get_migration is a function that allows the user to get a demographic
dataset regarding migration based on the given parameters.
Arguments
- v_state
State(s) of desired data.
- v_year
Year(s) of desired data. Must have numbers between 1970 and 2050.
- v_sex
Vector selecting sex. Options: Female, Male and Total.
- v_age
Specifies the age bins to aggregate and return.
- v_type
Indicates whether type of migration to include. It can be Interstate migration, International migration or Total migration.
- age_groups
Specifies whether to aggregate the output by age groups.
Value
A demographic dataset containing the selected year, the state, the
state code (CVE_GEO), the age (age group, when age_groups = TRUE), the
type of migration, the number of emigrants, the number of immigrants,
migration balance (immigrants - emigrants), and the rate of
emigration and immigration, respectively.
Examples
get_migration(v_state = c("Yucatan", "Sonora"),
v_year = 2015,
v_sex = "Total",
v_age = c(0, 25, 35, 45),
v_type = "International",
age_groups = TRUE)
#> # A tibble: 8 x 12
#> year state CVE_GEO sex age_group type emigrants immigrants net_migration
#> <int> <chr> <dbl> <chr> <fct> <chr> <dbl> <dbl> <dbl>
#> 1 2015 Sonora 26 Total [0,25] Inte~ 2137 2282 145
#> 2 2015 Sonora 26 Total (25,35] Inte~ 982 1258 276
#> 3 2015 Sonora 26 Total (35,45] Inte~ 519 833 314
#> 4 2015 Sonora 26 Total (45,Inf] Inte~ 636 877 241
#> 5 2015 Yucatan 31 Total [0,25] Inte~ 951 466 -485
#> 6 2015 Yucatan 31 Total (25,35] Inte~ 437 260 -177
#> 7 2015 Yucatan 31 Total (35,45] Inte~ 232 172 -60
#> 8 2015 Yucatan 31 Total (45,Inf] Inte~ 284 179 -105
#> # ... with 3 more variables: em_rate <dbl>, im_rate <dbl>, nm_rate <dbl>
get_migration(v_state = "Mexico City",
v_year = c(2000, 2010),
v_sex = "Female",
v_age = c(0, 15, 35, 45, 75),
v_type = c("Interstate", "International", "Total"),
age_groups = FALSE)
#> # A tibble: 30 x 12
#> year state CVE_GEO sex age emigrants immigrants type net_migration
#> <int> <chr> <dbl> <chr> <int> <dbl> <dbl> <chr> <dbl>
#> 1 2000 Mexico Ci~ 9 Fema~ 0 160 77 Inte~ -83
#> 2 2000 Mexico Ci~ 9 Fema~ 0 4048 746 Inte~ -3302
#> 3 2000 Mexico Ci~ 9 Fema~ 0 4209 823 Total -3386
#> 4 2000 Mexico Ci~ 9 Fema~ 15 408 49 Inte~ -359
#> 5 2000 Mexico Ci~ 9 Fema~ 15 859 783 Inte~ -76
#> 6 2000 Mexico Ci~ 9 Fema~ 15 1267 831 Total -436
#> 7 2000 Mexico Ci~ 9 Fema~ 35 101 84 Inte~ -17
#> 8 2000 Mexico Ci~ 9 Fema~ 35 985 291 Inte~ -694
#> 9 2000 Mexico Ci~ 9 Fema~ 35 1086 375 Total -711
#> 10 2000 Mexico Ci~ 9 Fema~ 45 42 47 Inte~ 5
#> # ... with 20 more rows, and 3 more variables: em_rate <dbl>, im_rate <dbl>,
#> # nm_rate <dbl>