Fix incomplete merge, inaccurate new_epi_df(*_type) docs

Author: brookslogan

R/epi_df.R

@@ -151,26 +151,30 @@
 #' attr(ex3, "metadata")
 NULL
 
-#' Create an `epi_df` object
-#'
-#' @rdname epi_df
-#' @param geo_type DEPRECATED Has no effect. Geo value type is inferred from the
-#' location column and set to "custom" if not recognized.
-#' @param time_type DEPRECATED Has no effect. Time value type inferred from the time
-#' column and set to "custom" if not recognized. Unpredictable behavior may result
-#' if the time type is not recognized.
+#' @describeIn epi_df Lower-level constructor for `epi_df` object
+#' @order 2
+#' @param geo_type `r lifecycle::badge("deprecated")` in `as_epi_df()`, has no
+#'   effect; the geo value type is inferred from the location column and set to
+#'   "custom" if not recognized. In `new_epi_df()`, should be set to the same
+#'   value that would be inferred.
+#' @param time_type `r lifecycle::badge("deprecated")` in `as_epi_df()`, has no
+#'   effect: the time value type inferred from the time column and set to
+#'   "custom" if not recognized. Unpredictable behavior may result if the time
+#'   type is not recognized. In `new_epi_df()`, should be set to the same value
+#'   that would be inferred.
 #' @param as_of Time value representing the time at which the given data were
 #'   available. For example, if `as_of` is January 31, 2022, then the `epi_df`
 #'   object that is created would represent the most up-to-date version of the
 #'   data available as of January 31, 2022. If the `as_of` argument is missing,
 #'   then the current day-time will be used.
-#' @param other_keys If your tibble has additional keys, be sure to specify them as a
-#'   character vector here (typical examples are "age" or sub-geographies).
+#' @param other_keys If your tibble has additional keys, be sure to specify them
+#'   as a character vector here (typical examples are "age" or sub-geographies).
 #' @param ... Additional arguments passed to methods.
 #' @return An `epi_df` object.
 #'
 #' @export
-new_epi_df <- function(x = tibble::tibble(), geo_type, time_type, as_of,
+new_epi_df <- function(x = tibble::tibble(geo_value = character(), time_value = as.Date(integer())),
+                       geo_type, time_type, as_of,
                        other_keys = character(), ...) {
   # Define metadata fields
   metadata <- list()
@@ -195,7 +199,8 @@ new_epi_df <- function(x = tibble::tibble(), geo_type, time_type, as_of,
   return(x)
 }
 
-#' @rdname epi_df
+#' @describeIn epi_df The preferred way of constructing `epi_df`s
+#' @order 1
 #' @param x An `epi_df`, `data.frame`, [tibble::tibble], or [tsibble::tsibble]
 #'   to be converted
 #' @param ... used for specifying column names, as in [`dplyr::rename`]. For
@@ -206,17 +211,19 @@ as_epi_df <- function(x, ...) {
 }
 
 #' @rdname epi_df
+#' @order 1
 #' @method as_epi_df epi_df
 #' @export
 as_epi_df.epi_df <- function(x, ...) {
   return(x)
 }
 
 #' @rdname epi_df
-#' @method as_epi_df tbl_df
+#' @order 1
 #' @importFrom rlang .data
 #' @importFrom tidyselect any_of
 #' @importFrom cli cli_inform
+#' @method as_epi_df tbl_df
 #' @export
 as_epi_df.tbl_df <- function(
     x,
@@ -273,15 +280,17 @@ as_epi_df.tbl_df <- function(
   new_epi_df(x, geo_type, time_type, as_of, other_keys)
 }
 
-#' @method as_epi_df data.frame
 #' @rdname epi_df
+#' @order 1
+#' @method as_epi_df data.frame
 #' @export
 as_epi_df.data.frame <- function(x, as_of, other_keys = character(), ...) {
   as_epi_df.tbl_df(x = tibble::as_tibble(x), as_of = as_of, other_keys = other_keys, ...)
 }
 
-#' @method as_epi_df tbl_ts
 #' @rdname epi_df
+#' @order 1
+#' @method as_epi_df tbl_ts
 #' @export
 as_epi_df.tbl_ts <- function(x, as_of, other_keys = character(), ...) {
   tsibble_other_keys <- setdiff(tsibble::key_vars(x), "geo_value")

man/epi_df.Rd

@@ -7,10 +7,12 @@ test_that("canonical arrangement works", {
   )
   expect_error(arrange_canonical(tib))
 
-  tib <- tib %>% as_epi_df(additional_metadata = list(other_keys = "demo_grp"))
-  expect_equal(names(tib), c("geo_value", "time_value", "x", "demo_grp"))
+  tib <- tib %>% as_epi_df(other_keys = "demo_grp")
+  expect_equal(names(tib), c("geo_value", "time_value", "demo_grp", "x"))
 
-  tib_sorted <- arrange_canonical(tib)
+  tib_cols_shuffled <- tib %>% select(geo_value, time_value, x, demo_grp)
+
+  tib_sorted <- arrange_canonical(tib_cols_shuffled)
   expect_equal(names(tib_sorted), c("geo_value", "time_value", "demo_grp", "x"))
   expect_equal(tib_sorted$geo_value, rep(c("ca", "ga"), each = 4))
   expect_equal(tib_sorted$time_value, c(1, 1, 2, 2, 1, 1, 2, 2))