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Clean up categories and groups from crosstabs

clean_cws_lvls.Rd

This is a bunch of string cleaning to standardize the categories (Gender, Age, etc) and groups (Male, Ages 65+, etc) across all available crosstabs. This does the same operation on both categories and groups because there is some overlap. The lists of regex and other replacements aren't exported, but they aren't hidden either: access them at dcws:::to_replace, dcws:::to_remove, dcws:::to_recode, or dcws:::to_collapse if you need them.

Usage

clean_cws_lvls(x, is_category = FALSE, order = FALSE)

Arguments

x

A vector. If not a factor already, will be coerced to one.

is_category

Boolean: if FALSE, assume these are groups (e.g. "High school or less", "Some college or Associate's") rather than categories (e.g. "Education").

order

Boolean: if TRUE, groups will be put into logical order (e.g. <$30K, $30K-$100K). This only applies to groups (i.e. is_category = FALSE), and only really affects ages and income groups. If FALSE (default), levels will be kept in the same order as they were received.

Value

A factor of the same length as x

Examples

# vector of strings as read in from crosstabs
categories <- c(
    "Connecticut", "NH Inner Ring", "Gender", "Age",
    "Race/Ethnicity", "Education", "Income", "Children in HH"
)
levels(clean_cws_lvls(categories, is_category = TRUE))
#> [1] "Connecticut"          "New Haven Inner Ring" "Gender"              
#> [4] "Age"                  "Race/Ethnicity"       "Education"           
#> [7] "Income"               "With children"       

groups <- c(
    "M", "F", "18-34", "35 to 49", "65 and older",
    "Black/Afr Amer", "African American/Black", "High School",
    "Less than $15,000", "$15,000 to $30,000", "No"
)
levels(clean_cws_lvls(groups))
#>  [1] "Male"        "Female"      "Ages 18-34"  "Ages 35-49"  "Ages 65+"   
#>  [6] "Black"       "High school" "<$15K"       "$15K-$30K"   "No kids"