I have a data.table, DT containing one string variable, s, from which I want to create additional variables based on the positions of each character in s. The varname, start and end positions and vartype of each variable are given in a dictionary, dic. Here is an example, including the desired output:
DT <- DT <- data.table(s=c('a191','b292','c393'))
dic <- data.table(varname=c('bla,ble,bli'),start=c(1,2,3),end=c(1,2,4),vartype=c('c','i','i')
DTdesired <- data.table(bla=c('a','b','c'),ble=c(1,2,3),bli=c(91,92,93))
This is the same problem as importing data from a fixed width file (fwf), which has been covered in this SO question. The answer to that post includes a data table solution
DT[ , lapply(seq_len(length(cols$beg)), function(ii) {
stri_sub(V1, cols$beg[ii], cols$end[ii])
})]
But I am looking for a solution that besides start and end would also use the varname and coltype variables of the dictionary
Edit: In reality, DT would be a large Census file, around 200 million observations. Each element of s is a string with 200 characters. And the dictionary, dic, can contain about 10 to 50 variables to be extracted, depending on the year.
We can use Map to do the conversion. (added the updated function created by @LucasMation)
library(magrittr)
library(data.table)
subtr_typeconvert <- function(x, y)
{
DT$s %>%
substr(x, y) %>%
type.convert(as.is = TRUE)
}
dic[, setNames(Map(function(x, y)
subtr_typeconvert(x,y), start, end), varname)]