Country, regional, and sub-national population estimates by 10 year age groups

ONS National and sub-national 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).

Usage

data("uk_population_2019_by_10yr_age")

Format

An object of class grouped_df (inherits from tbl_df, tbl, data.frame) with 3980 rows and 6 columns.

Source

https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates

Originally licensed under the Open Government Licence v3.0

Details

Mid-2019: April 2019 local authority district codes edition of this dataset, this is UK wide and covers country, regions and LTLA (2019 boundaries)

Stratified by 10 year age groups

uk_population_2019_by_10yr_age dataframe with 3980 rows and 6 columns

name (chr)

The region name

code (chr)

The region code

codeType (chr)

The ONS geographical region code type (including year)

class (chr)

The age group in 10 year age bands

population (dbl)

the count of the population in that age group

baseline_proportion (dbl)

the proportion of the total regional population that is in an age group

Examples

dplyr::glimpse(uk_population_2019_by_10yr_age)
#> Rows: 3,980
#> Columns: 6
#> Groups: name, code, codeType [398]
#> $ code                <chr> "E06000001", "E06000001", "E06000001", "E06000001"…
#> $ class               <chr> "00_09", "10_19", "20_29", "30_39", "40_49", "50_5…
#> $ population          <dbl> 11152, 10979, 11279, 11687, 10834, 13600, 11101, 8…
#> $ name                <chr> "Hartlepool", "Hartlepool", "Hartlepool", "Hartlep…
#> $ codeType            <chr> "LAD19", "LAD19", "LAD19", "LAD19", "LAD19", "LAD1…
#> $ baseline_proportion <dbl> 0.119065159, 0.117218112, 0.120421084, 0.124777127…