Tidy HMD Age-Specific Mortality Data

Put data on age-specific mortality rates from a zipped file downloaded from the Human Mortality Database into a tidy data frame.

Usage

tidy_hmd(zipfile, date = c("2025-09-25", "2024-02-26"), year_min = NULL)

Arguments

zipfile

The name of a zipped file downloaded from the Human Mortality Database. A path name that is handled by utils::unzip().

date

Date on which data produced. Choices are "2025-09-25", "2024-02-26". (Class is character, not Date.)

year_min

Only include data for year_min onwards. Ignored if year_min is NULL (the default).

Value

A tibble

See also

• data_ssvd_hmd() Put data from the Human Mortality Database into the format required by the ssvd() function in bage

• coef_hmd() Obtain time series of SVD coefficients for Human Mortality Database data

Examples

zipfile <- system.file("extdata", "hmd_statistics_20250925_subset.zip",
                       package = "bssvd")
tidy_hmd(zipfile)
#> # A tibble: 40,905 × 7
#>    country  time type_age age        mx    Lx sex  
#>    <chr>   <int> <fct>    <chr>   <dbl> <int> <fct>
#>  1 AUS      1921 single   0     0.0684  95294 Total
#>  2 AUS      1921 single   1     0.0132  92864 Total
#>  3 AUS      1921 single   2     0.00592 91978 Total
#>  4 AUS      1921 single   3     0.00355 91543 Total
#>  5 AUS      1921 single   4     0.00325 91232 Total
#>  6 AUS      1921 single   5     0.00251 90969 Total
#>  7 AUS      1921 single   6     0.00235 90748 Total
#>  8 AUS      1921 single   7     0.00187 90557 Total
#>  9 AUS      1921 single   8     0.00165 90398 Total
#> 10 AUS      1921 single   9     0.0014  90260 Total
#> # ℹ 40,895 more rows
tidy_hmd(zipfile,
         date = "2025-09-25",
         year_min = 1950)
#> # A tibble: 29,160 × 7
#>    country  time type_age age        mx    Lx sex   
#>    <chr>   <int> <fct>    <chr>   <dbl> <int> <fct> 
#>  1 AUS      1950 single   43    0.00373 92874 Female
#>  2 AUS      1950 single   47    0.00462 91426 Female
#>  3 AUS      1950 single   44    0.00348 92539 Female
#>  4 AUS      1950 single   45    0.00382 92202 Female
#>  5 AUS      1950 single   46    0.00422 91832 Female
#>  6 AUS      1950 single   59    0.0116  83452 Female
#>  7 AUS      1950 single   56    0.00911 86090 Female
#>  8 AUS      1950 single   57    0.00954 85292 Female
#>  9 AUS      1950 single   58    0.0113  84409 Female
#> 10 AUS      1950 single   50    0.00642 89974 Female
#> # ℹ 29,150 more rows