Hi,
lst1<- lapply(letters[1:3],function(i)
{df1<-data.frame(my_df[i],my_df["dat"]); res<-ddply(df1,.(df1[[i]]),function(x)
c("mean"=mean(x$dat),"n"=nrow(x)));names(res)[1]<-i;res<-res[res[,1]==1,]})
res1<-Reduce(function(...) merge(...,all=TRUE),lst1)
res1[is.na(res1)]<-"*"
res1
# mean n a b c
#1 11 3 1 * *
#2 12 3 * * 1
#3 14 3 * 1 *
A.K.
----- Original Message -----
From: Alexander Shenkin <ashen...@ufl.edu>
To: r-help@r-project.org
Cc:
Sent: Wednesday, March 20, 2013 3:57 PM
Subject: [R] summarize dataframe based on multiple cols, not their combinations
Hi folks,
I'm trying to figure out how to get summarized data based on multiple
columns. However, instead of giving summaries for every combination of
categorical columns, I want it for each value of each categorical column
regardless of the other columns. I could do this with three different
commands, but i'm wondering if there's a more elegant way that I'm
missing. Thanks!
allie
> my_df = data.frame(a = c(1,1,1,0,0,0), b=c(0,0,0,1,1,1),
c=c(1,0,1,0,1,0), dat=c(10,11,12,13,14,15))
> my_df
a b c dat
1 1 0 1 10
2 1 0 0 11
3 1 0 1 12
4 0 1 0 13
5 0 1 1 14
6 0 1 0 15
> # not what I want
> ddply(my_df, .(a,b,c), function(x) c("mean"=mean(x$dat), "n"=nrow(x)))
a b c mean n
1 0 1 0 14 2
2 0 1 1 14 1
3 1 0 0 11 1
4 1 0 1 11 2
What I want:
a b c mean n
1 1 * * 11 3
2 * 1 * 14 3
3 * * 1 12 3
where "*" refers to any value of the other columns.
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and provide commented, minimal, self-contained, reproducible code.
