From a dataframe like this
test <- data.frame('id'= rep(1:5,2), 'string'= LETTERS[1:10])
test <- test[order(test$id), ]
rownames(test) <- 1:10
> test
id string
1 1 A
2 1 F
3 2 B
4 2 G
5 3 C
6 3 H
7 4 D
8 4 I
9 5 E
10 5 J
I want to create a new one with the first row of each id / string pair. If sqldf accepted R code within it, the query could look like this:
res <- sqldf("select id, min(rownames(test)), string
from test
group by id, string")
> res
id string
1 1 A
3 2 B
5 3 C
7 4 D
9 5 E
Is there a solution short of creating a new column like
test$row <- rownames(test)
and running the same sqldf query with min(row)?
You can use duplicated
to do this very quickly.
test[!duplicated(test$id),]
Benchmarks, for the speed freaks:
ju <- function() test[!duplicated(test$id),]
gs1 <- function() do.call(rbind, lapply(split(test, test$id), head, 1))
gs2 <- function() do.call(rbind, lapply(split(test, test$id), `[`, 1, ))
jply <- function() ddply(test,.(id),function(x) head(x,1))
jdt <- function() {
testd <- as.data.table(test)
setkey(testd,id)
# Initial solution (slow)
# testd[,lapply(.SD,function(x) head(x,1)),by = key(testd)]
# Faster options :
testd[!duplicated(id)] # (1)
# testd[, .SD[1L], by=key(testd)] # (2)
# testd[J(unique(id)),mult="first"] # (3)
# testd[ testd[,.I[1L],by=id] ] # (4) needs v1.8.3. Allows 2nd, 3rd etc
}
library(plyr)
library(data.table)
library(rbenchmark)
# sample data
set.seed(21)
test <- data.frame(id=sample(1e3, 1e5, TRUE), string=sample(LETTERS, 1e5, TRUE))
test <- test[order(test$id), ]
benchmark(ju(), gs1(), gs2(), jply(), jdt(),
replications=5, order="relative")[,1:6]
# test replications elapsed relative user.self sys.self
# 1 ju() 5 0.03 1.000 0.03 0.00
# 5 jdt() 5 0.03 1.000 0.03 0.00
# 3 gs2() 5 3.49 116.333 2.87 0.58
# 2 gs1() 5 3.58 119.333 3.00 0.58
# 4 jply() 5 3.69 123.000 3.11 0.51
Let's try that again, but with just the contenders from the first heat and with more data and more replications.
set.seed(21)
test <- data.frame(id=sample(1e4, 1e6, TRUE), string=sample(LETTERS, 1e6, TRUE))
test <- test[order(test$id), ]
benchmark(ju(), jdt(), order="relative")[,1:6]
# test replications elapsed relative user.self sys.self
# 1 ju() 100 5.48 1.000 4.44 1.00
# 2 jdt() 100 6.92 1.263 5.70 1.15