Added a population dataset

R/ons_uk_population_2023.R

@@ -0,0 +1,48 @@
+#' 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).
+#'
+#' ONS Estimates of the population for the UK, England, Wales, Scotland, and Northern Ireland
+#'
+#' @source
+#' \url{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}{country/geography code}
+#' \item{Name}{country of the UK}
+#' \item{Geography}{Country}
+#' \item{age}{year of age}
+#' \item{count}{the number of people in this group}
+#' }
+#'
+#' @usage data(ons_uk_population_2023)
+#'
+#' @examples
+#' data(ons_uk_population_2023)
+#'
+#'
+#' library(dplyr)
+#' library(tidyr)
+#'
+#' # create a dataset that has total population by age groups for England
+#' ons_uk_population_2023 |>
+#'   filter(Name == "ENGLAND") |>
+#'   mutate(age_group = case_when(
+#'     as.numeric(age) <= 17 ~ "0-17",
+#'     as.numeric(age) >= 18 & as.numeric(age) <= 64 ~ "18-64",
+#'     as.numeric(age) >= 65 ~ "65+",
+#'     age == "90+" ~ "65+"
+#'   )) |>
+#'   group_by(age_group) |>
+#'   summarise(count = sum(count))
+#'
+"ons_uk_population_2023"

data-raw/ons-mortality.R

@@ -407,3 +407,5 @@ ons_mortality %>%
   slice(1)
 
 unlink("working_files", recursive = TRUE)
+
+usethis::use_data(ons_mortality, overwrite = TRUE)

data-raw/ons_uk_population_2023.R

@@ -0,0 +1,36 @@
+# Source: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland
+
+library(readxl)
+library(tidyverse)
+library(tidyr)
+
+# Load the data in
+population_data_2023_f <- read_excel(
+  "mye23tablesuk.xlsx", # add full file path here before file name
+  sheet = "MYE2 - Females",
+  skip = 7
+)
+
+population_data_2023_m <- read_excel(
+  "mye23tablesuk.xlsx", # add full file path here before file name
+  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")
+
+ons_uk_population_2023 <- bind_rows(
+  females = population_data_2023_f,
+  males = population_data_2023_m,
+  .id = "sex"
+)
+
+usethis::use_data(ons_uk_population_2023, overwrite = TRUE)