How to change change variables to 0 if BOTH columns = NA - r

Question

In the R data frame below, I would like to replace all of the instances where that both columns = NA to both columns = 0
So I would like to change this:
Col 1 Col 2
1 1
3 2
NA NA
3 NA
NA 3
NA NA
and would like the result to be:
Col 1 Col 2
1 1
3 2
0 0
3 NA
NA 3
0 0

Answer 1

One option is to create a logical index with rowSums on the logical matrix (!is.na(df1) - which will give TRUE values for non-NA and FALSE for NA. By doing the rowSums, rows that have 0 NAs i.e. all FALSE, will return 0 and others will be greater than 0. Negating (!) the vector returns TRUE for 0 values and all others FALSE) and then assign the rows to 0
df1[!rowSums(!is.na(df1)),] <- 0
df1
# Col 1 Col 2
#1 1 1
#2 3 2
#3 0 0
#4 3 NA
#5 NA 3
#6 0 0
Or it can be also done in the other way by not negating and comparing with the number of columns
Another option is to loop through the columns, check for the NAs with is.na and then Reduce it to a logical vector to assign the rows that are TRUE based on it to 0
df1[Reduce(`&`, lapply(df1, is.na)), ] <- 0

Answer 2

In case you want the columns explicitly referenced, you can also do
df <- data.frame(col1=c(1, 3, NA, 3, NA, NA), col2=c(1, 2, NA, NA, 3, NA))
df[is.na(df$col1) & is.na(df$col2), ] <- 0
df
## col1 col2
## 1 1 1
## 2 3 2
## 3 0 0
## 4 3 NA
## 5 NA 3
## 6 0 0
for the case of changing to zero just specific columns, you can reference those columns by index or name inside the brackets. E.g.
df <- data.frame(col1=c(1, 3, NA, 3, NA, NA), col2=c(1, 2, NA, NA, 3, NA), col3=rep(1, 6))
df[is.na(df$col1) & is.na(df$col2), c("col1", "col2")] <- 0
df
## col1 col2 col3
## 1 1 1 1
## 2 3 2 1
## 3 0 0 1
## 4 3 NA 1
## 5 NA 3 1
## 6 0 0 1