I have a data.table and want to pick those lines of the data.table where some values of a variable x are unique relative to another variable y
It\'s possible to get
Thanks to dplyR
library(dplyr)
col1 = c(1,1,3,3,5,6,7,8,9)
col2 = c("cust1", 'cust1', 'cust3', 'cust4', 'cust5', 'cust5', 'cust5', 'cust5', 'cust6')
df1 = data.frame(col1, col2)
df1
distinct(select(df1, col1, col2))
data.table
is a bit different in how to use duplicated
. Here's the approach I've seen around here somewhere before:
dt <- data.table(y=rep(letters[1:2],each=3),x=c(1,2,2,3,2,1),z=1:6)
setkey(dt, "y", "x")
key(dt)
# [1] "y" "x"
!duplicated(dt)
# [1] TRUE TRUE FALSE TRUE TRUE TRUE
dt[!duplicated(dt)]
# y x z
# 1: a 1 1
# 2: a 2 2
# 3: b 1 6
# 4: b 2 5
# 5: b 3 4
The simpler data.table
solution is to grab the first element of each group
> dt[, head(.SD, 1), by=.(y, x)]
y x z
1: a 1 1
2: a 2 2
3: b 3 4
4: b 2 5
5: b 1 6
The idiomatic data.table
way is:
require(data.table)
unique(dt, by = c("y", "x"))
# y x z
# 1: a 1 1
# 2: a 2 2
# 3: b 3 4
# 4: b 2 5
# 5: b 1 6