Hi,
When using the aggregate function to aggregate a data.frame by one or more grouping variables I often have the problem, that I want the mean for some numeric variables but the unique value for factor variables.
So for example in this data-frame:
data <- data.frame(x = rnorm(10,1,2), group = c(rep(1,5), rep(2,5)), gender =c(rep('m',5), rep('f',5)))
aggregate(data, by=list(data$group), FUN=mean)
I would like to have 'm' and 'f' in the third column, not NA.
I see the problem, that it could happen that there is no unique factor level in a group ?
but is there an alternative function who at least tries what I am aiming at?
That is;
"aggregate the data.frame by a list of grouping variables,
for numeric variables compute the mean,
for factor variables return the unique factor value"
Thanks!
aggregate data.frame based on column class
4 messages · Martin Batholdy, Ista Zahn, arun
Hi,
Hope this is what you meant.
#data1
aggregate(.~group+gender,data=data1,mean)
#? group gender???????? x
#1???? 2????? f? 1.750686
#2???? 1????? m -1.074343
A.K.
----- Original Message -----
From: Martin Batholdy <batholdy at googlemail.com>
To: "r-help at r-project.org" <r-help at r-project.org>
Cc:
Sent: Friday, January 11, 2013 10:07 AM
Subject: [R] aggregate data.frame based on column class
Hi,
When using the aggregate function to aggregate a data.frame by one or more grouping variables I often have the problem, that I want the mean for some numeric variables but the unique value for factor variables.
So for example in this data-frame:
data <- data.frame(x = rnorm(10,1,2), group = c(rep(1,5), rep(2,5)), gender =c(rep('m',5), rep('f',5)))
aggregate(data, by=list(data$group), FUN=mean)
I would like to have 'm' and 'f' in the third column, not NA.
I see the problem, that it could happen that there is no unique factor level in a group ?
but is there an alternative function who at least tries what I am aiming at?
That is;
"aggregate the data.frame by a list of grouping variables,
for numeric variables compute the mean,
for factor variables return the unique factor value"
Thanks!
______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Please see in line. On Fri, Jan 11, 2013 at 10:07 AM, Martin Batholdy
<batholdy at googlemail.com> wrote:
Hi,
When using the aggregate function to aggregate a data.frame by one or more grouping variables I often have the problem, that I want the mean for some numeric variables but the unique value for factor variables.
So for example in this data-frame:
data <- data.frame(x = rnorm(10,1,2), group = c(rep(1,5), rep(2,5)), gender =c(rep('m',5), rep('f',5)))
aggregate(data, by=list(data$group), FUN=mean)
I would like to have 'm' and 'f' in the third column, not NA.
I see the problem, that it could happen that there is no unique factor level in a group ?
but is there an alternative function who at least tries what I am aiming at?
That is;
"aggregate the data.frame by a list of grouping variables,
for numeric variables compute the mean,
for factor variables return the unique factor value"
R is a language, so you just have to do the translation:
mt <- function(x) {
if(is.numeric(x)) { # if x is numeric
return(mean(x)) # compute the mean
} else { # otherwise
tab <- table(x) # tabulate x
return(paste(paste(names(tab), # and format it for display
tab, sep=": "),
collapse=", "))
}
}
aggregate(Dat, by=list(Dat$group), FUN=mt)
Best,
Ista
Thanks!
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Hi,
May be I misunderstood ur question.
You could do this:
res<-aggregate(.~group,data=data1,mean)
res$gender<-data1$gender[match(res$gender,as.numeric(data1$gender))]
?res
#? group???????? x gender
#1???? 1 -1.074343????? m
#2???? 2? 1.750686????? f
A.K.
----- Original Message -----
From: Martin Batholdy <batholdy at googlemail.com>
To: "r-help at r-project.org" <r-help at r-project.org>
Cc:
Sent: Friday, January 11, 2013 10:07 AM
Subject: [R] aggregate data.frame based on column class
Hi,
When using the aggregate function to aggregate a data.frame by one or more grouping variables I often have the problem, that I want the mean for some numeric variables but the unique value for factor variables.
So for example in this data-frame:
data <- data.frame(x = rnorm(10,1,2), group = c(rep(1,5), rep(2,5)), gender =c(rep('m',5), rep('f',5)))
aggregate(data, by=list(data$group), FUN=mean)
I would like to have 'm' and 'f' in the third column, not NA.
I see the problem, that it could happen that there is no unique factor level in a group ?
but is there an alternative function who at least tries what I am aiming at?
That is;
"aggregate the data.frame by a list of grouping variables,
for numeric variables compute the mean,
for factor variables return the unique factor value"
Thanks!
______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.