Hi, You could also use ?dcast() occ.data1<-occ.data[,-c(2:3)] library(reshape2) res1<-dcast(occ.data1,year+Site+specie+Pres~Rep,value.var="Rep") names(res1)[grep("[0-9]",names(res1))]<-paste("Rep",1:5,sep="")
res1[,-c(1:4)]<-sapply(res1[,-c(1:4)],function(x) as.integer(is.na(x))) res1 # year Site specie Pres Rep1 Rep2 Rep3 Rep4 Rep5 #1 2003 2021 MICH 1 1 1 0 0 1 #2 2003 2021 MISA 1 0 1 1 1 1 #3 2003 2021 MOBO 1 0 0 0 0 1 #4 2003 2021 SILU 1 0 1 1 0 1 #5 2003 2021 TYSA 1 1 1 1 1 0 #6 2003 2021 ZEAU 1 0 1 0 0 0 #7 2003 2021 ZOCA 1 0 1 1 0 0 #8 2003 2022 MICH 1 1 1 1 1 0 #9 2003 2022 MISA 1 1 0 0 1 1 A.K. ----- Original Message ----- From: Andrea Goijman <agoij...@cnia.inta.gov.ar> To: R help <r-help@r-project.org> Cc: Sent: Friday, January 4, 2013 6:15 PM Subject: [R] help "reshaping" dataframe List, I want to reshape my data, but I'm not sure how to do it... it might be a simple task, but don't know which package does this. "occ.data" (see below) is how my original data are arranged, and I know that with melt() I can reshape it like "y" (see below). However, I just want to build a matrix like the "y" matrix, but with only 2 dimensions. Something like this: year Site specie Pres Rep1 Rep2 Rep3 Rep4 Rep5 1 2003 2021 MICH 1 0 0 1 1 0 3 2003 2021 MISA 1 1 0 0 0 0 4 2003 2021 MOBO 1 1 1 0 0 0 where "year" and "specie" are not another dimension, they are different columns; and Rep is the other dimension > occ.data <- read.table("Occ_03.csv", header=TRUE,sep=",",na.strings=TRUE) > occ.data[1:20,] year Ruta Point Site specie Pres Rep 1 2003 202 3 2021 MICH 1 3 2 2003 202 4 2021 MICH 1 4 3 2003 202 1 2021 MISA 1 1 4 2003 202 1 2021 MOBO 1 1 5 2003 202 2 2021 MOBO 1 2 6 2003 202 3 2021 MOBO 1 3 7 2003 202 4 2021 MOBO 1 4 8 2003 202 1 2021 SILU 1 1 9 2003 202 4 2021 SILU 1 4 10 2003 202 5 2021 TYSA 1 5 11 2003 202 1 2021 ZEAU 1 1 12 2003 202 3 2021 ZEAU 1 3 13 2003 202 4 2021 ZEAU 1 4 14 2003 202 5 2021 ZEAU 1 5 15 2003 202 1 2021 ZOCA 1 1 16 2003 202 4 2021 ZOCA 1 4 17 2003 202 5 2021 ZOCA 1 5 18 2003 202 10 2022 MICH 1 5 19 2003 202 7 2022 MISA 1 2 20 2003 202 8 2022 MISA 1 3 > > ###Reshape the data using the R package "reshape" > library(reshape) > > all.melt=melt(occ.data,id.var=c("specie", "Site", "Rep", "year"), measure.var="Pres") > y=cast(all.melt, Site ~ Rep ~ specie ~ year) > > y[is.na(y)] <- 0 > > y[1:10,,1,] , , year = 2003 Rep Site 1 2 3 4 5 1021 0 0 0 0 0 1022 0 0 0 0 0 1023 0 0 0 0 0 1024 0 0 0 0 0 1025 0 0 0 0 0 1026 0 0 0 0 0 2021 0 0 0 0 0 2022 0 0 0 0 0 2023 0 0 0 0 0 2024 0 0 0 0 0 , , year = 2004 Rep Site 1 2 3 4 5 1021 0 0 0 0 1 1022 1 0 0 0 0 1023 0 0 0 0 0 1024 0 0 0 0 0 1025 0 0 0 0 0 1026 0 0 0 0 0 2021 0 0 0 0 0 2022 0 0 0 0 0 2023 0 0 0 0 0 2024 0 0 0 0 0 [[alternative HTML version deleted]] ______________________________________________ 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.