How do I change NA in df$x when df$y == 1 - r

Question

I have a simple data frame read from a csv:
df <- read.csv("test.csv", na.strings = c("", NA))
that gives this (I am using R):
x y
1 a 1
2 <NA> 1
3 <NA> 2
4 a 1
5 b 2
6 <NA> 3
I would like to change the NA in df$x to another value based on the value in df$y. Such that, if df$x = NA and df$y = 1, df$x = "p1", if df$x = NA and df$y = 2, df$x = "p2" and so on to look like this:
x y
1 a 1
2 p1 1
3 p2 2
4 a 1
5 b 2
6 p3 3
df <- df %>% replace_na(list(x = "p1"))
Lets me change the whole of df$x, but I am unable to find anything that puts a stringent condition on it. It would seem I need to use an ifelse statement but I cannot seem to get the syntax correct.
mutate(df, x = ifelse(is.na(x) && y == 1, x == 'p1', x == 'p2'))
Thanks for any help.

Answer 1

You can use the following solution. It should be noted that those <NA> values your are trying to change or stored as character strings so they are not considered NA values (you can verify that with is.na(df1$x).
library(dplyr)
df1 %>%
mutate(x = ifelse(x == "<NA>" & y == 1, "p1", ifelse(x == "<NA>" & y == 2,
"p2", ifelse(x == "<NA>" & y == 3,
"p3", x))))
x y
1 a 1
2 p1 1
3 p2 2
4 a 1
5 b 2
6 p3 3
Here is another very concise way for as many replacements as possible:
library(dplyr)
library(stringr)
library(glue)
df1 %>%
mutate(x = str_replace(x, "<NA>", glue::glue("p{y}")))
x y
1 a 1
2 p1 1
3 p2 2
4 a 1
5 b 2
6 p3 3

Answer 2

You can try the code below using replace + is.na
transform(
df,
x = replace(x, is.na(x), paste0("p", y[is.na(x)]))
)
which gives
x y
1 a 1
2 p1 1
3 p2 2
4 a 1
5 b 2
6 p3 3
Data
> dput(df)
structure(list(x = c("a", NA, NA, "a", "b", NA), y = c(1L, 1L,
2L, 1L, 2L, 3L)), class = "data.frame", row.names = c("1", "2",
"3", "4", "5", "6"))

Answer 3

In base R you can use a simple one-liner
df$x <- ifelse(is.na(df$x), paste0('p', df$y), df$x)
# x y
# 1 1 1
# 2 p1 1
# 3 p2 2
# 4 1 1
# 5 2 2
# 6 p3 3