Merge pull request #311 from njtierney/prepare-for-1-0-0-release-310

Prepare for 1.0.0 release

Author: njtierney

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: naniar
 Type: Package
 Title: Data Structures, Summaries, and Visualisations for Missing Data
-Version: 0.6.1.9000
+Version: 1.0.0
 Authors@R: c(
   person("Nicholas", "Tierney", 
          role = c("aut", "cre"),

NAMESPACE

@@ -22,6 +22,8 @@ S3method(miss_var_summary,default)
 S3method(miss_var_summary,grouped_df)
 S3method(miss_var_table,default)
 S3method(miss_var_table,grouped_df)
+S3method(recode_shadow,data.frame)
+S3method(recode_shadow,grouped_df)
 S3method(replace_with_na,data.frame)
 S3method(shadow_shift,"NULL")
 S3method(shadow_shift,character)
@@ -139,7 +141,6 @@ export(shade)
 export(shadow_long)
 export(shadow_shift)
 export(stat_miss_point)
-export(to_basic.GeomMissPoint)
 export(unbind_data)
 export(unbind_shadow)
 export(vis_miss)

NEWS.md

@@ -1,4 +1,14 @@
-# naniar 0.6.1.9000
+# naniar 1.0.0
+
+Version 1.0.0 of naniar is to signify that this release is associated with
+the publication of the associated JSS paper, <doi:10.18637/jss.v105.i07>.
+There are also a few small changes that have been implemented in this release, 
+which are described below.
+
+There is still a lot to do in naniar, and this release does not signify that
+there are no changes upcoming, more so to establish that this is a stable
+release, and that any changes upcoming will go through a more formal deprecation
+process and so on.
 
 ## New
 

R/add-cols.R

@@ -269,6 +269,8 @@ add_label_missings <- function(data,
 #' @param complete character character a label for when values are complete - defaults to "Not Missing"
 #'
 #' @return "Missing" or "Not Missing"
+#' @keywords internal
+#' @noRd
 #'
 label_shadow <- function(data,
                          ...,

R/data-pedestrian.R

@@ -4,7 +4,7 @@
 #'   Melbourne: Birrarung Marr, Bourke Street Mall, Flagstaff station, and
 #'   Spencer St-Collins St (south), recorded from January 1st 2016 at 00:00:00
 #'   to December 31st 2016 at 23:00:00. The data is made free and publicly
-#'   available from \url{https://data.melbourne.vic.gov.au/Transport-Movement/Pedestrian-volume-updated-monthly-/b2ak-trbp}
+#'   available from \url{https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/information/}
 #'
 #' @format A tibble with 37,700 rows and 9 variables:
 #' \describe{
@@ -24,7 +24,7 @@
 #' @name pedestrian
 #' @docType data
 #' @usage data(pedestrian)
-#' @source \url{https://data.melbourne.vic.gov.au/Transport-Movement/Pedestrian-volume-updated-monthly-/b2ak-trbp}
+#' @source \url{https://data.melbourne.vic.gov.au/explore/dataset/pedestrian-counting-system-monthly-counts-per-hour/information/}
 #' @keywords datasets
 #'
 #' @examples

R/geom2plotly.R

@@ -12,7 +12,7 @@
 #' @param p a ggplot2 object (the conversion may depend on scales, for
 #'        instance).
 #' @param ... currently ignored
-#' @export
+#' @keywords internal
 to_basic.GeomMissPoint <- function(data,
                                    prestats_data,
                                    layout,

R/mcar-test.R

@@ -21,8 +21,8 @@
 #'   1198--1202. \doi{10.1080/01621459.1988.10478722}.
 #'
 #' @note Code is adapted from LittleMCAR() in the now-orphaned {BaylorEdPsych}
-#'   package: https://rdrr.io/cran/BaylorEdPsych/man/LittleMCAR.html. Some of
-#'   code is adapted from Eric Stemmler - <https://web.archive.org/web/20201120030409/https://stats-bayes.com/post/2020/08/14/r-function-for-little-s-test-for-data-missing-completely-at-random/>
+#'   package: \url{https://rdrr.io/cran/BaylorEdPsych/man/LittleMCAR.html}. Some of
+#'   code is adapted from Eric Stemmler: \url{https://web.archive.org/web/20201120030409/https://stats-bayes.com/post/2020/08/14/r-function-for-little-s-test-for-data-missing-completely-at-random/}
 #'   using Maximum likelihood estimation from {norm}.
 #'
 #' @author Andrew Heiss, \email{[email protected]}

R/shade.R

@@ -4,6 +4,8 @@
 #' @param extra_levels the extra levels to give to `shade` objects, such as "broken_machine" and so on, which get converted into "NA_broken_machine".
 #'
 #' @return a new shade, which is built upon a factor
+#' @keywords internal
+#' @noRd
 new_shade <- function(x, extra_levels = NULL){
 
   if (!is.factor(x)) {

R/shadow-recode.R

@@ -28,6 +28,8 @@
 #'
 #' # test that this breaks
 #' # shadow_expand_relevel(airquality, "weee")
+#' @keywords internal
+#' @noRd
 shadow_expand_relevel <- function(.var, suffix){
 
   # create level
@@ -78,7 +80,8 @@ shadow_expand_relevel <- function(.var, suffix){
 #'# update_shadow(dfs, "weee")
 #'# update_shadow(dfs, "weee") %>% what_levels()
 #' }
-#'
+#'@keywords internal
+#'@noRd
 update_shadow <- function(data, suffix) {
 
   class_of_cols <- purrr::map(data,class)
@@ -152,6 +155,7 @@ update_shadow <- function(data, suffix) {
 #'
 #' @return a dataframe with altered shadows
 #' @export
+#' @rdname recode_shadow
 #'
 #' @examples
 #'
@@ -176,6 +180,12 @@ recode_shadow <- function(data, ...){
 
   test_if_null(data)
   test_if_any_shade(data)
+  UseMethod("recode_shadow")
+}
+
+#' @name recode_shadow
+#' @export
+recode_shadow.data.frame <- function(data, ...){
 
   formulas <- rlang::dots_list(...)
 
@@ -234,3 +244,9 @@ recode_shadow <- function(data, ...){
 
   shadow_recoded
 }
+
+#' @name recode_shadow
+#' @export
+recode_shadow.grouped_df <- function(data, ...){
+  group_by_fun(data, .fun = recode_shadow, ...)
+}

R/utils.R

@@ -19,7 +19,8 @@ rlang::are_na
 #' @param ... additional arguments to be passed to map
 #'
 #' @return a dataframe with the function applied to each group
-#'
+#' @keywords internal
+#' @noRd
 #' @examples
 #'
 #' \dontrun{
@@ -52,6 +53,8 @@ group_by_fun <- function(data,.fun, ...){
 #' my_test <- NULL
 #' test_if_null(my_test)
 #' }
+#' @keywords internal
+#' @noRd
 test_if_null <- function(x){
 
   # test for null
@@ -74,6 +77,8 @@ test_if_null <- function(x){
 #' #fail
 #' test_if_missing()
 #' }
+#' @keywords internal
+#' @noRd
 test_if_missing <- function(x){
 
   # test for null
@@ -97,6 +102,8 @@ test_if_missing <- function(x){
 #' test_if_dataframe(my_test)
 #' }
 #'
+#' @keywords internal
+#' @noRd
 test_if_dataframe <- function(x){
   # test for dataframe
   if (!inherits(x, "data.frame")) {
@@ -152,6 +159,8 @@ add_span_counter <- function(data, span_size) {
 #' @param x data.frame, usually
 #'
 #' @return a list containing the levels of everything
+#' @keywords internal
+#' @noRd
 what_levels <- function(x) purrr::map(x, levels)
 
 quo_to_shade <- function(...){