Added a population dataset

R/ons_uk_population_2023.R

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+#' ONS Mid-2023 Population Estimate for UK
+#'
+#' ONS Population Estimates for Mid-year 2023
+#' National and subnational mid-year population estimates for the UK and its
+#'  constituent countries by administrative area, age and sex (including
+#'   components of population change, median age and population density).
+#'
+#' Data sourced from
+#' \href{https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland}
+#'
+#' @docType data
+#'
+#' @keywords datasets ons population
+#'
+#' @format Tibble with six columns
+#' \describe{
+#' \item{sex}{male or female}
+#' \item{Code}{The country/geography code}
+#' \href{Name}{country of the UK}
+#' \item{Geography}{Country}
+#' \item{age}{year of age}
+#' \item{count}{the number of people in this group}
+#' }
+#'
+#' @source \href{https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland}{ONS Estimates of the population for the UK, England, Wales, Scotland, and Northern Ireland}
+#'
+#' @usage data(ons_uk_population_2023)
+#'
+#' @examples
+#' data(ons_uk_population_2023)
+#'
+#' library(readxl)
+#' library(tidyverse)
+#' library(tidyr)
+
+#' Load the data in
+#' population_data_2023_f <- read_excel(
+#' "C:/Users/jacqueline.grout/Downloads/mye23tablesuk.xlsx",
+#'  sheet="MYE2 - Females",
+#'  skip = 7)
+
+#' population_data_2023_m <- read_excel(
+#'  "C:/Users/jacqueline.grout/Downloads/mye23tablesuk.xlsx",
+#'  sheet="MYE2 - Males",
+#'  skip = 7)
+
+
+#' pivot longer
+#' population_data_2023_f <- population_data_2023_f |>
+#'  select(!`All ages`) |>
+#'  pivot_longer(`0`:`90+`, names_to = "age", values_to = "count")
+
+#' population_data_2023_m <- population_data_2023_m |>
+#'  select(!`All ages`) |>
+#'  pivot_longer(`0`:`90+`, names_to = "age", values_to = "count")
+
+#' population_data_combined <- bind_rows(
+#'  females = population_data_2023_f,
+#'  males = population_data_2023_m,
+#'  .id = "sex"
+#' )
+#'
+#'
+#'
+"ons_uk_population_2023"