Replace values in entire data frame with column values in R - r

Question

I did some search but cannot find an obvious answer of this question so hopefully it's not a duplicated question. I have a data frame looks like this:
X1 X2 V1 V2 V3 ... Vn
A B 0 1 2 1
B C 1 0 1 0
A C 2 1 0 1
What I want to achieve is to replace V1 to Vn values to the "dosage" of X2. So for row 1 (each row may have different values of X1 and X2),
if the value is 0, I want to replace it to AA;
if the value is 1, I want to replace it to AB;
if the value is 2, I want to replace it to BB;
The expected outcome is:
X1 X2 V1 V2 V3 ... Vn
A B AA AB BB AB
B C BC BB BC BB
A C CC AC AA AC
Here is the sample data frame:
df=data.frame(X1=c("A","B","A"),
X2=c("B","C","C"),
V1=c(0,1,2),
V2=c(1,0,1),
V3=c(2,1,0))
Thanks for the help!

Answer 1

This is inspired from #Matt's answer. We can use mutate_at with paste0 to achieve this task.
## Load packages
library(dplyr)
dat2 <- dat %>%
mutate_at(vars(-X1, -X2), .funs = list(
~case_when(
. == 0 ~paste0(X1, X1),
. == 1 ~paste0(X1, X2),
. == 2 ~paste0(X2, X2),
TRUE ~NA_character_
)
))
dat2
# X1 X2 V1 V2 V3 Vn
# 1 A B AA AB BB AB
# 2 B C BC BB BC BB
# 3 A C CC AC AA AC
DATA
dat <- read.table(text = "X1 X2 V1 V2 V3 Vn
A B 0 1 2 1
B C 1 0 1 0
A C 2 1 0 1 ",
stringsAsFactors = FALSE, header = TRUE)

Answer 2

With your actual df you can replace V1:V3 with V1:Vn.
Using your reprex, you can do:
library(dplyr)
df %>%
mutate_at(
vars(V1:V3),
funs(case_when(
. == 0 ~ "AA",
. == 1 ~ "AB",
. == 2 ~ "BB"
))
)

Answer 3

It not an elegant solution but for the sake of completeness: just nest two for-loops
for (i in 1:dim(df)[1]) {
for (j in 3:dim(df)[2]){
if (df[i,j] == 0){
df[i,j] <- paste0(df[i,1], df[i,1])
} else if (df[i,j] == 1) {
df[i,j] <- paste0(df[i,1], df[i,2])
} else if (df[i,j] == 2) {
df[i,j] <- paste0(df[i,2], df[i,2])
}
}
}
Sorry for that.

Answer 4

Use spread and gather
library(tidyverse)
df <- tibble(X1=c("A","B","A"),
X2=c("B","C","C"),
V1=c(0,1,2),
V2=c(1,0,1),
V3=c(2,1,0))
Capture your from:to translation
transl <- tibble(DOSE = c(0,1,2),
OUTCOME = c("AA", "AB", "AC"))
Then Gather your values into long form
longTbl <- df %>%
gather(key = "TheV", value = "DOSE", na.rm = TRUE,starts_with("V")) %>%
left_join(transl, by = "DOSE") %>%
select(- DOSE)
# A tibble: 9 x 4
X1 X2 TheV OUTCOME
<chr> <chr> <chr> <chr>
1 A B V1 AA
2 B C V1 AB
3 A C V1 AC
4 A B V2 AB
5 B C V2 AA
6 A C V2 AB
7 A B V3 AC
8 B C V3 AB
9 A C V3 AA
You might be better leaving it there. But we can pivot it back with spread.
widTbl <- longTbl %>%
spread(TheV, OUTCOME )
widTbl
# A tibble: 3 x 5
X1 X2 V1 V2 V3
<chr> <chr> <chr> <chr> <chr>
1 A B AA AB AC
2 A C AC AB AA
3 B C AB AA AB
And Bob's your uncle.