From your description I understand that you want to replace the z
values in d1
with the z
values in d2
when x
& y
match.
Using base R:
d3 <- merge(d1, d2, by = c("x","y"), all.x = TRUE)
d3[is.na(d3$z.y),"z.y"] <- d3[is.na(d3$z.y),"z.x"]
d3 <- d3[,-3]
names(d3)[3] <- "z"
which gives:
> d3
x y z
1 10 10 100
2 10 12 6
3 11 10 200
4 11 12 2
5 12 10 1
6 12 12 400
Using the data.table-package:
library(data.table)
setDT(d1) # convert the data.frame to a data.table
setDT(d2) # idem
# join the two data.table's and replace the values
d1[d2, on = .(x, y), z := i.z]
or in one go:
setDT(d1)[setDT(d2), on = .(x, y), z := i.z]
which gives:
> d1
x y z
1: 10 10 100
2: 10 12 6
3: 11 10 200
4: 11 12 2
5: 12 10 1
6: 12 12 400
Using the dplyr package:
d3 <- left_join(d1, d2, by = c("x","y")) %>%
mutate(z.y = ifelse(is.na(z.y), z.x, z.y)) %>%
select(-z.x) %>%
rename(z = z.y)
Since release 0.5.0 you can also use the coalesce
-function for this (thx to Laurent Hostert for bringing it to my attention):
d3 <- left_join(d1, d2, by = c("x","y")) %>%
mutate(z = coalesce(z.y, z.x)) %>%
select(-c(z.x, z.y))
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