I need to standardize how subgroups are referred to in a data set. To do this I need to identify when a variable matches one of several strings and then set a new variable with the standardized name. I am trying to do that with the following:
df <- data.frame(a = c(1,2,3,4), b = c(depression_male, depression_female, depression_hsgrad, depression_collgrad))
TestVector <- "male"
for (i in TestVector) {
df$grpl <- grepl(paste0(i), df$b)
df[ which(df$grpl == TRUE),]$standard <- "male"
}
The test vector will frequently have multiple elements. The grepl works (I was going to deal with the male/female match confusion later but I'll take suggestions on that) but the subsetting and setting a new variable doesn't. It would be better (and work) if I could transform the grepl output directly into the standard name variable.
Your only real issue is that you need to initialize the standard column. But we can simplify your code a bit:
df <- data.frame(a = c(1,2,3,4), b = c("depression_male", "depression_female", "depression_hsgrad", "depression_collgrad"))
TestVector <- "male"
df$standard <- NA
for (i in TestVector) {
df[ grepl(i, df$b), "standard"] <- "male"
}
df
# a b standard
# 1 1 depression_male male
# 2 2 depression_female male
# 3 3 depression_hsgrad <NA>
# 4 4 depression_collgrad <NA>
Then you've got the issue that the "male" pattern matches "female" as well.
Perhaps you're looking for sub instead? It works like find/replace:
df$standard = sub(pattern = "depression_", replacement = "", df$b)
df
# a b standard
# 1 1 depression_male male
# 2 2 depression_female female
# 3 3 depression_hsgrad hsgrad
# 4 4 depression_collgrad collgrad
It's hard to generalize what will be best in your case without more example input/output pairs. If all your data is of the form "depression_" this will work well. Or maybe the standard name is always after an underscore, so you could use pattern = ".*_" to replace everything before the last underscore. Or maybe something else... Hopefully these ideas give you a good start.