Using the dataset below, I got close to what I'm after, but not quite all
the way there. Any suggestions appreciated:
Daily <- read.table(textConnection(" 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)
aggregate(Q ~ wyr, data = Daily, which.max)
# gives:
# wyr Q
# 1 1990 4
# 2 1991 2
# 3 1992 1
# 4 1993 3
# 5 1994 2
I can 'see' that it is returning the which.max() relative to each
grouping. Is there a way to instead return the absolute position (row) of
the max value within each group. i.e.:
# Would instead like to have
# wyr Q
# 1 1990 4
# 2 1991 6
# 3 1992 9
# 4 1993 15
# 5 1994 18
The icing on the cake would be to get the Julien Day corresponding to the
date on which each year's maximum occurs?
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