Break string into several columns using tidyr::extract regex - regex

Question

I'm trying to break a string vector into several variables using regular expressions in R, preferably in a dplyr-tidyr way using the tidyr::extract command. For insctance in the vector bellow:
sasdic <- data.frame(a=c(
'#1 ANO_CENSO 5. /*Ano do Censo*/',
'#71 TP_SEXO $Char1. /*Sexo*/',
'#72 TP_COR_RACA $Char1. /*Cor/raça*/',
'#74 FK_COD_PAIS_ORIGEM 4. /*Código País de origem*/' ))
I would like for the:
first number ([0-9]+) to go to variable "int_pos"
the variable name connected by undersline ([a-zA-Z_]+) to go to variable "var_name"
The second number or the term $Char1 (could be $Char2, etc) to go to var "x". I figured ([0-9]+|$Char[0-9]+) could select this?
Lastly, whatever comes in between "/* ... /" to go to variable "label" (don´t know the regex for this).
All other intermidiate caracters (blank spaces, ".", "/", "" should be disconsidered)
This would be the result
d <- data.frame(int_pos=c(1,72,72,74),
var_name=c('ANO_CENSO','TP_SEXO','TP_COR_RACA','FK_COD_PAIS_ORIGEM'),
x=c('5','Chart1','$Char1','4'),
label=c('Ano do Censo','Sexo','Cor/raça','Código País de origem') )
I tryed to construct a regular expression for this. This is what I got so far:
sasdic %>% extract(a, c('int_pos','var_name','x','label'),
"([0-9]+)([a-zA-Z_]+)([0-9]+|$Char[0-9]+)(something to get the label")
-> d
above the regular expression is incomplete. Also, I don't know hot to make explicit in the extract command syntax, what are the parts to be recovered and what are the parts to leave out.

Answer 1

In the regex used, we are matchng one more more punctuation characters ([[:punct:]]+) i.e. # followed by capturing the numeric part ((\\d+) - this will be our first column of interest), followed by one or more white-space (\\s+), followed by the second capture group (\\S+ - one or more non white-space character i.e. "ANO_CENSO" for the first row), followed by space (\\s+), then we capture the third group (([[:alum:]$]+) - i.e. one or more characters that include the alpha numeric along with $ so as to match $Char1), next we match one or more characters that are not a letter ([^A-Za-z]+- this should get rid of the space and *) and the last part we capture one or more characters that are not * (([^*]+).
sasdic %>%
extract(a, into=c('int_pos', 'var_name', 'x', 'label'),
"[[:punct:]](\\d+)\\s+(\\S+)\\s+([[:alnum:]$]+)[^A-Za-z]+([^*]+)")
# int_pos var_name x label
#1 1 ANO_CENSO 5 Ano do Censo
#2 71 TP_SEXO $Char1 Sexo
#3 72 TP_COR_RACA $Char1 Cor/raça
#4 74 FK_COD_PAIS_ORIGEM 4 Código País de origem

Answer 2

This is another option, though it uses the data.table package instead of tidyr:
library(data.table)
setDT(sasdic)
# split label
sasdic[, c("V1","label") := tstrsplit(a, "/\\*|\\*/")]
# remove leading "#", split remaining parts
sasdic[, c("int_pos","var_name","x") := tstrsplit(gsub("^#","",V1)," +")]
# remove unneeded columns
sasdic[, c("a","V1") := NULL]
sasdic
# label int_pos var_name x
# 1: Ano do Censo 1 ANO_CENSO 5.
# 2: Sexo 71 TP_SEXO $Char1.
# 3: Cor/raça 72 TP_COR_RACA $Char1.
# 4: Código País de origem 74 FK_COD_PAIS_ORIGEM 4.
This assumes that the "remaining parts" (aside from the label) are space-separated.
This could also be done in one block (which is what I would do):
sasdic[, c("a","label","int_pos","var_name","x") := {
x = tstrsplit(a, "/\\*|\\*/")
x1s = tstrsplit(gsub("^#","",x[[1]])," +")
c(list(NULL), x1s, x[2])
}]

Answer 3

You could use the package unglue :
library(unglue)
unglue_unnest(sasdic, a, "#{int_pos}{=\\s+}{varname}{=\\s+}{x}.{=\\s+}/*{label}*/")
#> int_pos varname x label
#> 1 1 ANO_CENSO 5 Ano do Censo
#> 2 71 TP_SEXO $Char1 Sexo
#> 3 72 TP_COR_RACA $Char1 Cor/ra<e7>a
#> 4 74 FK_COD_PAIS_ORIGEM 4 C<f3>digo Pa<ed>s de origem