Is there an R dplyr method for merge with all=TRUE?

dataframe, dplyr, r

Solution

The most recent version of `dplyr` (0.4.0) now has a full_join option, which is what I believe you want.

cost <- data.frame(farm=c('farm A', 'office'), cost=c(10, 100))
trees <- data.frame(farm=c('farm A', 'farm B'), trees=c(20,30))
merge(cost, trees, all=TRUE)

Returns

> merge(cost, trees, all=TRUE)
        farm cost trees
    1 farm A   10    20
    2 office  100    NA
    3 farm B   NA    30

And

library(dplyr)
full_join(cost, trees)

Returns

> full_join(cost, trees)
Joining by: "farm"
    farm cost trees
1 farm A   10    20
2 office  100    NA
3 farm B   NA    30
Warning message:
joining factors with different levels, coercing to character vector

Problem

I have two R dataframes I want to merge. In straight R you can do: ``` cost <- data.frame(farm=c('farm A', 'office'), cost=c(10, 100)) trees <- data.frame(farm=c('farm A', 'farm B'), trees=c(20,30)) merge(cost, trees, all=TRUE) ``` which produces: ``` farm cost trees 1 farm A 10 20 2 office 100 NA 3 farm B NA 30 ``` I am using `dplyr`, and would prefer a solution such as: ``` left_join(cost, trees) ``` which produces something close to what I want: ``` farm cost trees 1 farm A 10 20 2 office 100 NA ``` In `dplyr` I can see `left_join`, `inner_join`, `semi_join` and `anti-join`, but none of these does what `merge` with `all=TRUE` does. Also - is there a quick way to set the NAs to 0? My efforts so far using `x$trees[is.na(x$trees)] <- 0;` are laborious (I need a command per column) and don't always seem to work. thanks

Original source