R/transformVotes.R

In danielmarcelino/CamaraBR: Download, Unpack and Tidy Legislative Data from the Brazilian Chamber of Deputies

if (getRversion() >= "2.15.1")
  utils::globalVariables(c(".data", ".cols"))
#' Transform the database of rollcall votes
#'
#' Transform a database of rollcall votes, use only after downloading data with `buildRollcallDataset`
#'
#' @param .data the data frame
#' @param filter a logical, if TRUE, only rollcall votes with government orientation is returned. So "liberado" or missing cases are filtered from data output.
#'
#' @importFrom dplyr mutate
#' @importFrom dplyr filter
#' @importFrom stringr str_detect
#' @importFrom stringi stri_trans_general
#'
#' @export
transformVotes <- function(.data,  filter = FALSE) {
  if (is.null(.data)) {
    stop("Need a data frame to perform vote transformation")
  }
  
  .data <- dplyr::mutate(
    .data,
    Governo = stringi::stri_trans_general(Governo, "Latin-ASCII"),
    legislator_vote = stringi::stri_trans_general(legislator_vote, "Latin-ASCII"),
    legislator_name = stringi::stri_trans_general(legislator_name, "Latin-ASCII")
  )
  
  .data <- dplyr::mutate(.data, Governo = ifelse(Governo == "Sim", 1,
                                                 ifelse(
                                                   Governo == "Nao",
                                                   0,
                                                   ifelse(Governo == "Liberado", NA_integer_, Governo)
                                                 )) %>% as.integer())
  
  .data <-
    dplyr::mutate(.data,
                  legislator_vote = ifelse(
                    legislator_vote == "Sim",
                    1,
                    ifelse(legislator_vote == "Nao", 0,
                           ifelse(
                             (legislator_vote == "Obstrucao" && !is.na(Governo)),
                             abs(Governo - 1),
                             legislator_vote
                           ))
                  ) %>% as.integer())
  
  if (filter) {
    .dados <-
      .data %>% dplyr::filter(Governo == 1 |
                                Governo == "1" | Governo == 0 | Governo == "0")
  }
  
  .dados <-
    dplyr::mutate(.data, governismo = ifelse(Governo == legislator_vote, 1, 0))
  
  return(.dados)
}
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