R/fct_clean_dfp_itr_data.R

In msperlin/GetCVMData: Reading Annual and Quarterly Financial Reports from CVM

#' Cleans ITR/DFP table
#'
#' @param file_in path of csv file
#' @param df_in A itr/dpf dataframe
#'
#' @return A Clean dataframe
#' @export
#'
#' @examples
#'
#' \dontrun{
#' # no example
#' }
#'
clean_dfp_itr_data <- function(df_in, file_in) {

  message('\t\t\tCleaning table' )

  # filter penultimo cases
  possible_cases <- sort(unique(df_in$ORDEM_EXERC))

  idx <- df_in$ORDEM_EXERC == possible_cases[2]
  df_in <- df_in[idx, ]

  # change order of columns
  my_cols <- names(df_in)
  full_cols <- c("CNPJ_CIA", "CD_CVM", "DT_REFER", "DT_INI_EXERC", "DT_FIM_EXERC",
                  "DENOM_CIA", "VERSAO", "GRUPO_DFP",
                  "MOEDA", "ESCALA_MOEDA", "ORDEM_EXERC",
                  "CD_CONTA", "DS_CONTA", "VL_CONTA", "COLUNA_DF")

  missing_cols <- full_cols[!(full_cols %in% my_cols)]

  if (length(missing_cols) !=0 ) {
    df_in[, missing_cols] <- NA
  }

  df_in <- df_in[, full_cols]

  # set filename
  df_in$source_file <- basename(file_in)

  # set col for cnpj number (deprecated)

  #unique_cnpj <- unique(df$CNPJ_CIA)
  #number_cnpj <- sapply(unique_cnpj, fix_cnpj)

  #idx <- match(df$CNPJ_CIA, unique_cnpj)
  #df$cnpj_number <- number_cnpj[idx]

  return(df_in)

}