Render a template report

render_report() generates a report for a given template and year. The final output can be viewed interactively in RStudio. Reports can also be rendered across multiple years.

Usage

render_report(
  template_name,
  disease,
  estimated = NULL,
  notified = NULL,
  year = NULL,
  vars = NULL,
  interactive = TRUE,
  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

Integer matching the year(s) of the report to be rendered. Can be a single integer like 2019, or a vector of integers such as 2019:2021. The argument is to passed to build_dm() under the hood.

vars

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

interactive

Logical indicating whether to open the report with the RStudio Viewer.

override_vars_check

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

On override_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_report(
  template_name = "eda.Rmd",
  disease = "tb",
  estimated = "who_estimates.e_inc_num",
  notified = "who_notifications.c_newinc",
  year = 2019,
  vars = tb_vars
)
}