Return data on educated population for a given age and state or lga of Australia.

Return data on educated population for a given age and state or lga of Australia.

Usage

get_data_abs_age_education(age = NULL, state = NULL, lga = NULL)

Arguments

age

a numeric or numeric vector denoting ages between 0 to 115. The default is to return all ages.

state

target Australian state name or a vector with multiple state names in its abbreviated form, such as "QLD", "NSW", or "TAS"

lga

target Australian local government area (LGA) name, such as "Fairfield (C)" or a vector with multiple lga names. See abs_lga_lookup() for list of lga names.

Value

dataset with information on the number of educated people belonging to a particular age, its total population and the corresponding proportion.

Examples

get_data_abs_age_education(state = "VIC")
#> # A tibble: 116 × 6
#>     year state   age population_educated total_population proportion
#>    <dbl> <chr> <dbl>               <dbl>            <dbl>      <dbl>
#>  1  2016 VIC       0                   0            70920      0    
#>  2  2016 VIC       1                   0            74723      0    
#>  3  2016 VIC       2                   0            74475      0    
#>  4  2016 VIC       3               25354            76009      0.334
#>  5  2016 VIC       4               49763            75084      0.663
#>  6  2016 VIC       5               64489            73468      0.878
#>  7  2016 VIC       6               70717            74780      0.946
#>  8  2016 VIC       7               69543            73391      0.948
#>  9  2016 VIC       8               69673            73373      0.950
#> 10  2016 VIC       9               69894            73627      0.949
#> # … with 106 more rows
get_data_abs_age_education(state = "WA", lga = "Albany (C)", age = 1:5)
#> # A tibble: 5 × 8
#>    year state lga          age population_educated total_popul…¹ propo…² anoma…³
#>   <dbl> <chr> <chr>      <dbl>               <dbl>         <dbl>   <dbl> <lgl>  
#> 1  2016 WA    Albany (C)     1                   0           348   0     FALSE  
#> 2  2016 WA    Albany (C)     2                   0           413   0     FALSE  
#> 3  2016 WA    Albany (C)     3                  44           434   0.101 FALSE  
#> 4  2016 WA    Albany (C)     4                 319           418   0.763 FALSE  
#> 5  2016 WA    Albany (C)     5                 355           376   0.944 FALSE  
#> # … with abbreviated variable names ¹​total_population, ²​proportion,
#> #   ³​anomaly_flag
get_data_abs_age_education(state = c("QLD", "TAS"), age = 5)
#> # A tibble: 2 × 6
#>    year state   age population_educated total_population proportion
#>   <dbl> <chr> <dbl>               <dbl>            <dbl>      <dbl>
#> 1  2016 QLD       5               55416            61981      0.894
#> 2  2016 TAS       5                5745             6132      0.937
get_data_abs_age_education(lga = c("Albury (C)", "Barcoo (S)"), age = 10)
#> # A tibble: 2 × 8
#>    year state lga          age population_educated total_popul…¹ propo…² anoma…³
#>   <dbl> <chr> <chr>      <dbl>               <dbl>         <dbl>   <dbl> <lgl>  
#> 1  2016 NSW   Albury (C)    10                 615           654   0.940 FALSE  
#> 2  2016 QLD   Barcoo (S)    10                   7             7   1     FALSE  
#> # … with abbreviated variable names ¹​total_population, ²​proportion,
#> #   ³​anomaly_flag