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runits-of-measurementexponent

Converting unit abbreviations to numbers


I have a dataset that abbreviates numerical values in a column. For example, 12M mean 12 million, 1.2k means 1,200. M and k are the only abbreviations. How can I write code that allows R to sort these values from lowest to highest?

I've though about using gsub to convert M to 000,000 etc but that does not take into account the decimals (1.5M would then be 1.5000000).


Solution

    • So you want to translate SI unit abbreviations ('K','M',...) into exponents, and thus numerical powers-of-ten. Given that all units are single-letter, and the exponents are uniformly-spaced powers of 10**3, here's working code that handles 'Kilo'...'Yotta', and any future exponents:
        > 10 ** (3*as.integer(regexpr('T', 'KMGTPEY')))
        [1] 1e+12
    

    Then just multiply that power-of-ten by the decimal value you have.

    • Also, you probably want to detect and handle the 'no-match' case for unknown letter prefixes, otherwise you'd get a nonsensical -1*3
        > unit_to_power <- function(u) {
            exp_ <- 10**(as.integer(regexpr(u, 'KMGTPEY')) *3)
            return (if(exp_>=0) exp_ else 1)
        }
    
    • Now if you want to case-insensitive-match both 'k' and 'K' to Kilo (as computer people often write, even though it's technically an abuse of SI), then you'll need to special-case e.g with if-else ladder/expression (SI units are case-sensitive in general, 'M' means 'Mega' but 'm' strictly means 'milli' even if disk-drive users say otherwise; upper-case is conventionally for positive exponents). So for a few prefixes, @DanielV's case-specific code is better.

    • If you want negative SI prefixes too, use as.integer(regexpr(u, 'zafpnum@KMGTPEY')-8) where @ is just some throwaway character to keep uniform spacing, it shouldn't actually get matched. Again if you need to handle non-power-of-10**3 units like 'deci', 'centi', will require special-casing, or the general dict-based approach WeNYoBen uses.

    • base::regexpr is not vectorized also its performance is bad on big inputs, so if you want to vectorize and get higher-performance use stringr::str_locate.