 0 3 53 4 2 0 64 3 2 0 David C -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Simon Kiss Sent: Friday, August 15, 2014 3:58 PM To: r-help@r-project.org Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame Both the suggestions I got work very well, but what I didn't realize is that NA values would cause serious problems. Where there is a missing value, using the argument na.last=NA to order just returns the the order of the factor levels, but excludes the missing values, but I have no idea where those occur in the or rather which of those variables were actually missing. Have I explained this problem sufficiently? I didn't think it would cause such a problem so I didn't include it in the original problem definition. Yours, Simon On Jul 25, 2014, at 4:58 PM, David L Carlson dcarl...@tamu.edu wrote: I think this gets what you want. But your data are not reproducible since they are randomly drawn without setting a seed and the two data sets have no relationship to one another. set.seed(42) mydf - data.frame(t(replicate(100, sample(c(red, blue, + green, yellow) colnames(mydf) - c(rank1, rank2, rank3, rank4) mydf2 - data.frame(t(apply(mydf, 1, order))) colnames(mydf2) - levels(mydf$rank1) head(mydf) rank1 rank2 rank3 rank4 1 yellow greenred blue 2 green blue yellow red 3 green yellowred blue 4 yellowred green blue 5 yellowred green blue 6 yellowred blue green head(mydf2) blue green red yellow 14 2 3 1 22 1 4 3 34 1 3 2 44 3 2 1 54 3 2 1 63 4 2 1 - David L Carlson Department of Anthropology Texas AM University College Station, TX 77840-4352 -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Simon Kiss Sent: Friday, July 25, 2014 2:34 PM To: r-help@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
Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
There is probably an easier way to do this, but
set.seed(42)
mydf - data.frame(t(replicate(100, sample(c(red, blue,
+ green, yellow, NA), 4
colnames(mydf) - c(rank1, rank2, rank3, rank4)
head(mydf)
rank1 rank2 rank3 rank4
1 NA yellowred blue
2 yellow green NA red
3 yellow green blue NA
4 NA blue yellow green
5 NAred blue green
6 NAred green blue
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$ind)
# add row numbers
mydf2 - data.frame(rows=1:100, mydf2)
# Create table
mytbl - xtabs(ind~rows+values, mydf2)
# convert to data frame
mydf3 - data.frame(unclass(mytbl))
colnames(mydf3) - lvls
head(mydf3)
blue green red yellow
14 0 3 2
20 2 4 1
33 2 0 1
42 4 0 3
53 4 2 0
64 3 2 0
David C
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Simon Kiss
Sent: Friday, August 15, 2014 3:58 PM
To: r-help@r-project.org
Subject: Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data
Frame
Both the suggestions I got work very well, but what I didn't realize is that NA
values would cause serious problems. Where there is a missing value, using the
argument na.last=NA to order just returns the the order of the factor levels,
but excludes the missing values, but I have no idea where those occur in the or
rather which of those variables were actually missing.
Have I explained this problem sufficiently?
I didn't think it would cause such a problem so I didn't include it in the
original problem definition.
Yours, Simon
On Jul 25, 2014, at 4:58 PM, David L Carlson dcarl...@tamu.edu wrote:
I think this gets what you want. But your data are not reproducible since
they are randomly drawn without setting a seed and the two data sets have no
relationship to one another.
set.seed(42)
mydf - data.frame(t(replicate(100, sample(c(red, blue,
+ green, yellow)
colnames(mydf) - c(rank1, rank2, rank3, rank4)
mydf2 - data.frame(t(apply(mydf, 1, order)))
colnames(mydf2) - levels(mydf$rank1)
head(mydf)
rank1 rank2 rank3 rank4
1 yellow greenred blue
2 green blue yellow red
3 green yellowred blue
4 yellowred green blue
5 yellowred green blue
6 yellowred blue green
head(mydf2)
blue green red yellow
14 2 3 1
22 1 4 3
34 1 3 2
44 3 2 1
54 3 2 1
63 4 2 1
-
David L Carlson
Department of Anthropology
Texas AM University
College Station, TX 77840-4352
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Simon Kiss
Sent: Friday, July 25, 2014 2:34 PM
To: r-help@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@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
Re: [R] 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 dcarl...@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 greenred blue
2 green blue yellow red
3 green yellowred blue
4 yellowred green blue
5 yellowred green blue
6 yellowred blue green
head(mydf2)
blue green red yellow
14 2 3 1
22 1 4 3
34 1 3 2
44 3 2 1
54 3 2 1
63 4 2 1
-
David L Carlson
Department of Anthropology
Texas AM University
College Station, TX 77840-4352
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Simon Kiss
Sent: Friday, July 25, 2014 2:34 PM
To: r-help@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@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
__
R-help@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.
Re: [R] Turn Rank Ordering Into Numerical Scores By Transposing A Data Frame
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 greenred blue
2 green blue yellow red
3 green yellowred blue
4 yellowred green blue
5 yellowred green blue
6 yellowred blue green
head(mydf2)
blue green red yellow
14 2 3 1
22 1 4 3
34 1 3 2
44 3 2 1
54 3 2 1
63 4 2 1
-
David L Carlson
Department of Anthropology
Texas AM University
College Station, TX 77840-4352
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Simon Kiss
Sent: Friday, July 25, 2014 2:34 PM
To: r-help@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@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.
__
R-help@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.
