a1 <- data.frame(id=c(1,1,1,1,2,2,2,3,3),
var=c("6402","1","1","3","6406","6406","2","1","1"))
b1 <- data.frame(var=c("6402","6406"),
txt=c("A","B"))
n1 <- data.frame(id=c(1,2,3))
desired <- data.frame(id=c(1,2,3),
txt=c("A","B",NA))
How can I join a1,b1 and n1 to generate the desired df?
With next code you can get something similar to desired dataframe:
#Code
merge(n1,merge(a1,b1)[,-1],all.x = T)[!duplicated(merge(n1,merge(a1,b1)[,-1],all.x = T)[,'id']),]
Output:
id txt
1 1 A
2 2 B
4 3 <NA>
We can use tidyverse
library(dplyr)
distinct(a1) %>%
left_join(b1, by = 'var') %>%
full_join(n1) %>%
group_by(id) %>%
summarise(txt = first(txt))
# A tibble: 3 x 2
# id txt
# <dbl> <chr>
#1 1 A
#2 2 B
#3 3 <NA>
Or using data.table
unique(setDT(a1))[b1, txt := txt, on = .(var)][n1, .SD[1],
on = .(id), by = .EACHI][, var := NULL][]
Here is a base R option using nested merge
merge(n1,
merge(unique(a1),
b1,
by = "var",
all.y = TRUE
),
by = "id",
all = TRUE
)[c("id", "txt")]
which gives
id txt
1 1 A
2 2 B
3 3 <NA>
