R/to-be-deprecated.R

In Skomim/COVID_trajectory_Madison: Used to calculate sub-state metrics relating to the COVID-19 pandemic

#' OBSOLETE - VERSION Process the shaped confirmed case data.frame into a Tableau ready format
#'
#' @param clean_case_df shaped case data produced by \code{\link{shape_case_data}}
#'
#' @return a Tableau ready data.frame with the following columns:
#' \describe{
#'   \item{}{}
#'   \item{}{}
#'   \item{}{}
#'   \item{}{}
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#' }
#'
#' @export
#'
#' @importFrom dplyr mutate
#' @importFrom dplyr select
#' @importFrom dplyr ungroup
#' @importFrom dplyr if_else
#' @importFrom rlang .data
#'
#' @examples
#' library(dplyr)
#'
#' output <- pull_histTable() %>%
#'   shape_case_data() %>%
#'   process_confirmed_cases()
OLD_process_confirmed_cases <- function(clean_case_df) {
  dplyr::ungroup(clean_case_df) %>%
    dplyr::mutate(
      Count = .data$case_weekly_1 + .data$case_weekly_2,
      Burden = score_burden(curr = .data$case_weekly_1,
                            prev = .data$case_weekly_2,
                            pop = .data$pop_2018),
      Burden_Class = class_burden(.data$Burden),
      Trajectory = score_trajectory(curr = .data$case_weekly_1,
                                    prev = .data$case_weekly_2),
      Trajectory_P = pval_trajectory(curr = .data$case_weekly_1,
                                     prev = .data$case_weekly_2),
      Trajectory_Class = class_trajectory(traj = .data$Trajectory,
                                          pval = .data$Trajectory_P),
      Trajectory_FDR = fdr_trajectory(pval = .data$Trajectory_P),
      Composite_Class = confirmed_case_composite(traj_class = .data$Trajectory_Class,
                                                 burd_class = .data$Burden_Class)

    ) %>%
    dplyr::mutate(
      Trajectory = signif(.data$Trajectory, 2),
      Trajectory = dplyr::if_else(.data$Trajectory_Class == "No significant change", "N/A",
                                  as.character(.data$Trajectory)),
      Burden = signif(.data$Burden, 2),
      RowType = "Summary"
    ) %>%
    dplyr::select(
      Date = .data$week_end_1,
      Region_ID = .data$fips,
      Region = .data$geo_name,
      RowType = .data$RowType,
      Conf_Case_Count = .data$Count,
      Conf_Case_Burden = .data$Burden,
      Conf_Case_Trajectory = .data$Trajectory,
      Conf_Case_Burden_Class = .data$Burden_Class,
      Conf_Case_Trajectory_Class = .data$Trajectory_Class,
      Conf_Case_Composite_Class = .data$Composite_Class,
      Conf_Case_Trajectory_P = .data$Trajectory_P,
      Conf_Case_Trajectory_FDR = .data$Trajectory_FDR
    )
}