regex (in gathering multiple sets of columns with tidyr) - r

Question

inspired by hadley's nifty gather approach in this answer I tried to use tidyr's gather() and spread() in combination with a regular expression, regex, but I seem to get it wrong on the regex.
I did study several regex questions; this one, this one, and also at regex101.com. I tried to circumvent the regex by using starts_with(), ends_with() and matches() inspired by this question, but with no luck.
I am asking here in the hope that someone can show where I get it wrong and I can solve it, preferably using, the select helpers from tidyselect.
I need to select 2 regex-groups one up to the last . and one consisting of what comes after the last ., I made this two example below, one where my code s working and one where I am stuck.
First the example that is working,
# install.packages(c("tidyverse"), dependencies = TRUE)
require(tidyverse)
The first data set, that work, looks like this,
myData1 <- tibble(
id = 1:10,
Wage.1997.1 = c(NA, 32:38, NA, NA),
Wage.1997.2 = c(NA, 12:18, NA, NA),
Wage.1998.1 = c(NA, 42:48, NA, NA),
Wage.1998.2 = c(NA, 2:8, NA, NA),
Wage.1998.3 = c(NA, 42:48, NA, NA),
Job.Type.1997.1 = NA,
Job.Type.1997.2 = c(NA, rep(c('A', 'B'), 4), NA),
Job.Type.1998.1 = c(NA, rep(c('A', 'B'), 4), NA),
Job.Type.1998.2 = c(NA, rep(c('A', 'B'), 4), NA)
)
and this is how I gather() it,
myData1 %>% gather(key, value, -id) %>%
extract(col = key, into = c("variable", "id.job"), regex = "(.*?\\..*?)\\.(.)$") %>%
spread(variable, value)
#> # A tibble: 30 x 6
#> id id.job Job.Type.1997 Job.Type.1998 Wage.1997 Wage.1998
#> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 1 <NA> <NA> <NA> <NA>
#> 2 1 2 <NA> <NA> <NA> <NA>
#> 3 1 3 <NA> <NA> <NA> <NA>
#> 4 2 1 <NA> A 32 42
#> 5 2 2 A A 12 2
#> 6 2 3 <NA> <NA> <NA> 42
#> 7 3 1 <NA> B 33 43
#> 8 3 2 B B 13 3
#> 9 3 3 <NA> <NA> <NA> 43
#> 10 4 1 <NA> A 34 44
#> # ... with 20 more rows
It works, I suspect I overdoing it with the regex, but it works. However, my real data can have either one or two digest at the end, i.e.
The second data, where I get stuck,
myData2 <- tibble(
id = 1:10,
Wage.1997.1 = c(NA, 32:38, NA, NA),
Wage.1997.12 = c(NA, 12:18, NA, NA),
Wage.1998.1 = c(NA, 42:48, NA, NA),
Wage.1998.12 = c(NA, 2:8, NA, NA),
Wage.1998.13 = c(NA, 42:48, NA, NA),
Job.Type.1997.1 = NA,
Job.Type.1997.12 = c(NA, rep(c('A', 'B'), 4), NA),
Job.Type.1998.1 = c(NA, rep(c('A', 'B'), 4), NA),
Job.Type.1998.12 = c(NA, rep(c('A', 'B'), 4), NA)
)
Now, this is where I use (0[0-1]|1[0-9])$ for the second group, I also tried thing like \d{1}|\d{2}, but did that not work either.
myData2 %>% gather(key, value, -id) %>%
extract(col = key, into = c("variable", "id.job"),
regex = "(.*?\\..*?)\\.(0[0-1]|1[0-9])$") %>%
spread(variable, value)
The expected output would be something like this,
#> # A tibble: 30 x 6
#> id id.job Job.Type.1997 Job.Type.1998 Wage.1997 Wage.1998
#> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 1 <NA> <NA> <NA> <NA>
#> 2 1 12 <NA> <NA> <NA> <NA>
#> 3 1 13 <NA> <NA> <NA> <NA>
#> 4 2 1 <NA> A 32 42
#> 5 2 12 A A 12 2
#> 6 2 13 <NA> <NA> <NA> 42
#> 7 3 1 <NA> B 33 43
#> 8 3 12 B B 13 3
#> 9 3 13 <NA> <NA> <NA> 43
#> 10 4 1 <NA> A 34 44
#> # ... with 20 more rows
A simply solution à la t this question using select helpers like starts_with(), ends_with(), matches(), etc. would be appreciated.

Answer 1

We can change the regex in extract to match characters and capture as group ((.*)) from the start (^) of the string followed by a dot (\\.) and one or more characters that are not a dot captured as a group (([^.]+)) till the end ($) of the string
myData2 %>%
gather(key, value, -id) %>%
extract(col = key, into = c("variable", "id.job"), "^(.*)\\.([^.]+)$") %>%
spread(variable, value)
# A tibble: 30 x 6
# id id.job Job.Type.1997 Job.Type.1998 Wage.1997 Wage.1998
# * <int> <chr> <chr> <chr> <chr> <chr>
# 1 1 1 <NA> <NA> <NA> <NA>
# 2 1 12 <NA> <NA> <NA> <NA>
# 3 1 13 <NA> <NA> <NA> <NA>
# 4 2 1 <NA> A 32 42
# 5 2 12 A A 12 2
# 6 2 13 <NA> <NA> <NA> 42
# 7 3 1 <NA> B 33 43
# 8 3 12 B B 13 3
# 9 3 13 <NA> <NA> <NA> 43
#10 4 1 <NA> A 34 44
# ... with 20 more rows