Lookup table with subset/grepl in R - regex

Question

I'm analyzing a set of urls and values extracted using a crawler. While I could extract substrings from the URL, I'd really rather not bother with the regex to do so—is there a simple way to do a lookup table-style replacement using subset/grepl without resorting to dplyr(do a conditional mutate on the vairables)?
My current process:
test <- data.frame(
url = c('google.com/testing/duck', 'google.com/evaluating/dog', 'google.com/analyzing/cat'),
content = c(1, 2, 3),
subdir = NA
)
test[grepl('testing', test$url), ]$subdir <- 'testing'
test[grepl('evaluating', test$url), ]$subdir <- 'evaluating'
test[grepl('analyzing', test$url), ]$subdir <- 'analyzing'
Obviously, this is a little clumsy and doesn't scale well. With dplyr, I'd be able to do something with conditionals like:
test %<>% tbl_df() %>%
mutate(subdir = ifelse(
grepl('testing', subdir),
'test r',
ifelse(
grepl('evaluating', subdir),
'eval r',
ifelse(
grepl('analyzing', subdir),
'anal r',
NA
))))
But, again, really goofy and I don't want to incur a package dependency if at all possible. Is there any way to do regex-based subsetting with some sort of lookup table?
Edit: Just a few clarifications:
For extracting subdirectories, yes, regex would be most efficient; however, I was hoping for a more general pattern that could match a dictionary-like struct of strings with other, arbitrary values.
Of course, nested ifelse is ugly and prone to error—just wanted to get a quick-and-dirty example with dplyr up.
Edit 2: Thought I'd loop back and post what I ended up with based upon BondedDust's approach. Decided to practice some mapping and non-standard eval while at it:
test <- data.frame(
url = c(
'google.com/testing/duck',
'google.com/testing/dog',
'google.com/testing/cat',
'google.com/evaluating/duck',
'google.com/evaluating/dog',
'google.com/evaluating/cat',
'google.com/analyzing/duck',
'google.com/analyzing/dog',
'google.com/analyzing/cat',
'banana'
),
content = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),
subdir = NA
)
# List used for key/value lookup, names can be regex
lookup <- c(
"testing" = "Testing is important",
"Eval.*" = 'eval in R',
"analy(z|s)ing" = 'R is fun'
)
# Dumb test for error handling:
# lookup <- c('test', 'hey')
# Defining new lookup function
regexLookup <- function(data, dict, searchColumn, targetColumn, ignore.case = TRUE){
# Basic check—need to separate errors/handling
if(is.null(names(dict)) || is.null(dict[[1]])) {
stop("Not a valid replacement value; use a key/value store for `dict`.")
}
# Non-standard eval for the column names; not sure if I should
# add safetytype/checks for these
searchColumn <- eval(substitute(searchColumn), data)
targetColumn <- deparse(substitute(targetColumn))
# Define find-and-replace utility
findAndReplace <- function (key, val){
data[grepl(key, searchColumn, ignore.case = ignore.case), targetColumn] <- val
data <<- data
}
# Map over the key/value store
mapply(findAndReplace, names(dict), dict)
# Return result, with non-matching rows preserved
return(data)
}
regexLookup(test, lookup, url, subdir, ignore.case = FALSE)

Answer 1

for (target in c('testing','evaluating','analyzing') ) {
test[grepl(target, test$url),'subdir' ] <- target }
test
url content subdir
1 google.com/testing/duck 1 testing
2 google.com/evaluating/dog 2 evaluating
3 google.com/analyzing/cat 3 analyzing
The vector of targets could have instead been the name of a vector that is in the workspace.
targets <- c('testing','evaluating','analyzing')
for( target in targets ) { ...}

Answer 2

Try this:
test$subdir<-gsub('.*\\/(.*)\\/.*','\\1',test$url)