Using R, I am about to calculate groupwise means with aggregate(..., mean). The mean return however is wrong.
testdata <-read.table(text="
a b c d year
2 10 1 NA 1998
1 7 NA NA 1998
4 6 NA NA 1998
2 2 NA NA 1998
4 3 2 1 1998
2 6 NA NA 1998
3 NA NA NA 1998
2 7 NA 3 1998
1 8 NA 4 1998
2 7 2 5 1998
1 NA NA 4 1998
2 5 NA 6 1998
2 4 NA NA 1998
3 11 2 7 1998
1 18 4 10 1998
3 12 7 5 1998
2 17 NA NA 1998
2 11 4 5 1998
1 3 1 1 1998
3 5 1 3 1998
",header=TRUE,sep="")
aggregate(. ~ year, testdata,
function(x) c(mean = round(mean(x, na.rm=TRUE), 2)))
colMeans(subset(testdata, year=="1998", select=d), na.rm=TRUE)
aggregate says the mean of d for group 1998 is 4.62, but it is 4.5.
Reducing the data to one column only, aggregate gets it right:
aggregate(. ~ year, test[4:5],
function(x) c(mean = round(mean(x, na.rm=TRUE), 2)))
What's wrong with my aggregate() + mean() function?
aggregate is taking out your rows containing NAs in any column before passing it to the mean function. Try running your aggregate call without na.rm=TRUE - it will still work.
To fix this, you need to change the default na.action in aggregate to na.pass:
aggregate(. ~ year, testdata,
function(x) c(mean = round(mean(x, na.rm=TRUE), 2)), na.action = na.pass)
year a b c d
1 1998 2.15 7.89 2.67 4.5
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