#' Indicator selection
#'
#' @param df data frame to review
#' @param opunit operatingunit
#' @importFrom dplyr %>%
#' @export
rw_pairdown <- function(df, opunit){
#filter to selected OU
df <- dplyr::filter(df, operatingunit == opunit)
#identify current period
curr_pd <- ICPIutilities::identifypd(df)
#identify Q3 indicators
ind_list <- df %>%
dplyr::filter(standardizeddisaggregate == "Total Numerator") %>%
dplyr::group_by(indicator) %>%
dplyr::summarise_at(dplyr::vars(curr_pd), ~ sum(., na.rm = TRUE)) %>%
dplyr::ungroup() %>%
dplyr::filter_at(dplyr::vars(curr_pd), dplyr::any_vars(.!= 0)) %>%
dplyr::filter(!indicator %in% c("PMTCT_EID_Less_Equal_Two_Months", "PMTCT_EID_Two_Twelve_Months",
"PMTCT_STAT_KnownatEntry_POSITIVE", "PMTCT_STAT_NewlyIdentified_Negative",
"PMTCT_STAT_NewlyIdentified_POSITIVE", "PMTCT_HEI_POS", "HTS_TST_NEG")) %>%
dplyr::pull(indicator)
#filter df to include indicators reported in pd and only numerator or relevant disaggs
df <- dplyr::filter(df,
indicator %in% ind_list,
standardizeddisaggregate == "Total Numerator" |
(indicator == "VMMC_CIRC" & standardizeddisaggregate == "Age/Sex") |
(indicator %in% c("HTS_TST", "HTS_TST_POS") &
standardizeddisaggregate %in% c("Modality/Age Aggregated/Sex/Result", "Modality/Age/Sex/Result")))
}
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