encode_binary_cats: Encode categorical variables as binary factors

In eHDPrep: Quality Control and Semantic Enrichment of Datasets

Encode categorical variables as binary factors

Description

In a data frame, converts binary categories to factors. Ordering of levels is standardised to: negative_finding, positive_finding. This embeds a standardised numeric relationship between the binary categories while preserving value labels.

Usage

encode_binary_cats(data, ..., values = NULL)

Arguments

data	A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr).
...	<tidy-select> One or more unquoted expressions separated by commas. Variable names can be used as if they were positions in the data frame, so expressions like x:y can be used to select a range of variables.
values	Optional named vector of user-defined values for binary values using binary_label_1 = binary_label_2 syntax (e.g. c("No" = "Yes") would assign level 1 to "No" and 2 to "Yes").

Details

Binary categories to convert can be specified with a named character vector, specified in values. The syntax of the named vector is: negative_finding = positive_finding. If values is not provided, the default list will be used: "No"="Yes", "No/unknown"="Yes", "no/unknown"="Yes", "Non-user"="User", "Never"="Ever", "WT"="MT", "Male"="Female", "male"="female", "M"="F", "m"="f", "FALSE"="TRUE", "false"="true", "0"="1", "rural"="urban", "Absent"="Present", "absent"="present", "Negative"="Positive", "negative"="positive".

Value

dataset with specified binary categories converted to factors.

Examples

# use built-in values. Note: rural_urban is not modified
# Note: diabetes is not modified because "missing" is interpreted as a third category.
# strings_to_NA() should be applied first
encode_binary_cats(example_data, hypertension, rural_urban)

# use custom values. Note: rural_urban is now modified as well.
encoded_data <- encode_binary_cats(example_data, hypertension, rural_urban,
                   values = c("No"= "Yes", "rural" = "urban"))

# to demonstrate the new numeric encoding:
dplyr::mutate(encoded_data, hypertension_num = as.numeric(hypertension), .keep = "used") 

eHDPrep documentation built on Oct. 21, 2026, 5:10 p.m.