Hi Bert and thank you for your assistance, I will try this. I was not clear enough about the number of expected output columns based on the DiagnosisCode column, my appologies.
Specifically, by virtue of the ClaimServiceID being the unique identifier, among them there is one with 12 DiagnosisCodes so the record length would be at the most 12 + the ClaimServiceID and the ClaimID Example: ClaimServiceID ClaimID DX1 DX2 DX3 DX4 DX5 DX6 DX7 DX8 DX9 DX10 DX11 DX12 And of course those ClaimServiceID’s with less than 12 DX’s would be NULL in place of a DiagnosisCode I will work with what you suggest and report back thank you again Sir! WHP From: Bert Gunter [mailto:bgunter.4...@gmail.com] Sent: Friday, June 22, 2018 11:54 AM To: Bill Poling <bill.pol...@zelis.com> Cc: r-help (r-help@r-project.org) <r-help@r-project.org> Subject: Re: [R] Help with transpose please. 1. "The max number of columns based on this transpose of the DiagnosisCode column (in this dataset) is 12 if that is important to know." I count about 20 different DX codes in the data you show, so I don't know what this means. 2. I was not able to unambiguously parse your request (I admit that I just may be dense) , but maybe split() is what you want, at least to start with: ##untested in the absence of a reprex ## dat is your data frame split(dat, dat$ClaimServiceID) This will give you a list of data frames, one for eachClaimServiceID. You can order each list however you like using, e.g. lapply() with order(). If I have missed your intent completely, just say so and hopefully someone else can help. Or follow Ramesh's suggestion Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Fri, Jun 22, 2018 at 4:43 AM, Bill Poling <bill.pol...@zelis.com<mailto:bill.pol...@zelis.com>> wrote: Good morning. I have data in the form: head(Edit041IA, n=25) ClaimServiceID ClaimID DiagnosisCode 1 183056004 78044473 C562 2 183056004 78044473 C778 3 183056004 78044473 C784 4 183056004 78044473 C786 5 183056004 78044473 C7961 6 183056004 78044473 C7982 7 183056004 78044473 C7989 8 183056008 78044473 C562 9 183056008 78044473 C778 10 183056008 78044473 C784 11 183056008 78044473 C786 12 183056008 78044473 C7961 13 183056008 78044473 C7982 14 183056008 78044473 C7989 15 183139945 78078925 M79606 16 183139945 78078925 M7989 17 183139945 78078925 R600 18 183236728 78119632 H02831 19 183236728 78119632 H02832 20 183236728 78119632 H02834 21 183236728 78119632 H02835 22 183236728 78119632 H04123 23 183236728 78119632 Z411 24 183236728 78119632 H2513 25 183236728 78119632 H43813 And wish to transpose to single record for single claimServiceID, ClaimID, and Dx1,Dx2,Dx3, etc: There can be multiple claimServiceIDs for a ClaimID so I want the unique ClaimServiceID as the identifier when I join this data back into a longer single record length file by that column. claimServiceID ClaimID Dx1 Dx2 Dx3 ...etc 1 183056004 78044473 C562 C778 C784 C786 C7961 ...etc 2 183056008 78044473 C562 C778 C784 C786 C7961 ...etc (If you would prefer the complete dput of the 1272 records I will gladly provide .Names = c("ClaimServiceID", "ClaimID", "DiagnosisCode"), class = "data.frame", row.names = c(NA, -1272L)) At the moment the classes are: classes <- as.character(sapply(Edit041IA, class)) classes # [1] "integer" "integer" "character" <---but do not have to be if that helps its just that's how the csv load pulled them in The max number of columns based on this transpose of the DiagnosisCode column (in this dataset) is 12 if that is important to know. I have looked at a variety of webpages and cannot get this right, dta2 <- melt(dta1, id=c("ClaimServiceID","ClaimID")) View(dta2) # https://www.r-bloggers.com/pivot-tables-in-r/<https://www.r-bloggers.com/pivot-tables-in-r/> # https://stackoverflow.com/questions/18449938/pivot-on-data-table-similar-to-rehape-melt-function<https://stackoverflow.com/questions/18449938/pivot-on-data-table-similar-to-rehape-melt-function> dta3 <- cast(Edit041IA, ClaimServiceID ~ DiagnosisCode, ClaimID) View(dta3) dta3 <- cast(Edit041IA, DiagnosisCode ~ ClaimServiceID, ClaimID) View(dta3) dta3 <- melt(Edit041IA, id=c("ClaimServiceID")) View(dta3) dta3 <- aggregate(Edit041IA, by=list(ClaimServiceID, ClaimID, DiagnosisCode)) View(dta3) dta3 <- aggregate(Edit041IA, by=list(ClaimServiceID)) View(dta3) # https://www.r-statistics.com/tag/transpose/<https://www.r-statistics.com/tag/transpose/> dta3 <- aggregate(Edit041IA, by=list(DiagnosisCode, ClaimServiceID, ClaimID)) View(dta3) I am sure it's a basic, simple procedure, but I am pressed for time on this one, any support will be greatly appreciated, thank you. 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