HI Alain,
Try this:
df.breaks<-data.frame(id=df[,1],sapply(df[,-1],function(x)
findInterval(x,quantile(x),rightmost.closed=TRUE)),stringsAsFactors=FALSE)
df.breaks
# id a b c
#1 x01 1 1 1
#2 x02 1 1 1
#3 x03 2 2 2
#4 x04 3 3 3
#5 x05 4 4 4
#6 x06 4 4 4
A.K.
----- Original Message -----
From: D. Alain <dialva...@yahoo.de>
To: Mailinglist R-Project <r-help@r-project.org>
Cc:
Sent: Tuesday, February 19, 2013 5:01 AM
Subject: [R] recode data according to quantile breaks
Dear R-List,
I would like to recode my data according to quantile breaks, i.e. all data
within the range of 0%-25% should get a 1, >25%-50% a 2 etc.
Is there a nice way to do this with all columns in a dataframe.
e.g.
df<-
f<-data.frame(id=c("x01","x02","x03","x04","x05","x06"),a=c(1,2,3,4,5,6),b=c(2,4,6,8,10,12),c=c(1,3,9,12,15,18))
df
id a b c
1 x01 1 2 1
2 x02 2 4 3
3 x03 3 6 9
4 x04 4 8 12
5 x05 5 10 15
6 x06 6 12 18
#I can do it in very complicated way
apply(df[-1],2,quantile)
a b c
0% 1.0 2.0 1.0
25% 2.2 4.5 4.5
50% 3.5 7.0 10.5
75% 4.8 9.5 14.2
100% 6.0 12.0 18.0
#then
df$a[df$a<=2.2]<-1
...
#result should be
df.breaks
id a b c
x01 1 1 1
x02 1 1 1
x03 2 2 2
x04 3 3 3
x05 4 4 4
x06 4 4 4
But there must be a way to do it more elegantly, something like
df.breaks<- apply(df[-1],2,recode.by.quantile)
Can anyone help me with this?
Best wishes
Alain
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