I must imagine this question is not unique, but I was struggling with which words to search for so if this is redundant please point me to the post!
I have a dataframe
test <- data.frame(x = c("a", "b", "c", "d", "e"))
x
1 a
2 b
3 c
4 d
5 e
And I'd like to replace SOME of the values using a separate data frame
metadata <- data.frame(
a = c("c", "d"),
b = c("REPLACE_1", "REPLACE_2"))
Resulting in:
x
1 a
2 b
3 REPLACE_1
4 REPLACE_2
5 e
A base R solution using match + replace
test <- within(test,x <- replace(as.character(x),match(metadata$a,x),as.character(metadata$b)))
such that
> test
x
1 a
2 b
3 REPLACE_1
4 REPLACE_2
5 e
Importing your data with stringsAsFactors = FALSE and using dplyr and stringr, you can do:
test %>%
mutate(x = str_replace_all(x, setNames(metadata$b, metadata$a)))
x
1 a
2 b
3 REPLACE_1
4 REPLACE_2
5 e
Or using the basic idea from @Sotos:
test %>%
mutate(x = pmax(x, metadata$b[match(x, metadata$a, nomatch = x)], na.rm = TRUE))
You can do,
test$x[test$x %in% metadata$a] <- na.omit(metadata$b[match(test$x, metadata$a)])
# x
#1 a
#2 b
#3 REPLACE_1
#4 REPLACE_2
#5 e
Here's one approach, though I presume there are shorter ones:
library(dplyr)
test %>%
left_join(metadata, by = c("x" = "a")) %>%
mutate(b = coalesce(b, x))
# x b
#1 a a
#2 b b
#3 c REPLACE_1
#4 d REPLACE_2
#5 e e
(Note, I have made the data types match by loading metadata as character, not factors:
metadata <- data.frame(stringsAsFactors = F,
a = c("c", "d"),
b = c("REPLACE_1", "REPLACE_2"))
You can use match to make this update join.
i <- match(metadata$a, test$x)
test$x[i] <- metadata$b
# test
# x
#1 a
#2 b
#3 REPLACE_1
#4 REPLACE_2
#5 e
Or:
i <- match(test$x, metadata$a)
j <- !is.na(i)
test$x[j] <- metadata$b[i[j]]
test
# x
#1 a
#2 b
#3 REPLACE_1
#4 REPLACE_2
#5 e
Data:
test <- data.frame(x = c("a", "b", "c", "d", "e"), stringsAsFactors = FALSE)
metadata <- data.frame(
a = c("c", "d"),
b = c("REPLACE_1", "REPLACE_2"), stringsAsFactors = FALSE)
