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#
#' Poverty Probability Index (PPI) lookup table for Papua New Guinea 2023
#'
#' @format A data frame with 9 columns and 101 rows:
#' \describe{
#' \item{\code{score}}{PPI score}
#' \item{\code{percentile20_wi}}{Below 20th percentile wealth index}
#' \item{\code{percentile40_wi}}{Below 40th percentile wealth index}
#' \item{\code{percentile60_wi}}{Below 60th percentile wealth index}
#' \item{\code{percentile80_wi}}{Below 80th percentile wealth index}
#' \item{\code{percentile20_wi_ur}}{Below 20th percentile wealth index urban/rural}
#' \item{\code{percentile40_wi_ur}}{Below 40th percentile wealth index urban/rural}
#' \item{\code{percentile60_wi_ur}}{Below 60th percentile wealth index urban/rural}
#' \item{\code{percentile80_wi_ur}}{Below 80th percentile wealth index urban/rural}
#' }
#'
#' @examples
#' # Access Papua New Guinea PPI table
#' ppiPNG2023
#'
#' # Given a specific PPI score (from 0 - 100), get the row of poverty
#' # probabilities from PPI table it corresponds to
#' ppiScore <- 50
#' ppiPNG2023[ppiPNG2023$score == ppiScore, ]
#'
#' # Use subset() function to get the row of poverty probabilities corresponding
#' # to specific PPI score
#' ppiScore <- 50
#' subset(ppiPNG2023, score == ppiScore)
#'
#' # Given a specific PPI score (from 0 - 100), get a poverty probability
#' # based on a specific poverty definition. In this example, the USAID
#' # extreme poverty definition
#' ppiScore <- 50
#' ppiPNG2023[ppiPNG2023$score == ppiScore, "percentile20_wi"]
#'
#' @source \url{https://www.povertyindex.org}
#'
#
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"ppiPNG2023"
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