Perform dictionary-based cleaning

Usage

clean_using_dictionary(data, dictionary)

Arguments

data

The input <data.frame> or <linelist>

dictionary

A <data.frame> with the dictionary associated with the input data. This is expected to be compatible with the matchmaker package and must contain the following four columns:

options: This column contains the current values used to represent the different groups in the input data frame (required).
values: The values that will be used to replace the current options (required).
grp: The name of the columns where every option belongs to (required).
orders: This defines the user-defined order of different options (optional).

Value

A <data.frame> or <linelist> where the target options have been replaced with their corresponding values in the columns specified in the data dictionary.

Examples

data <- readRDS(
  system.file("extdata", "messy_data.RDS", package = "cleanepi")
)
dictionary <- readRDS(
  system.file("extdata", "test_dict.RDS", package = "cleanepi")
)

# adding an option that is not defined in the dictionary to the 'gender'
# column
data$gender[2] <- "homme"
cleaned_df <- clean_using_dictionary(
  data = data,
  dictionary = dictionary
)
#> ! Cannot replace "homme" present in column gender but not defined in the dictionary.
#> ℹ You can either:
#> • correct the misspelled option from the input data, or
#> • add it to the dictionary using the `add_to_dictionary()` function.

# print the report
print_report(cleaned_df, "misspelled_values")
#>   idx column value
#> 1   2 gender homme