[R] lapply and aggregate function

ONKELINX, Thierry Thierry.ONKELINX at inbo.be
Tue Feb 3 16:22:43 CET 2009

Have a look at cast() form the reshape package.

myD <- data.frame( Light = sample(LETTERS[1:2], 10, replace=T),
		Feed  = sample(letters[1:5], 20, replace=T),
		value=rnorm(20) )
cast(myD, Light ~ ., fun = mean)
cast(myD, Feed ~ ., fun = mean)
cast(myD, Light + Feed ~ ., fun = mean)
cast(myD, Light ~ Feed, fun = mean)



ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
~ John Tukey

-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens Patrick Hausmann
Verzonden: dinsdag 3 februari 2009 16:12
Aan: r-help at r-project.org
Onderwerp: [R] lapply and aggregate function

Dear list,

I have two things I am struggling...

# First
myD <- data.frame( Light = sample(LETTERS[1:2], 10, replace=T),
                     Feed  = sample(letters[1:5], 20, replace=T),
                     value=rnorm(20) )

# Mean for Light
myD$meanLight <- unlist( lapply( myD$Light,
                         function(x) mean( myD$value[myD$Light == x]) )
# Mean for Feed
myD$meanFeed  <- unlist( lapply( myD$Feed,
                         function(x) mean( myD$value[myD$Feed == x]) ) )

# I would like to get a new Var "meanLightFeed"
# holding the "Group-Mean" for each combination (eg. A:a = 0.821581)
# by(myD$value, list(myD$Light, myD$Feed), mean)[[1]]

# Second
myD <- data.frame( Light = sample(LETTERS[1:2], 10, replace=T),
                     value=rnorm(20) )

w1 <- tapply(myD$value, myD$Light, mean)
# > w1
#         A          B
# 0.4753412 -0.2108387

myfun <- function(x) (myD$value > w1[x] & myD$value < w1[x] * 1.5)

I would like to have a TRUE/FALSE-Variable depend on the constraint in
"myfun" for each level in "Light"...

As always - thanks for any help!!

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