Update examples

R/cols_align.R

@@ -78,9 +78,14 @@
 #' ```r
 #' countrypops |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::filter(country_name == "San Marino") |>
-#'   dplyr::slice_tail(n = 5) |>
-#'   gt(rowname_col = "year", groupname_col = "country_name") |>
+#'   dplyr::filter(
+#'     country_name == "San Marino",
+#'     year %in% 2017:2021
+#'   ) |>
+#'   gt(
+#'     rowname_col = "year",
+#'     groupname_col = "country_name"
+#'   ) |>
 #'   cols_align(
 #'     align = "left",
 #'     columns = population

R/cols_hide.R

@@ -68,8 +68,10 @@
 #'
 #' ```r
 #' countrypops |>
-#'   dplyr::filter(country_name == "Egypt") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Egypt",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_hide(columns = c(country_code_2, country_code_3))
 #' ```
@@ -86,8 +88,10 @@
 #'
 #' ```r
 #' countrypops |>
-#'   dplyr::filter(country_name == "Pakistan") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Pakistan",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_hide(columns = c(country_code_3, population)) |>
 #'   tab_footnote(
@@ -189,8 +193,10 @@ cols_hide <- function(
 #' ```r
 #' tab_1 <-
 #'   countrypops |>
-#'   dplyr::filter(country_name == "Singapore") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Singapore",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_hide(columns = c(country_code_2, country_code_3))
 #'

R/cols_label.R

@@ -142,8 +142,10 @@
 #' ```r
 #' countrypops |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::filter(country_name == "Uganda") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Uganda",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_label(
 #'     country_name = "Name",
@@ -164,8 +166,10 @@
 #' ```r
 #' countrypops |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::filter(country_name == "Uganda") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Uganda",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_label(
 #'     country_name = md("**Name**"),

R/cols_move.R

@@ -79,8 +79,10 @@
 #' ```r
 #' countrypops |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::filter(country_name == "Japan") |>
-#'   dplyr::slice_tail(n = 10) |>
+#'   dplyr::filter(
+#'     country_name == "Japan",
+#'     year %in% 2012:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_move(
 #'     columns = population,
@@ -214,8 +216,10 @@ cols_move <- function(
 #' ```r
 #' countrypops |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::filter(country_name == "Fiji") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Fiji",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_move_to_start(columns = year)
 #' ```
@@ -231,8 +235,10 @@ cols_move <- function(
 #' ```r
 #' countrypops |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::filter(country_name == "Fiji") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Fiji",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_move_to_start(columns = c(year, population))
 #' ```
@@ -336,8 +342,10 @@ cols_move_to_start <- function(
 #' ```r
 #' countrypops |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::filter(country_name == "Benin") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Benin",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_move_to_end(columns = year)
 #' ```
@@ -353,8 +361,10 @@ cols_move_to_start <- function(
 #' ```r
 #' countrypops |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::filter(country_name == "Benin") |>
-#'   dplyr::slice_tail(n = 5) |>
+#'   dplyr::filter(
+#'     country_name == "Benin",
+#'     year %in% 2017:2021
+#'   ) |>
 #'   gt() |>
 #'   cols_move_to_end(columns = c(year, country_name))
 #' ```

R/data_color.R

@@ -439,9 +439,11 @@
 #'
 #' ```r
 #' countrypops |>
-#'   dplyr::filter(country_name == "Bangladesh") |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::slice_tail(n = 10) |>
+#'   dplyr::filter(
+#'     country_name == "Bangladesh",
+#'     year %in% 2012:2021
+#'   ) |>
 #'   gt() |>
 #'   data_color(
 #'     columns = population,
@@ -464,9 +466,11 @@
 #'
 #' ```r
 #' countrypops |>
-#'   dplyr::filter(country_name == "Bangladesh") |>
 #'   dplyr::select(-contains("code")) |>
-#'   dplyr::slice_tail(n = 10) |>
+#'   dplyr::filter(
+#'     country_name == "Bangladesh",
+#'     year %in% 2012:2021
+#'   ) |>
 #'   gt() |>
 #'   data_color(
 #'     columns = population,

R/format_data.R

@@ -8005,7 +8005,7 @@ get_image_hw_ratio <- function(filepath) {
 #' make this work seamlessly, the input cells need to contain some reference to
 #' a country, and this can be in the form of a 2- or 3-letter ISO 3166-1 country
 #' code (e.g., Egypt has the `"EG"` country code). This function will parse the
-#' targeted body cells for those codes (and the [countrypops] dataset contains
+#' targeted body cells for those codes (and the [`countrypops`] dataset contains
 #' all of them) and insert the appropriate flag graphics.
 #'
 #' Multiple flags can be included per cell by separating country codes with