Calculates variables necessary for WATS Plots. This the first of two functions
that needs to be called to produce WATS Plots. annotate_data() is the second.
Usage
augment_year_data_with_month_resolution(ds_linear, date_name)
augment_year_data_with_second_resolution(ds_linear, date_name)Arguments
- ds_linear
The data.frame to containing the detailed data.
- date_name
The variable name in
ds_linearcontaining the date or datetime value.
Value
Returns a tibble::tibble with additional variables:
cycle_tally, proportion_through_cycle, proportion_id, and terminal_point_in_cycle.
Examples
library(Wats)
ds_linear <-
Wats::county_month_birth_rate_2005_version |>
dplyr::filter(county_name == "oklahoma") |>
augment_year_data_with_month_resolution(date_name = "date")
head(ds_linear)
#> # A tibble: 6 × 18
#> fips county_name year month fecund_population birth_count date
#> <chr> <chr> <int> <int> <int> <int> <date>
#> 1 40109 oklahoma 1990 1 143192 853 1990-01-15
#> 2 40109 oklahoma 1990 2 143278 758 1990-02-15
#> 3 40109 oklahoma 1990 3 143365 886 1990-03-15
#> 4 40109 oklahoma 1990 4 143452 871 1990-04-15
#> 5 40109 oklahoma 1990 5 143538 822 1990-05-15
#> 6 40109 oklahoma 1990 6 143625 834 1990-06-15
#> # ℹ 11 more variables: days_in_month <int>, days_in_year <int>, stage_id <int>,
#> # birth_rate_monthly <dbl>, birth_rate <dbl>, cycle_tally <dbl>,
#> # proportion_through_cycle <dbl>, proportion_id <dbl>,
#> # starting_point_in_cycle <lgl>, terminal_point_in_cycle <lgl>,
#> # stage_progress <dbl>