> bindata <- 1:5 > nobs <- c(2, 3, 1, 4, 3) > rep(bindata, times=nobs) [1] 1 1 2 2 2 3 4 4 4 4 5 5 5
for the R part, and see below: Sarah On Tue, Dec 20, 2011 at 5:45 PM, kbrownk <kbro...@gmail.com> wrote: > I need to measure kurtosis, skew, and maybe dip test on some > distributions I have. Currently my data is in the form of 2 vectors x > and y. Where x is 10 bins and y is the number of observations found in > that bin. It seems that the measures I want to run require the actual > observations laid out rather than already summed like I have them. Any > suggestions on how to transform the data automatically? I have a semi- > automated method in Excel but I think r will do a better job. I > provide a more specific example below: > > My csv file with the data looks like this: > Bin: 1,2,3, ... ,10 #Observations: 23,42,1,... 56 Really? By default R will treat everything after the # as a comment, so you'll need to watch out for the comment character option when you import it. You're also trying to use two or maybe three separate delimiters, which R can't easily handle. Why not use a proper CSV file with Comma Separated Values? > I need this transformed into a single vector like this: > c(1,1,1,1...2,2,2,2...3,...10,10,10,10...) The vector would have 23 > "1"s, 42 "2s", 1 "3", etc. > > I actually have 68 of these vectors laid out in rows that I will > measure separately, so my csv file actually looks like this: > Bin: 1,2,3, ... ,10 #Observations: 23,42,1,... 56 > Bin: 1,2,3, ... ,10 #Observations: 13,33,32,...98 > . > . > . > Bin: 1,2,3, ... ,10 #Observations: 11,76,55,...46 > > I want to automate the process. > -- Sarah Goslee http://www.functionaldiversity.org ______________________________________________ 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.
