rescale_occupation: Rescale the Eurobarometer occupation variable
In antaldaniel/surveyreader: Data cleaning and integration for survey files

Description Usage Arguments Examples

The Eurobarometer occupations have three groups: none-active, self-employed, and employed occupations. If you only need this categorization, you should use the recatogorized version of this variable. The numeric recategorization keeps this grouping, giving numeric representations starting with digit 1 for none-active, 2 for self-employed and 3 for employed respondents. Keeping only the first digit will re-create the recoded version of this variable. The second digit is a unique numeric identifier, but the ordering of the numeric variable, or the differences between numeric codes have little if any meaning. This is a truly categorical variable. The return_class="factor" and return_class="character" give shorthened versions of the GESIS labels for easier handling in R. This is a wrapper function around the rescale_categories function.

1 2	rescale_occupation(column, from = NULL, to = NULL, na_labels = c("default"), return_class = "factor", underscore = TRUE)

`column`	A column from a survey data with the subjective urbanization answers.
`from`	Defaults to `c("NULL")` in which case the GESIS coding in English `c(..., "Retired, unable to work","Farmer", ...)` will be used.
`to`	Defaults to `NULL` in which case the GESIS coding will be shortened to `c(... "retired", "farmer" ...)`. If you choose `return_class = "numeric"` the default `to` parameter changes to `c(0,1,2)`.
`na_labels`	Defaults to `c("default")`.
`return_class`	Default is `"factor"`, alternatives `"character"` or `"numeric"`.
`underscore`	Defaults to `TRUE` in which case factor names or character strings contain underscore_between_words. This is a better approach for further programming, but you can choose `FALSE` for nicer printing results. See examples.

rescale_occupation (c("Owner of a shop, craftsmen, etc.",
                      "Retired, unable to work",
                      "Employed position, at desk",
                      "Employed professional (employed doctor, etc.)",
                      "DK"),
                    return_class = "character")

##Nicer printing factor names without underscore:

rescale_occupation (c("Owner of a shop, craftsmen, etc.",
                      "Retired, unable to work","DK"),
                    underscore = FALSE)

##Beware that the numeric representation is grouped but not ordered.

rescale_occupation (c("Owner of a shop, craftsmen, etc.",
                      "Retired, unable to work",
                      "Employed position, at desk",
                      "Employed professional (employed doctor, etc.)",
                      "DK"),
                    return_class = "numeric")