Apply a variable dictionary to a dataset. Each column is replaced with a new name and a corresponding label attribute is applied.

Usage

update_columns(
  data,
  dict,
  old = NULL,
  new = NULL,
  label = NULL,
  reorder = FALSE
)

Arguments

data: A data.frame-like object
dict: A data.frame-like object or .csv file path (.csv, .txt, .xlsx, .rds). Should have 3 columns specifying: old names, new names, and labels. The order that columns appear in $old determines the final ordering in the cleaned data.
old: Column name in dict with old column names (default "old")
new: Column name in dict with new column names (default "new")
label: Column name in dict with human-readable labels (default "label")
reorder: Logical, default FALSE. If TRUE, columns listed in the dictionary will be reordered according to the order they appear in the dictionary. Columns not referenced in the dictionary remain at the end in their original order.

Value

A data.frame with renamed columns and labels applied

Examples

data("data_patient", package = "thekidsbiostats")

# 1) Create a data dictionary and formulate some cleaned column names, assign to `dict` object
dict <- make_column_dict(data_patient, auto_clean = TRUE, quiet = FALSE)
#> dict_patient <- tribble(
#>   ~old, ~new, ~label,
#>   'Patient ID#', 'patient_id_number', '',
#>   'DOB [YYYY-MM-DD]', 'dob_yyyy_mm_dd', '',
#>   'Sex (0=Male, 1=Female)', 'sex_0_male_1_female', '',
#>   'WHAT IS YOUR HEIGHT? (cm)', 'what_is_your_height_cm', '',
#>   'WHAT IS YOUR CURRENT WEIGHT? (kg)', 'what_is_your_current_weight_kg', '',
#>   'Do you currently smoke any form of tobacco products, including cigarettes, cigars, or pipes, on a regular basis?', 'do_you_currently_smoke_any_form_of_tobacco_products_including_cigarettes_cigars_or_pipes_on_a_regular_basis', '',
#>   'bp (mmHg)', 'bp_mm_hg', '',
#>   'Cholesterol / mmolL', 'cholesterol_mmol_l', '',
#> ) 

# 2) Apply column names to data, assign to `data_patient_clean`
data_patient_clean <- update_columns(data_patient, dict = dict)