Can I match regular expressions in switch statements in R? - r

Question

I have a vector of string where people where asked to guess someones age, this includes statements like "50-60", "ca. 50" or ">50". I want to use regular expressions to match these cases and get the real numerical values. "50-60" should produce 55 (as the mean of both values), the other two examples 50.
For each variant, I wanted to have a case in a switch like below, but it doesn't seem to work. Is it even possible to use a regex in a switch?
switch (string,
str_detect(string, "[:digit:]+[:blank:]*(-|_)[:blank:]*[:digit:]+") = {
first <- str_sub(string, 1, 2) %>% as.numeric()
second <- str_sub(string, str_length(string)-1, str_length(string)) %>% as.numeric()
value <- mean(c(first, second))
},
str_detect(string, "((ca)\.?)|>|~[:blank:]*[:digit:]+") = {
value <- str_sub(string, str_length(string)-1, str_length(string)) %>% as.numeric()
},
str_detect(string, "[:digit:]+[:punct:]") = {
value <- str_sub(string, 1, 2) %>% as.numeric()
},
print(string, " could not be matched")
)
The expressions themselves are working as intended (as far as I tested), so I guess I can't use them in the switch like this. However I couldn't find a solution anywhere.
Edit: Added what the expected output for the examples is

Answer 1

We can do this with tidyverse methods
Convert the string to a tibble/data.frame
Remove the characters not neeeded with str_remove_all
Then, separate the column into two by specifying the sep
Get the rowMeans
library(dplyr)
library(tidyr)
library(stringr)
tibble(mystring) %>%
mutate(mystring = str_remove_all(mystring, "[A-Za-z.><]+")) %>%
separate(mystring, into = c('col1', 'col2'), sep="[- ]+",
convert = TRUE) %>%
transmute(out = rowMeans(., na.rm = TRUE))
-output
# A tibble: 3 x 1
out
<dbl>
1 55
2 50
3 50
data
mystring <- c("50-60", "ca. 50", ">50")

Answer 2

You can use a nested if/else approach -
library(stringr)
string <- "50-60"
if(str_detect(string, "[:digit:]+[:blank:]*(-|_)[:blank:]*[:digit:]+")) {
first <- str_sub(string, 1, 2) %>% as.numeric()
second <- str_sub(string, str_length(string)-1, str_length(string)) %>% as.numeric()
value <- mean(c(first, second))
value
} else if(str_detect(string, "((ca)\\.?)|>|~[:blank:]*[:digit:]+")) {
value <- str_sub(string, str_length(string)-1, str_length(string)) %>% as.numeric()
value
} else if(str_detect(string, "[:digit:]+[:punct:]")) {
value <- str_sub(string, 1, 2) %>% as.numeric()
value
} else NA
#[1] 55
For string <- "ca. 50" it returns 50.

Answer 3

mystring <- c("50-60", "ca. 50", ">50")
library(stringr)
lapply(str_extract_all(mystring, "[0-9]+"),
function(x) if (length(x) == 1) as.numeric(x[1]) else mean(as.numeric(x)))
[[1]]
[1] 55
[[2]]
[1] 50
[[3]]
[1] 50