Merge pull request #1700 from olivroy/edits-pkgdown

Edits pkgdown + fixup of some docs

NEWS.md

@@ -301,7 +301,7 @@
 
 * The `docx` output format is now better detected in R Markdown and Quarto (#1040). (#1084, thanks @cderv!)
 
-* Replaced all `match.arg()` calls with **rlang**'s `match_arg()` for better error output (#672). (#1099, thanks @mojister!)
+* Replaced all `match.arg()` calls with `rlang::arg_match()` for better error output (#672). (#1099, thanks @mojister!)
 
 * Project website improvements; we now have a doublet of sites: (1) https://gt.rstudio.com and (2) https://gt.rstudio.com/dev (#1074, thanks @ddsjoberg!)
 

R/format_data.R

@@ -8050,7 +8050,9 @@ extract_duration_pattern <- function(
 }
 
 #' Format column data containing bin/interval information
-
+#'
+#' @description
+#'
 #' When using `cut()` (or other functions that use it in some way)
 #' you get bins that can look like this: `"(0,10]"`, `"(10,15]"`, `"(15,20]"`,
 #' `"(20,40]"`. This interval notation expresses the lower and upper limits of
@@ -12838,11 +12840,10 @@ fmt_country <- function(
 #' Depending on which train services are offered at the subset of stations,
 #' *Font Awesome* icon names will be applied to cells where the different
 #' services exist (the specific names are `"train-subway"`, `"train"`, and
-#' `"train-tram"`). With **tidyr**'s `unite()` function, those icon names
-#' can be converged into a single column (`services`) with the `NA` values
-#' removed. Since the names correspond to icons and they are in the correct
-#' format (separated by commas), they can be formatted as *Font Awesome* icons
-#' with `fmt_icon()`.
+#' `"train-tram"`). With `tidyr::unite()`, those icon names can be converged
+#' into a single column (`services`) with the `NA` values removed. Since the
+#' names correspond to icons and they are in the correct format (separated by
+#' commas), they can be formatted as *Font Awesome* icons with `fmt_icon()`.
 #'
 #' ```r
 #' metro |>

R/info_tables.R

@@ -796,7 +796,8 @@ info_flags <- function() {
 #' from the **fontawesome** package). Because there is a very large number of
 #' icons available to use in *Font Awesome*, `info_icons()` can be used to
 #' provide us with a table that lists all the icons along with their short and
-#' full names (either can be used with [fmt_icon()]).
+#' full names (either can be used with [fmt_icon()]). It also contains
+#' acceptable codes for [fmt_country()]
 #'
 #' @return An object of class `gt_tbl`.
 #'

R/modify_columns.R

@@ -858,7 +858,7 @@ cols_width <- function(
 #' The [`illness`] dataset has units within the `units` column. They're
 #' formatted in just the right way for **gt** too. Let's do some text
 #' manipulation through `dplyr::mutate()` and some pivoting with
-#' **tidyr**'s `pivot_longer()` and `pivot_wider()` in order to include the
+#' `tidyr::pivot_longer()` and `tidyr::pivot_wider()` in order to include the
 #' units as part of the column names in the reworked table. These column names
 #' are in a format where the units are included within `"{{"`/`"}}"`, so, we can
 #' use `cols_label()` with the `.process_units = TRUE` option to register the
@@ -1611,18 +1611,17 @@ cols_units <- function(
 #'
 #' @description
 #'
-#' We can add new columns to a table with the `cols_add()` function and it works
-#' quite a bit like the **dplyr** `mutate()` function. The idea is that you
-#' supply name-value pairs where the name is the new column name and the value
-#' part describes the data that will go into the column. The latter can:
-#' (1) be a vector where the length of the number of rows in the data table,
-#' (2) be a single value (which will be repeated all the way down), or (3)
-#' involve other columns in the table (as they represent vectors of the correct
-#' length). The new columns are added to the end of the column series by default
-#' but can instead be added internally by using either the `.before` or `.after`
-#' arguments. If entirely empty (i.e., all `NA`) columns need to be added, you
-#' can use any of the `NA` types (e.g., `NA`, `NA_character_`, `NA_real_`, etc.)
-#' for such columns.
+#' We can add new columns to a table with `cols_add()` and it works quite a bit
+#' like `dplyr::mutate()` does. The idea is that you supply name-value pairs
+#' where the name is the new column name and the value part describes the data
+#' that will go into the column. The latter can: (1) be a vector where the
+#' length of the number of rows in the data table, (2) be a single value
+#' (which will be repeated all the way down), or (3) involve other columns in
+#' the table (as they represent vectors of the correct length). The new columns
+#' are added to the end of the column series by default but can instead be added
+#' internally by using either the `.before` or `.after` arguments. If entirely
+#' empty (i.e., all `NA`) columns need to be added, you can use any of the `NA`
+#' types (e.g., `NA`, `NA_character_`, `NA_real_`, etc.) for such columns.
 #'
 #' @inheritParams fmt_number
 #'
@@ -2604,7 +2603,7 @@ cols_add <- function(
 #' pizza analytics). We also have the sell price for a pizza, and that'll serve
 #' as the *y* values. The pizzas belong to four different groups (in the `type`
 #' column) and we'll group by that and create value streams with
-#' `paste(..., collapse = ",")` in the **dplyr** summarize call. With two value
+#' `paste(..., collapse = ",")` inside  the `dplyr::summarize()` call. With two value
 #' streams in each row (having the same number of values) we can now make a
 #' **gt** table with nanoplots.
 #'

R/rows_add.R

@@ -214,7 +214,7 @@
 #' Another application is starting from nothing (really just the definition of
 #' columns) and building up a table using several invocations of `rows_add()`.
 #' This might be useful in interactive or programmatic applications. Here's an
-#' example where two columns are defined with **dplyr**'s `tibble()` function
+#' example where two columns are defined with `dplyr::tibble()`
 #' (and no rows are present initially); with two calls of `rows_add()`, two
 #' separate rows are added.
 #'

R/tab_create_modify.R

@@ -1064,10 +1064,9 @@ resolve_spanned_column_names <- function(
 #' }}
 #'
 #' With a summarized, filtered, and pivoted version of the [`pizzaplace`]
-#' dataset, we can create another **gt** table and then use the
-#' `tab_spanner_delim()` function with the same delimiter/separator that was
-#' used in the **tidyr** `pivot_wider()` call. We can also process the generated
-#' column labels with [cols_label_with()].
+#' dataset, we can create another **gt** table and then use `tab_spanner_delim()`
+#' with the delimiter/separator also used in `tidyr::pivot_wider()`. We can also
+#' process the generated column labels with [cols_label_with()].
 #'
 #' ```r
 #' pizzaplace |>

R/topics.R

@@ -55,4 +55,5 @@
 #' * [text_case_match()]
 #'
 #' These functions contain more example of usage.
+#' @keywords internal
 NULL

pkgdown/_pkgdown.yml

@@ -34,10 +34,10 @@ reference:
       All **gt** tables begin with a call to `gt()`, where we would supply the
       input data table (data frame or tibble) and some basic options for
       creating a stub (`rowname_col`) and row groups (`groupname_col`). We
-      can also introduce a grouped tibble (via **dplyr**'s `group_by()`) for
-      more precise divisions of rows into row groups. The `gt_preview()`
-      function is great for getting a nicely-formatted preview of a data
-      table (defaulting to the first 5 rows and the last row).
+      can also introduce a grouped tibble (via `dplyr::group_by()`) for
+      more precise divisions of rows into row groups. `gt_preview()`
+      is great for getting a nicely-formatted preview of a data table
+      (defaulting to the first 5 rows and the last row).
     contents:
     - gt
     - gt_preview
@@ -185,13 +185,13 @@ reference:
     desc: >
       An assortment of helper functions is available in the **gt** package.
       The various `cells_*()` functions are used for targeting cells with the
-      `locations` argument in the `tab_footnote()`, `tab_style()`, and
-      `text_transform()` functions. The `cell_*()` functions are used
-      exclusively with `tab_style()`'s `style` argument. The `px()` &
-      `pct()` functions are useful there for specifying units in pixels or
-      percentages. The `md()` and `html()` helpers can used be during label
-      creation with the `tab_header()`, `tab_footnote()`, `tab_spanner()`,
-      `tab_stubhead_label()`, and `tab_source_note()` functions.
+      `locations` argument of `tab_footnote()`, `tab_style()`, and
+      `text_transform()`, `text_case_match()`, and `text_case_when()`.
+      The `cell_*()` functions are used exclusively with `tab_style()`'s `style`
+      argument. `px()` & `pct()` are useful there for specifying
+      units in pixels or percentages. The `md()` and `html()` helpers can used
+      be during label creation with `tab_header()`, `tab_footnote()`,
+      `tab_spanner()`, `tab_stubhead()`, and `tab_source_note()`.
     contents:
     - md
     - html