Now with updated dropWhen adding "except"

R/dropWhen.R

@@ -4,14 +4,21 @@
 #' @param df Data frame to column filter
 #' @param unique Boolean for whether to return only unique rows after column filtering
 #' @param requireAll Boolean as to whether you want to require all rows in a column to equal a value in `trash` before filtering the column out (TRUE).
+#' @param except Character vector containing all column names to ignore when dropping columns (these will be retained regardless of the other parameter choices).
 #' @return Returns a columnn filtered data frame.  Note, does not take into account numeric, integer or character value differences (it will treat them all the same).
 #' @author Amy Paguirigan
 #' @examples
-#' df <- data.frame(this = c(NA, seq(1, 5, 1), seq(1, 5, 1)), that = rep(0, 11),
-#' thisotherThing = rep(NA), ohAndThis = rep(c("trash", "0"), 11))
+#' df <- data.frame(this = c(NA, seq(1, 5, 1), seq(1, 5, 1)), that = rep(0, 11), thisotherThing = rep(NA), ohAndThis = rep(c("trash", "0"), 11))
 #' cleanerdf <- dropWhen(df, unique = FALSE, trash = c("0", "trash"), requireAll = FALSE)
 #' @export
-dropWhen <- function(df, unique = FALSE, trash=NULL, requireAll = TRUE) {
+dropWhen <- function(df, unique = FALSE, trash=NULL, requireAll = TRUE, except = NULL) {
+  # Add atemporary index column so in case there are non-unique rows in the original df, the join doesn't break.
+  df$dropIndex <- seq(1:nrow(df))
+  # save a copy of the index and the extra columns for future re-application, but not the entire thing for memory purposes
+  extraColumns <- df %>% select(c(dropIndex, except))
+  if(is.null(except)==F){
+  df <- df %>% select(-except) # Remove the columns we don't to apply dropWhen to.
+  }
 
   if (requireAll == FALSE){
     # If all the values in a column do not have to be the same value in `trash` to be removed, just have to all be ONE of the values,
@@ -35,12 +42,15 @@ dropWhen <- function(df, unique = FALSE, trash=NULL, requireAll = TRUE) {
   filtered <- Filter(function(x)!all(is.na(x)), df)
   # filter the data frame to retain only columns that are not all NA
 
+  fullframe <- suppressMessages(left_join(filtered, extraColumns))
+
   if(unique == TRUE) {
     # If unique rows are desired
-    filtered <- unique(filtered)
+    fullframe <- unique(fullframe)
       # only return rows that are unique
   }
+  fullframe$dropIndex <- NULL
 
-  return(filtered)
+  return(fullframe)
 }