Reputation: 345
I have tried searching for something but cannot find it. I have found similar threads but still they don't get what I want. I know there should be an easy way to do this without writing a loop function. Here it goes
I have two data frame df1 and df2
df1 <- data.frame(ID = c("a", "b", "c", "d", "e", "f"), y = 1:6 )
df2 <- data.frame(x = c("a", "c", "g", "f"), f=c("M","T","T","M"), obj=c("F70", "F60", "F71", "F82"))
df2$f <- as.factor(df2$f)
now I want to match df1 and df2 "ID" and "x" column with each other. But I want to add new columns to the df1 data frame that matches "ID" and "x" from df2 as well. The final output of df1 should look like this
ID y obj f1 f2
a 1 F70 M NA
b 2 NA NA NA
c 3 F60 NA T
d 4 NA NA NA
e 5 NA NA NA
f 6 F82 M NA
Upvotes: 0
Views: 108
Reputation: 38520
Here is a base R process.
# combine the data.frames
dfNew <- merge(df1, df2, by.x="ID", by.y="x", all.x=TRUE)
# add f1 and f2 variables
dfNew[c("f1", "f2")] <- lapply(c("M", "T"),
function(i) factor(ifelse(as.character(dfNew$f) == i, i, NA)))
# remove original factor variable
dfNew <- dfNew[-3]
ID y obj f1 f2
1 a 1 F70 M <NA>
2 b 2 <NA> <NA> <NA>
3 c 3 F60 <NA> T
4 d 4 <NA> <NA> <NA>
5 e 5 <NA> <NA> <NA>
6 f 6 F82 M <NA>
Upvotes: 1
Reputation: 887901
We can do this with tidyverse
after joining the two datasets and spread
the 'f' column
library(tidyverse)
left_join(df1, df2, by = c(ID = "x")) %>%
group_by(f) %>%
spread(f, f) %>%
select(-6) %>%
rename(f1 = M, f2 = T)
# A tibble: 6 × 5
# ID y obj f1 f2
#* <chr> <int> <fctr> <fctr> <fctr>
#1 a 1 F70 M NA
#2 b 2 NA NA NA
#3 c 3 F60 NA T
#4 d 4 NA NA NA
#5 e 5 NA NA NA
#6 f 6 F82 M NA
Or a similar approach with data.table
library(data.table)
dcast(setDT(df2)[df1, on = .(x = ID)], x+obj + y ~ f, value.var = 'f')[, -6, with = FALSE]
Upvotes: 2