Split a column of concatenated comma-delimited data and recode output as factors

Question

I am trying to clean up some data that has been incorrectly entered. The question for the variable allows for multiple responses out of five choices, numbered as 1 to 5. The data has been entered in the following manner (this is just an example--there are many more variables and many more observations in the actual data frame): ``` data V1 1 1, 2, 3 2 1, 2, 4 3 2, 3, 4, 5 4 1, 3, 4 5 1, 3, 5 6 2, 3, 4, 5 ``` Here's some code to recreate that example data: ``` data = data.frame(V1 = c("1, 2, 3", "1, 2, 4", "2, 3, 4, 5", "1, 3, 4", "1, 3, 5", "2, 3, 4, 5")) ``` What I actually need is the data to be treated more... binary--like a set of "yes/no" questions--entered in a data frame that looks more like: ``` data V1.1 V1.2 V1.3 V1.4 V1.5 1 1 1 1 NA NA 2 1 1 NA 1 NA 3 NA 1 1 1 1 4 1 NA 1 1 NA 5 1 NA 1 NA 1 6 NA 1 1 1 1 ``` The actual variable names don't matter at the moment--I can easily fix that. Also, it doesn't matter too much whether the missing elements are "O", "NA", or blank--again,…

Accepted Answer

You just need to write a function and use `apply`. First some dummy data:

```
##Make sure you're not using factors
dd = data.frame(V1 = c("1, 2, 3", "1, 2, 4", "2, 3, 4, 5", 
                         "1, 3, 4", "1, 3, 5", "2, 3, 4, 5"), 
                     stringsAsFactors=FALSE)
```

Next, create a function that takes in a row and transforms as necessary

```
make_row = function(i, ncol=5) {
  ##Could make the default NA if needed
  m = numeric(ncol)
  v = as.numeric(strsplit(i, ",")[[1]])
  m[v] = 1
  return(m)
}
```

Then use `apply` and transpose the result

```
t(apply(dd, 1, make_row))
```

Split a column of concatenated comma-delimited data and recode output as factors

Solution

Problem