Binary search based subset on NA values in data.table
data.table, r
Solution
In the example as shown, I would do it like this:
DT <- DT[!is.na(x) & !is.na(y)]
Doesn't use the J() function as requested, but thought I'd share this anyways.
Problem
I am trying to remove rows from my `data.table` where either one of two columns contain `NA` value. I would like to utilize binary search using `J` function from `data.table` package. Here is what I tried: ``` DT = data.table(x=rep(c("a","b",NA),each=10), y=c(1,3,6)) setkey(DT,x) DT x y 1: NA 6 2: NA 1 3: NA 3 4: NA 6 5: NA 1 6: NA 3 7: NA 6 8: NA 1 9: NA 3 10: NA 6 11: a 1 12: a 3 13: a 6 14: a 1 15: a 3 16: a 6 17: a 1 18: a 3 19: a 6 20: a 1 21: b 3 22: b 6 23: b 1 24: b 3 25: b 6 26: b 1 27: b 3 28: b 6 29: b 1 30: b 3 x y ``` To remove all rows where `x` is `NA` I tried: ``` DT[!J(NA_character_)] ``` ...but it still returns the entire `data table`. Does anyone have an idea of what I am doing wrong? Thank you so much!