Modifying Data Set within a function but data set is not changed - r

Question

My code is the following in R:
replaceNA<- function(myData,limit){
numNA<- rowsum(is.na(myData))
targetRows<- which(numNA<=limit)
targetCols<- length(names(myData))
for(row in targetRows){
for(col in 1:targetCols){
myData[row,col][is.na(myData[row,col])]<-1
}
}
}
I am trying to iterate through each element in myData and replace all NAs of a row with 1 IF the row does not have more than the number of NAs. I have tested my code with print statements and found that the iteration works perfectly (although not the most efficient code) and if I examine the modified myData by putting in a fix(myData) before the last bracket of the function, I see that my function worked perfectly(the NAs are replaced with 1s for the rows that meet the limit condition). However, when I examine myData after the function terminates, myData does not show the changes replaceNA made.
I know there is a problem in storing the modified myData but I am not sure how to store it properly.

Answer 1

The condition is not clear ( English problem). In any case you don't need a for loop here.
To compute the number of missing values for each row :
rowSums(is.na(myData))
Then you just test your condition and you replace all the row:
mm <- myData[rowSums(is.na(myData)) <= limit ,]
mm[is.na(mm)] <- 1
myData[rowSums(is.na(myData)) <= limit ,] <- mm

Answer 2

You should make your function explicitly return the modified data,
replaceNA<- function(myData,limit){
numNA<- rowsum(is.na(myData))
targetRows<- which(numNA<=limit)
targetCols<- length(names(myData))
for(row in targetRows){
for(col in 1:targetCols){
myData[row,col][is.na(myData[row,col])]<-1
}
}
return(myData)
}
then assign the modified data. You could overwrite your old data
myData <- replaceNA(myData, limit = 2)
or make a copy to compare
myData_no_na <- replaceNA(myData, limit = 2)
You can also avoid the loop entirely, which is much more R-like. #agstudy's answer seems to be covering that approach nicely.