tibble_func_1 <- function(x) {
y = as_tibble(x)
return (y) }
tibble_func_2 <- function (meta) {
empty_vec <- vector(mode = 'list', length = length(meta$step))
tibbles <- purrr::map(empty_vec, tibble_func_1)
return(tibbles) }
rename_func <- function (data, old_name, new_name){
renamed <- data %>%
rename({{new_name}} := old_name)
return(renamed)}
#' Rename Function
#' Renames variables to new variable name
#' @param raw Raw data
#' @param scoresheet scoresheet
#'
#' @return table with renamed variables
#' @export
rename_vars <- function (raw, scoresheet) {
#from the scoresheet file - filter rows where the variables need to be renamed
raw_data <-raw
#filter rows of the scoresheet where the operation is 'recode'
scoresheet1 <- scoresheet %>%
filter (scoresheet$operation == 'rename')
#loop through the rename function, using the arguments defined in the scoresheet file and using the functions above
i <- 1
m <- 2
x <- ((length(scoresheet1$step) + 1))
tibbles <- tibble_func_2(scoresheet1)
tibbles[[1]] <- raw_data
while (i < x) {
raw_var <- scoresheet1$raw_vars[[i]]
new_var <- scoresheet1$new_var[i]
data_for_fun <- tibbles[[i]]
tibbles[[m]] <- rename_func(data = data_for_fun, old_name = raw_var, new_name = {{new_var}})
i <- i+1
m <- m+1}
return(tibbles[[x]]) }
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