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> data.frame(A=1:10, B=1:10) |> dplyr::left_join(data.frame(A=1:5, C=1:5, D=1:5))
Joining, by = "A"
    A  B  C  D
1   1  1  1  1
2   2  2  2  2
3   3  3  3  3
4   4  4  4  4
5   5  5  5  5
6   6  6 NA NA
7   7  7 NA NA
8   8  8 NA NA
9   9  9 NA NA
10 10 10 NA NA

Instead of the NA, can I tell left_join to fill the cells that were not joinable with something else?

Big Cat Public Safety Act
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  • you can do this afterwards `%>% replace(., is.na(.), -999)` – akrun Oct 05 '21 at 18:42
  • that does not work when there are NA that were present NOT due to the join. And this is precisely why this functionality is needed. If NA were already present, then the 2 types of NA become conflated. – Big Cat Public Safety Act Oct 05 '21 at 19:05

1 Answers1

1

We could write a function: Learned here: R Left Outer Join with 0 Fill Instead of NA While Preserving Valid NA's in Left Table

library(dplyr)
library(tidyr) 

left_join_999 <- function(x, y, fill = 999, ...){
  z <- left_join(x, y, ...)
  new_cols <- setdiff(names(z), names(x))
  z <- replace_na(z, setNames(as.list(rep(fill, length(new_cols))), new_cols))
  z
}

left_join_999(df1, df2, by="A")

output:

  A  B   C   D
1   1  1   1   1
2   2  2   2   2
3   3  3   3   3
4   4  4   4   4
5   5  5   5   5
6   6  6 999 999
7   7  7 999 999
8   8  8 999 999
9   9  9 999 999
10 10 10 999 999
TarJae
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