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#
#' Poverty Probability Index (PPI) lookup table for Guatemala
#'
#' @format A data frame with 17 columns and 101 rows:
#' \describe{
#' \item{\code{score}}{PPI score}
#' \item{\code{nlFood}}{Food poverty line}
#' \item{\code{nl100}}{National poverty line (100\%)}
#' \item{\code{nl150}}{National poverty line (150\%)}
#' \item{\code{nl200}}{National poverty line (200\%)}
#' \item{\code{half100}}{Poorest half below 100\% national}
#' \item{\code{ppp125}}{Below $1.25 per day purchasing power parity (2005)}
#' \item{\code{ppp200}}{Below $2.00 per day purchasing power parity (2005)}
#' \item{\code{ppp250}}{Below $2.50 per day purchasing power parity (2005)}
#' \item{\code{ppp500}}{Below $5.00 per day purchasing power parity (2005)}
#' \item{\code{ppp190}}{Below $1.90 per day purchasing power parity (2011)}
#' \item{\code{ppp310}}{Below $3.10 per day purchasing power parity (2011)}
#' \item{\code{percentile20}}{Below 20th percentile poverty line}
#' \item{\code{percentile40}}{Below 40th percentile poverty line}
#' \item{\code{percentile50}}{Below 50th percentile poverty line}
#' \item{\code{percentile60}}{Below 60th percentile poverty line}
#' \item{\code{percentile80}}{Below 80th percentile poverty line}
#' }
#'
#' @examples
#' # Access Guatemala PPI table
#' ppiGTM2016
#'
#' # Given a specific PPI score (from 0 - 100), get the row of poverty
#' # probabilities from PPI table it corresponds to
#' ppiScore <- 50
#' ppiGTM2016[ppiGTM2016$score == ppiScore, ]
#'
#' # Use subset() function to get the row of poverty probabilities corresponding
#' # to specific PPI score
#' ppiScore <- 50
#' subset(ppiGTM2016, score == ppiScore)
#'
#' # Given a specific PPI score (from 0 - 100), get a poverty probability
#' # based on a specific poverty definition. In this example, the national
#' # poverty line definition
#' ppiScore <- 50
#' ppiGTM2016[ppiGTM2016$score == ppiScore, "nl100"]
#'
#' @source \url{https://www.povertyindex.org}
#'
#
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"ppiGTM2016"
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#
#' Poverty Probability Index (PPI) lookup table for Guatemala for 2023
#'
#' @format A data frame with 17 columns and 101 rows:
#' \describe{
#' \item{\code{score}}{PPI score}
#' \item{\code{ppp190}}{Below $1.90 per day purchasing power parity (2011)}
#' \item{\code{ppp320}}{Below $3.20 per day purchasing power parity (2011)}
#' \item{\code{ppp550}}{Below $5.50 per day purchasing power parity (2011)}
#' \item{\code{ppp215}}{Below $2.15 per day purchasing power parity (2017)}
#' \item{\code{ppp365}}{Below $3.65 per day purchasing power parity (2017)}
#' \item{\code{ppp685}}{Below $6.85 per day purchasing power parity (2017)}
#' \item{\code{percentile20}}{Below 20th percentile poverty line}
#' \item{\code{percentile40}}{Below 40th percentile poverty line}
#' \item{\code{percentile60}}{Below 60th percentile poverty line}
#' \item{\code{percentile80}}{Below 80th percentile poverty line}
#' }
#'
#' @examples
#' # Access Guatemala PPI table
#' ppiGTM2023
#'
#' # Given a specific PPI score (from 0 - 100), get the row of poverty
#' # probabilities from PPI table it corresponds to
#' ppiScore <- 50
#' ppiGTM2023[ppiGTM2023$score == ppiScore, ]
#'
#' # Use subset() function to get the row of poverty probabilities corresponding
#' # to specific PPI score
#' ppiScore <- 50
#' subset(ppiGTM2023, score == ppiScore)
#'
#' # Given a specific PPI score (from 0 - 100), get a poverty probability
#' # based on a specific poverty definition. In this example, the national
#' # poverty line definition
#' ppiScore <- 50
#' ppiGTM2023[ppiGTM2023$score == ppiScore, "ppp190"]
#'
#' @source \url{https://www.povertyindex.org}
#'
#
################################################################################
"ppiGTM2023"
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