R: Standard evaluation for *_join (dplyr)

Question

How to join 2 tables using *_join() from dplyr, when the join variable names are different and stored in another variable?

e.g.

df1 = data_frame(x1 = 1:10,y1 = 21:30)
df2 = data_frame(x2 = 6:15,y2 = 26:35)
df3 = data_frame(x1 = 6:15,y2 = 26:35)

var1 = "x1"
var2 = "x2"

df1 %>% left_join(df3,by=c(var1)) # #1 works

but this gives error -

df1 %>% left_join(df2,by=c(var1 = var2)) # #2 doesn't work
Error: cannot join on columns 'x2' x 'var1': index out of bounds

surprisingly, this works -

df1 %>% left_join(df2,by=c("x1" = var2)) # #3 works

Answer 1

The problem here is that you have to supply a named vector if the common column has different names in the data.frames. See what happens in your example:

It works when you supply the names directly:

df1 %>% left_join(df2, by = c("x1" = "x2"))
#Source: local data frame [10 x 3]
#
#   x1 y1 y2
#1   1 21 NA
#2   2 22 NA
#3   3 23 NA
#4   4 24 NA
#5   5 25 NA
#6   6 26 26
#7   7 27 27
#8   8 28 28
#9   9 29 29
#10 10 30 30

And the named vector you supply is:

c("x1" = "x2")
#  x1 
#"x2" 

Now if you use character vectors, the named vector changes to:

var1 = "x1"
var2 = "x2"

c(var1 = var2)
#var1             # <~~ this is why it doesn't work
#"x2"

I don't know if there's a "clean" way to solve this in dplyr currently. A workaround is the following tweak to construct the named vector as required:

df1 %>% left_join(df2, by = setNames(var2, var1))
#Source: local data frame [10 x 3]
#
#   x1 y1 y2
#1   1 21 NA
#2   2 22 NA
#3   3 23 NA
#4   4 24 NA
#5   5 25 NA
#6   6 26 26
#7   7 27 27
#8   8 28 28
#9   9 29 29
#10 10 30 30

This works because:

setNames(var2, var1)
#  x1 
#"x2" 

Hope it helps.

---

Note: you could do the same with names<- like so:

df1 %>% left_join(df2, by = `names<-`(var2, var1))

but Hadley recommends using the setNames approach instead.