Render templates across multiple years

render_bulk() is a convenience wrapper around render_report() that allows you to render templates across multiple years.

Usage

render_bulk(
  template_name,
  disease,
  estimated = NULL,
  notified = NULL,
  year = NULL,
  vars = NULL,
  override_vars_check = FALSE
)

Arguments

template_name

String containing the name of the template to render. Run view_templates() to see a list of valid options.

disease

A character of length one identifying the disease for which the user wants to build a wide table. The tibble dxgap_diseases shows the diseases that are currently supported.

estimated

Override the default NULL with a dot-separated character indicating which field from which table should be used as estimated cases for DX Gap computation. If kept to NULL, the function will use the value estimates_table.estimates_field from the notified column in the dxgap_diseases meta table.

notified

Override the default NULL with a dot-separated character indicating which field from which table should be used as notified cases for DX Gap computation. If kept to NULL, the function will use the value notifications_table.notifications_field from the notified column in the dxgap_diseases meta table.

year

An integer vector indicating consecutive years to filter the data on. Defaults to NULL, returning all years present in the data.

vars

A vector of strings naming columns to subset the data on. Passed to build_tbl(). Defaults to NULL, indicating all variables should be used.

override_vars_check

Logical indicating whether to override checks on supported vars. Defaults to FALSE. If TRUE, consistent results are not guaranteed.

Vars Check

This check consists in comparing the character vector of variable names supplied by the user through the vars argument, with those that were selected in light of the exploratory data analysis. If some of the provided variables are not part of the original subset, the function will throw an error. However, new variables names can always be added overriding the check by setting override_vars_check = TRUE. If a new variable name should be part of the core subset, it should be added to the dxgap_diseases tibble.

Examples

if (FALSE) {
tb_vars <- c("year", "is_hbc", "country_code", "dx_gap",
             "pop_total", "pop_urban_perc", "pop_density", "gdp", "c_newinc",
             "e_inc_num", "e_mort_100k", "culture", "smear", "xpert", "m_wrd")
render_bulk("eda.Rmd", disease = "tb", year = 2018:2021, vars = tb_vars)
}