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

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

Usage

get_data_abs_age_work(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

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

Examples

get_data_abs_age_work(state = "NSW")
#> # A tibble: 116 × 6
#>     year state   age employed_population total_population proportion
#>    <dbl> <chr> <dbl>               <dbl>            <dbl>      <dbl>
#>  1  2016 NSW       0                   0            87708          0
#>  2  2016 NSW       1                   0            92876          0
#>  3  2016 NSW       2                   0            93584          0
#>  4  2016 NSW       3                   0            95179          0
#>  5  2016 NSW       4                   0            95791          0
#>  6  2016 NSW       5                   0            95216          0
#>  7  2016 NSW       6                   0            96479          0
#>  8  2016 NSW       7                   0            95142          0
#>  9  2016 NSW       8                   0            95833          0
#> 10  2016 NSW       9                   0            95516          0
#> # … with 106 more rows
get_data_abs_age_work(state = "WA", lga = "Albany (C)", age = 1:5)
#> # A tibble: 5 × 8
#>    year state lga          age employed_population 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                   0           434       0 FALSE  
#> 4  2016 WA    Albany (C)     4                   0           418       0 FALSE  
#> 5  2016 WA    Albany (C)     5                   0           376       0 FALSE  
#> # … with abbreviated variable names ¹​total_population, ²​proportion,
#> #   ³​anomaly_flag
get_data_abs_age_work(state = c("QLD", "TAS"), age = 5)
#> # A tibble: 2 × 6
#>    year state   age employed_population total_population proportion
#>   <dbl> <chr> <dbl>               <dbl>            <dbl>      <dbl>
#> 1  2016 QLD       5                   0            61981          0
#> 2  2016 TAS       5                   0             6132          0
get_data_abs_age_work(lga = c("Albury (C)", "Barcoo (S)"), age = 39)
#> # A tibble: 2 × 8
#>    year state lga          age employed_population total_popul…¹ propo…² anoma…³
#>   <dbl> <chr> <chr>      <dbl>               <dbl>         <dbl>   <dbl> <lgl>  
#> 1  2016 NSW   Albury (C)    39                 434           587   0.739 FALSE  
#> 2  2016 QLD   Barcoo (S)    39                   5             4   1.25  TRUE   
#> # … with abbreviated variable names ¹​total_population, ²​proportion,
#> #   ³​anomaly_flag