Determining which.max() within groups

Aggregate can do both which.max and group length calculations, but the 
result ends up as a matrix inside the data frame, which I find cumbersome 
to work with.

Daily <- read.table( text =
"     Date  wyr        Q
1911-04-01 1990 4.530695
1911-04-02 1990 4.700596
1911-04-03 1990 4.898814
1911-04-04 1990 5.097032
1911-04-05 1991 5.295250
1911-04-06 1991 6.569508
1911-04-07 1991 5.861587
1911-04-08 1991 5.153666
1911-04-09 1992 4.445745
1911-04-10 1992 3.737824
1911-04-11 1992 3.001586
1911-04-12 1992 3.001586
1911-04-13 1993 2.350298
1911-04-14 1993 2.661784
1911-04-16 1993 3.001586
1911-04-17 1993 2.661784
1911-04-19 1994 2.661784
1911-04-28 1994 3.369705
1911-04-29 1994 3.001586
1911-05-20 1994 2.661784
", header = TRUE, stringsAsFactors=FALSE)

# this algorithm only works if wyr groups are contiguous
out <- out[ order(out$wyr), ]
# generate a data frame with key column wyr and matrix Q as the second 
column
out <- aggregate( Q ~ wyr
                 , data = Daily
                 , FUN = function(x) {
                      c( WM = which.max(x)
                       , n=length( x )
                       )
                   }
                 )
# put matrix into separate columns Q.WM
out[ , paste( "Q", colnames( out$Q ), sep="." ) ] <- out$Q
# drop the matrix
out$Q <- NULL
# form absolute indexes Q.N
out <- within( out, {
         Q.maxidx <- cumsum( c( 0, Q.n[ -length(Q.n) ] ) ) + Q.WM
        })
result <- Daily[ with( out, Q.maxidx ), ]

# or save ourselves some effort
library(dplyr)
result2 <- (   Daily
            %>% group_by( wyr )
            %>% slice( which.max( Q ) )
            %>% as.data.frame
            )

Determining which.max() within groups

Thread (5 messages)