Complete partially filled in columns, based on established relationships between columns

Question

I'm looking to complete a two columns which are based on each other, however they are partially filled. ``` title <- c("Mrs", "Ms", "", "Ms", "Mr", "Mr", "") gender <- c("female", "", "male", "female", "", "Male", "female") df <- as.data.frame(cbind(title, gender)) df title gender 1 Mrs female 2 Ms 3 male 4 Ms female 5 Mr 6 Mr Male ``` In this example, we know that if `title=Mrs` or `Ms`, then gender should be filled in with `female`, and if `title=Mr` then gender should be filled in as `male`. On the flip side if only gender is filled in to be `female`, then title should be `Ms`, or for `male` title should be `Mr`. To add to this, how would you be able to complete a partially filled table without having to establish the relationships beforehand. Refer to the example below: ``` c1 <- paste(rep(letters[1:12], 4)) c2 <- paste(rep(letters[13:24], 4)) df <- as.data.frame(cbind(c1, c2), stringsAsFactors=FALSE) #replacing 8 strings in each column df[sample(nrow(df), 8),]$c1 <- "" df[sample(…

Accepted Answer

I think this is what you want:

```
#Find those where there is no title
noTitle = which(df$title=="")
#And fill them in based on the gender
df$title[noTitle] = ifelse(grepl("[Ff]",df$gender[noTitle]), "Ms", "Mr")
#Do the same for gender
noGender = which(df$gender=="")
df$gender[noGender] = ifelse(grepl("[Ss]",df$title[noGender]), "female", "male")
```

If they were both empty then there would be a check to start with and a convert them as appropriate; something like:

```
#Find where both empty
Neither = intersect( which(df$title=""), which(df$gender=="") )
##Do something here
```

Complete partially filled in columns, based on established relationships between columns

Solution

Problem