If Statement, do function, say statement

I am trying to write a simple if statement. I have data like this

Number Description Type
1 Snow in road "weather"
2 Ice on Roof "Weather"
3 Dog bite "Not Classified"


Basically trying to do this:

if(data$type == "Not Classified") {sapply(data$description, colcheck)} else "Not Classified"


The desired result would be for the function that I have stated previously in my code to run on row 3, the "Not Classified" row. For some reason, I keep getting the same error:

"Not Classified"

"the condition has length > 1 and only the first element will be used".


colcheck is a function created previously. I have tried IfElse, taking out the else at the end, and adding a do in front of the function, but they aren't working. I am trying to filter the data to only use the function on the rows where type == "Not classified". Thank you

colcheck

IfElse

else

do

type == "Not classified"

data$newColumn <- ifelse(data$type == "Not Classified", colcheck(data$description), "Not Classified")

1 Answer
1

The problem is that data$type is a vector of length > 1. The == operator compares a single value only and when you pass it a vector, it takes only the first value, rather than failing.

data$type

==

What you want to do is use apply or dplyr::mutate to apply the test to each element of data$type:

apply

dplyr::mutate

data$type

data <- data.frame('id' = c(1,2,3,4,5,6),
'type' = rep(c('Classified','Not Classified'),3),
'description' = c('Cat', 'Dog', 'Fish', 'Mouse', 'Horse', "Moose"))
data
id type description
1 1 Classified Cat
2 2 Not Classified Dog
3 3 Classified Fish
4 4 Not Classified Mouse
5 5 Classified Horse
6 6 Not Classified Moose


Example function for colcheck:

colcheck

colcheck <- function(x) return(paste0('x',x,'x'))


Using base apply:

apply

apply(data, 1, function(row) {
if (row['type'] == 'Not Classified') {
return(colcheck(row['description']))
} else {
return("Not Classified")
}
})

[1] "Not Classified" "xDogx" "Not Classified" "xMousex" "Not Classified"
[6] "xMoosex"


Or with dplyr:

dplyr

data %>%
mutate('colcheck' = if_else(type == 'Not Classified',
colcheck(description),
'Not Classified'))

id type description colcheck
1 1 Classified Cat Not Classified
2 2 Not Classified Dog xDogx
3 3 Classified Fish Not Classified
4 4 Not Classified Mouse xMousex
5 5 Classified Horse Not Classified
6 6 Not Classified Moose xMoosex


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