Lifted straight from Steve Miller's stevemisc package (v1.4.1). This recodes a numeric vector, character vector, or factor according to fairly simple recode specifications that former Stata users will appreciate. Yes, this is taken from John Fox's `recode()` function in his car package. I'm going with `carrec()` (i.e. shorthand for `car::recode()`, phonetically here: "car-wreck") for this package.
The goal here is to minimize the number of function clashes with multiple packages that I use in my workflow. For example: car, dplyr, and Hmisc all have `recode()` functions. I rely on the car package just for this function, but it conflicts with some other tidyverse functions that are vital to my workflow.
Arguments
- var
numeric vector, character vector, or factor
- recodes
character string of recode specifications: see below, but former Stata users will find this stuff familiar
- as_fac
return a factor; default is `TRUE` if `var` is a factor, `FALSE` otherwise
- as_num
if `TRUE` (which is the default) and `as.factor` is `FALSE`, the result will be coerced to a numeric if all values in the result are numeric. This should be what you want in majority of applications for regression analysis.
- levels
an optional argument specifying the order of the levels in the returned factor; the default is to use the sort order of the level names.
- ...
optional, only to make the shortcut (`carr()`) work
Details
Recode specifications appear in a character string, separated by semicolons (see the examples below), of the form input=output. If an input value satisfies more than one specification, then the first (from left to right) applies. If no specification is satisfied, then the input value is carried over to the result. NA is allowed on input and output.
References
Fox, J. and Weisberg, S. (2019). An R Companion to Applied Regression, Third Edition, Sage.
Examples
x <- seq(1,10)
carrec(x,"0=0;1:2=1;3:5=2;6:10=3")
#> [1] 1 1 2 2 2 3 3 3 3 3