This is a bug, which I've fixed in the development version (hopefully
to be released next week).
In the plyr 1.2:
OK, thank you both for your answers. I'll wait for the next version.
Regards,
Jan
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> daply(data.test, .(municipality, employed), function(d){mean(d$age)} )
> employed
> municipality no yes
> A 41.58759 44.67463
> B 55.57407 43.82545
> C 43.59330 NA
>
> The .drop argument has a different meaning in daply. Some R functio
Hi:
Here's what I tried:
# data frame versions (aggregate, ddply):
aggregate(age ~ municipality + employed, data = data.test, FUN = mean)
municipality employed age
1B no 55.57407
2C no 44.67463
3A yes 41.58759
4B yes 43
Dear list,
I get some strange results with daply from the plyr package. In the
example below, the average age per municipality for employed en
unemployed is calculated. If I do this using tapply (see code below) I
get the following result:
no yes
A NA 36.94931
B 51.2250
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