R/V4_T2.2.R

In Shelmith-Kariuki/rKenyaCensus: 2019 Kenya Population and Housing Census Results

#' Volume 4: Table 2.2
#'
#' Table 2.2: Distribution of Population Age 3 Years and Above by School Attendance Status,
#' Area of Residence, Sex, County and Sub-County
#' @docType data
#'
#' @usage data(V4_T2.2)
#'
#' @format A data frame with 14 variables
#' \describe{
#' \item{\code{County}}{County}
#' \item{\code{Gender}}{Gender}
#' \item{\code{Total}}{Total}
#' \item{\code{StillinSchool_No.}}{Number of persons still in school / a learning institution.}
#' \item{\code{StillinSchool_Perc}}{Percentage of personsstill in school / a learning institution.}
#' \item{\code{LeftSchoolAfterC_No.}}{Number of persons who left school / a learning institution, after completion.}
#' \item{\code{LeftSchoolAfterC_Perc}}{Percentage of persons who left school / a learning institution, after completion.}
#' \item{\code{LeftSchoolBeforeC_No.}}{Number of persons who left school / a learning institution, before completion.}
#' \item{\code{LeftSchoolBeforeC_Perc}}{Percentage of persons who left school / a learning institution, before completion.}
#' \item{\code{NeverbeentoSchool_No.}}{Number of persons who have never been to a school / a learning institution.}
#' \item{\code{NeverbeentoSchool_Perc}}{Percentage of persons who have never been to a school / a learning institution.}
#' \item{\code{...}}{The other variables indicate situations where the state of school attendance is not known / not stated.}
#'
#' Intersex population is excluded from the table since it is too small to be distributed at sub-national level.
#' }
#' @keywords datasets
"V4_T2.2"