#' @title Education data from Pakistan Social and Living Standards Measurement 2015-16
#' @name Education
#' @docType data
#' @keywords datasets
#' @usage data(Education)
#' @description \code{Education} data from Pakistan Social and Living Standards Measurement 2015-16.
#' @format A \code{data.table} and \code{data.frame} with 141828 observations of 22 variables.
#'
#' \describe{
#' \item{\code{hhcode}}{Household 10 digits code.}
#' \item{\code{Province}}{Province of Pakistan}
#' \item{\code{Region}}{Region of Pakistan (Rural/Urban)}
#' \item{\code{PSU}}{primary sampling unit 8 digits code}
#' \item{\code{idc}}{Identity code of household member}
#' \item{\code{s2ac01}}{Can read with understanding}
#' \item{\code{s2ac02}}{Can Write with understanding}
#' \item{\code{s2ac03}}{Can solve arithmatic questions}
#' \item{\code{s2ac04}}{Attended any educational institution}
#' \item{\code{s2ac05}}{Highest level of education passed}
#' \item{\code{s2ac06}}{Currently attending educational institution}
#' \item{\code{s2ac07}}{Currently studying class}
#' \item{\code{s2ac08}}{Type of currently attending institution}
#' \item{\code{s2ac9a}}{Last year expenditure on school Fees/Admission/Registration/Funds/Donations?}
#' \item{\code{s2ac9b}}{Last year expenditure on school Uniform?}
#' \item{\code{s2ac9c}}{Last year expenditure on school Books/stationery items?}
#' \item{\code{s2ac9d}}{Last year expenditure on school Examination Fee?}
#' \item{\code{s2ac9e}}{Last year expenditure on Private Tuition?}
#' \item{\code{s2ac9f}}{Last year expenditure on school transportation?}
#' \item{\code{s2ac9g}}{Last year expenditure on school hostel expenses?}
#' \item{\code{s2ac9h}}{Last year expenditure on school other expenses?}
#' \item{\code{s2ac9i}}{Total expenditure on schooling}
#' }
#' @author \enumerate{
#' \item Muhammad Yaseen (\email{myaseen208@gmail.com})
#' \item Muhammad Arfan Dilber (\email{pbsfsd041@gmail.com})
#' }
#' @references \enumerate{
#' \item Pakistan Bureau of Statistics, Micro data (\url{http://www.pbs.gov.pk/content/microdata}).
#' }
#'
#'
#'
#' @seealso
#' \code{\link{Agriculture}}
#' , \code{\link{Employment}}
#' , \code{\link{Expenditure}}
#' , \code{\link{HHRoster}}
#' , \code{\link{Housing}}
#' , \code{\link{ICT}}
#' , \code{\link{LiveStock}}
#'
#' @importFrom magrittr %>%
#' @importFrom dplyr group_by summarise
#' @importFrom ggplot2 ggplot
#'
#'
#' @examples
#' # library(PSLM2015)
#' # library(dplyr)
#' # data("Education")
#' # TotalP <- Education %>% group_by(Province, Region) %>%
#' # summarise(TotalPersons = n())
#' #
#' # literacy <- Education %>% filter(s2ac01 == "yes" & s2ac02 == "yes" & s2ac03 == "yes")
#' # literateP <- literacy %>%
#' # group_by(Province, Region) %>%
#' # summarise(literatePersons = n())
#' # literacyR <- TotalP %>% left_join(literateP, by = c("Province", "Region"))
#' # literacyRate <- mutate(literacyR, Rate = literatePersons/TotalPersons*100)
#' # library(ggplot2)
#' # ggplot(data = literacyRate, mapping = aes(x = Province, y = Rate)) +
#' # geom_col() +
#' # facet_grid(. ~ Region)
#' #
#' # # Merging two data files
#' #
#' # data("Employment")
#' # data("Education")
#' # income <- Employment %>% rowwise() %>%
#' # mutate(TotalIncome = sum((s1bq08*s1bq09),s1bq10,s1bq15,s1bq17,s1bq19,s1bq21, na.rm = TRUE))
#' # ab <- income %>% select(hhcode, idc, TotalIncome)
#' # EduEmp <- Education %>% left_join(ab, by = c("hhcode", "idc"))
#' # str(EduEmp)
#'
NULL
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