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
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
