I want to count attributes of IDs:
--8<---------------cut here---------------start------------->8---
z <- data.frame(id=c(10,20,10,30,10,20),
a1=c("a","b","a","c","b","b"),
a2=c("x","y","x","z","z","y"),
stringsAsFactors=FALSE)
z
id a1 a2
1 10 a x
2 20 b y
3 10 a x
4 30 c z
5 10 b z
6 20 b y
--8<---------------cut here---------------end--------------->8---
I want to get something like
--8<---------------cut here---------------start------------->8---
id a1.tot a1.val1 a1.num1 a1.val2 a1.num2 a2.tot a2.val1 a2.num1 a2.val2 a2.num2
10 3 "a" 2 "b" 1 3 "x" 2 "z" 1
20 2 "b" 2 <NA> 0 2 "y" 2 <NA> 0
30 1 "c" 1 <NA> 0 1 "z" 1 <NA> 0
--8<---------------cut here---------------end--------------->8---
(except that I don't care what appears in the cells marked with <NA>)
I tried this:
--8<---------------cut here---------------start------------->8---
aggregate(z,by=list(id=z$id),function (s) {
t <- sort(table(s),decreasing=TRUE)
if (length(t) == 1)
list(length(s),names(t)[1],t[1],"junk",0)
else
list(length(s),names(t)[1],t[1],names(t)[2],t[2])
})
id id a1 a2
1 10 3 3 3
2 20 2 2 2
3 30 1 1 1
Warning message:
In format.data.frame(x, digits = digits, na.encode = FALSE) :
corrupt data frame: columns will be truncated or padded with NAs
--8<---------------cut here---------------end--------------->8---
Thanks!
id id a1 a2
1 10 10, 10, 10 a, a, b x, x, z
2 20 20, 20 b, b y, y
3 30 30 c z
work, but
aggregate(z, list(id=z$id),FUN=function(l) {
t <- sort(table(l),decreasing=TRUE)
list(length(t),t[1],names(t)[1],t[2],names(t)[2])
})
id id a1 a2
1 10 1 2 2
2 20 1 1 1
3 30 1 1 1
Warning message:
In format.data.frame(x, digits = digits, na.encode = FALSE) :
corrupt data frame: columns will be truncated or padded with NAs
does not?
(I do not want to put the whole list of all possible values into the
return value of aggregate because I am afraid of running out of ram)
* arun <fznegcvax111 at lnubb.pbz> [2012-09-20 14:24:37 -0700]:
Hi,
Try this:
z1<-aggregate(z,list(id=z$id),FUN=paste,sep=",")
dat1<-data.frame(id=z1[,1],a1.total=unlist(lapply(z1[,3],length)),a1.val1=unique(z$a1),a1.num=unlist(lapply(lapply(z1[,3],table),`[`,1)),a1.val2=unlist(lapply(z1[,3],`[`,3)),a1.num2=unlist(lapply(lapply(z1[,3],table),`[`,2)),a2.total=unlist(lapply(z1[,4],length)),a2.val1=unique(z$a2),a2.num=unlist(lapply(lapply(z1[,4],table),`[`,1)),a2.val2=unlist(lapply(z1[,4],`[`,3)),a2.num2=unlist(lapply(lapply(z1[,4],table),`[`,2)))
dat1
# id a1.total a1.val1 a1.num a1.val2 a1.num2 a2.total a2.val1 a2.num a2.val2
#0 10??????? 3?????? a????? 2?????? b?????? 1??????? 3?????? x????? 2?????? z
#1 20??????? 2?????? b????? 2??? <NA>????? NA??????? 2?????? y????? 2??? <NA>
#2 30??????? 1?????? c????? 1??? <NA>????? NA??????? 1?????? z????? 1??? <NA>
#? a2.num2
#0?????? 1
#1????? NA
#2????? NA
#It is not an elegant way!
A.K.
----- Original Message -----
From: Sam Steingold <sds at gnu.org>
To: r-help at r-project.org
Cc:
Sent: Thursday, September 20, 2012 2:06 PM
Subject: [R] aggregate help
I want to count attributes of IDs:
z <- data.frame(id=c(10,20,10,30,10,20),
? ? ? ? ? ? ? ? a1=c("a","b","a","c","b","b"),
? ? ? ? ? ? ? ? a2=c("x","y","x","z","z","y"),
? ? ? ? ? ? ? ? stringsAsFactors=FALSE)
z
? id a1 a2
1 10? a? x
2 20? b? y
3 10? a? x
4 30? c? z
5 10? b? z
6 20? b? y
I want to get something like
id a1.tot a1.val1 a1.num1 a1.val2 a1.num2 a2.tot a2.val1 a2.num1 a2.val2 a2.num2
10? 3? ? "a"? ? ? 2? ? ? "b"? ? ? 1? ? ? 3? ? ? "x"? ? 2? ? ? "z"? ? 1
20? 2? ? "b"? ? ? 2? ? ? <NA>? ? 0? ? ? 2? ? ? "y"? ? 2? ? ? <NA>? ? 0
30? 1? ? "c"? ? ? 1? ? ? <NA>? ? 0? ? ? 1? ? ? "z"? ? 1? ? ? <NA>? ? 0
(except that I don't care what appears in the cells marked with <NA>)
I tried this:
aggregate(z,by=list(id=z$id),function (s) {
? t <- sort(table(s),decreasing=TRUE)
? if (length(t) == 1)
? ? list(length(s),names(t)[1],t[1],"junk",0)
? else
? ? list(length(s),names(t)[1],t[1],names(t)[2],t[2])
})
? id id a1 a2
1 10? 3? 3? 3
2 20? 2? 2? 2
3 30? 1? 1? 1
Warning message:
In format.data.frame(x, digits = digits, na.encode = FALSE) :
? corrupt data frame: columns will be truncated or padded with NAs
Thanks!