On Sat, Apr 9, 2011 at 5:14 AM, mathijsdevaan <mathijsdev...@gmail.com> wrote:
> Hi,
>
> I need to perform calculations on subsets of a data frame:
>
> DF = data.frame(read.table(textConnection(" A B C D E F
> 1 a 1995 0 4 1
> 2 a 1997 1 1 3
> 3 b 1995 3 7 0
> 4 b 1996 1 2 3
> 5 b 1997 1 2 3
> 6 b 1998 6 0 0
> 7 b 1999 3 7 0
> 8 c 1997 1 2 3
> 9 c 1998 1 2 3
> 10 c 1999 6 0 0
> 11 d 1999 3 7 0
> 12 e 1995 1 2 3
> 13 e 1998 1 2 3
> 14 e 1999 6 0 0"),head=TRUE,stringsAsFactors=FALSE))
>
> I'd like to create new dataframes for each unique year in which for each
> value of A, the values of D, E and F are summed over the last 3 years (e.g.
> 1998 = 1998, 1997, 1996):
> Question 1: How do I go from DF to newDFyear?
>
> Examples:
>
> newDF1995
> B D E F
> a 0 4 1
> b 3 7 0
> e 1 2 3
>
> newDF1998
> B D E F
> a 1 1 3
> b 8 4 6
> c 2 4 6
> e 1 2 3
>
> Then, for each new DF I need to generate a square matrix after doing the
> following:
>
> newDF1998$G<-newDF1998$D + newDF1998$E + newDF1998$F
> newDF1998$D<-newDF1998$D/newDF1998$G
> newDF1998$E<-newDF1998$E/newDF1998$G
> newDF1998$F<-newDF1998$F/newDF1998$G
> newDF1998<-NewDF1998[,c(-5)]
>
> newDF1998
> B D E F
> a 0.2 0.2 0.6
> b 0.4 0.2 0.3
> c 0.2 0.3 0.5
> e 0.2 0.3 0.5
>
> Question 2: How do I go from newDF1998 to a matrix
>
> a b c e
> a
> b
> c
> e
>
> in which Cell ab = (0.2*0.4 + 0.2*0.2 + 0.6*0.3)/((0.2*0.2 + 0.2*0.2 +
> 0.6*0.6)^0.5) * ((0.4*0.4 + 0.2*0.2 + 0.3*0.3)^0.5) = 0.84
First we use read.zoo to reform DF into a multivariate time series and
use rollapply (where we have used the devel version of zoo since it
supports the partial= argument on rollapply). We then reform each
resulting row into a matrix converting each row of each matrix to
proportions. Finally we form the desired scaled cross product.
# devel version of zoo
install.packages("zoo", repos = "http://r-forge.r-project.org";)
library(zoo)
z <- read.zoo(DF, split = 2, index = 3, FUN = identity)
sum.na <- function(x) if (any(!is.na(x))) sum(x, na.rm = TRUE) else NA
r <- rollapply(z, 3, sum.na, align = "right", partial = TRUE)
newDF <- lapply(1:nrow(r), function(i)
prop.table(na.omit(matrix(r[i,], nc = 4, byrow = TRUE,
dimnames = list(unique(DF$B), names(DF)[-2:-3]))[, -1]), 1))
names(newDF) <- time(z)
lapply(mats, function(mat) tcrossprod(mat / sqrt(rowSums(mat^2))))
--
Statistics & Software Consulting
GKX Group, GKX Associates Inc.
tel: 1-877-GKX-GROUP
email: ggrothendieck at gmail.com
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