Have 2 data-frames, need to join with multiple optional keys i.e, if t1.col1=t2.col1 OR t1.col3=t2.cold3
library(dplyr)
d1 <- data_frame(
x = letters[1:3],
y = LETTERS[2:4],
a = rnorm(3)
)
d2 <- data_frame(
x2 = letters[5:3],
y2 = LETTERS[3:1],
b = rnorm(3)
)
left_join(d1, d2, by = c("x" = "x2", "y" = "y2"))
#OUTPUT d1
x y a
<chr> <chr> <dbl>
1 a B 1.349394
2 b C -1.364727
3 c D 1.697234
#OUTPUT d2
x2 y2 b
<chr> <chr> <dbl>
1 e C 0.6587823
2 d B -1.2001558
3 c A 0.6175364
#OUTPUT joinresult : All NA in the B field
x y a b
<chr> <chr> <dbl> <dbl>
1 a B 1.349394 NA
2 b C -1.364727 NA
3 c D 1.697234 NA
#EXPECTATION : d1:x =d2:x2 for value "c" and d1:y=d2:y2 for value "B" & "C"
hence all B matching values should populated in JOIN
above sample join dataframe, when both key matches, I need to join when either or both key matches.
Any help would be greatly appreciated.
Your phrasing makes me think you know SQL, so the easiest answer might be to use sqldf, which lets you do SQL joins on dataframes as if they were tables:
library(sqldf)
sqldf('select x,y,a,b from d1 join d2 on d1.x = d2.x2 or d1.y = d2.y2')
x y a b
1 a B -0.62688156 -0.6449346
2 b C 0.04378374 -0.3865766
3 c D -0.23755237 -1.6633351
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