add digit argument to miss_var_summary to help display %missing d…

…ata correctly when there is a very small fraction of missingness. resolves #284

NEWS.md

@@ -3,6 +3,7 @@
 ## New
 
 - implement `impute_fixed`, `impute_zero`, and `impute_factor`. notably these do not implement "scoped variants" which were previously implemented - for example, `impute_fixed_if` etc. This is in favour of using the new `across` workflow within `dplyr`, and it is easier to maintain. #261
+- add `digit` argument to `miss_var_summary` to help display %missing data correctly when there is a very small fraction of missingness. #284
 
 # naniar 1.0.0
 

R/miss-x-summary.R

@@ -11,6 +11,8 @@
 #'   sum of missings to the data. This can be useful when exploring patterns
 #'   of nonresponse. These are calculated as the cumulative sum of the missings
 #'   in the variables as they are first presented to the function.
+#' @param digits how many digits to display in `pct_miss` column. Useful when
+#'   you are working with small amounts of missing data.
 #' @param ... extra arguments
 #'
 #' @note `n_miss_cumsum` is calculated as the cumulative sum of missings in the
@@ -39,6 +41,7 @@
 miss_var_summary <- function(data,
                              order = FALSE,
                              add_cumsum = FALSE,
+                             digits,
                              ...) {
 
   test_if_null(data)
@@ -52,14 +55,19 @@ miss_var_summary <- function(data,
 miss_var_summary.default <- function(data,
                                      order = TRUE,
                                      add_cumsum = FALSE,
+                                     digits = NULL,
                                      ...) {
 
   col_n_miss <- colSums(is.na(data))
-  col_pct_miss <- colMeans(is.na(data)) * 100
+  col_pct_miss <- as.numeric(colMeans(is.na(data)) * 100)
 
   res <- tibble::tibble(variable = names(col_n_miss),
                         n_miss = as.integer(col_n_miss),
-                        pct_miss = as.numeric(col_pct_miss))
+                        pct_miss = tibble::num(
+                          x = col_pct_miss,
+                          # control how rounding is presented
+                          digits = digits)
+                        )
 
   if (add_cumsum) {
    res <- res %>% dplyr::mutate(n_miss_cumsum = cumsum(n_miss))
@@ -77,12 +85,14 @@ miss_var_summary.default <- function(data,
 miss_var_summary.grouped_df <- function(data,
                                         order = TRUE,
                                         add_cumsum = FALSE,
+                                        digits = NULL,
                                         ...) {
 
   group_by_fun(data,
                .fun = miss_var_summary,
                order = order,
-               add_cumsum = add_cumsum)
+               add_cumsum = add_cumsum,
+               digits = digits)
 
 }