add_totals functions now work w/ non-numeric cols

per #57

R/add_totals.R

@@ -14,22 +14,36 @@
 #'   add_totals_row
 
 
-add_totals_row <- function(dat, na.rm = TRUE){
-  check_all_cols_after_first_are_numeric(dat)
-  dat[[1]] <- as.character(dat[[1]]) # for binding to the "Total" character value of add-on row
-  col_totals <- data.frame(x1 = "Total", t(colSums(dat[-1], na.rm = na.rm)), stringsAsFactors = FALSE) %>%
+add_totals_row <- function(dat, fill = "-", na.rm = TRUE){
+  clean_dat <- clean_names(dat) # bad names will make select_if choke
+
+  if(dim(select_if(clean_dat, is.numeric))[2] == 0){stop("data.frame must contain at least one column of class numeric")} # chokes on illegal names
+
+  # creates the totals row to be appended
+  col_vec <- function(a_col, na_rm = na.rm){
+    if(is.numeric(a_col)){ # can't do this with if_else because it doesn't like the sum() of a character vector, even if that clause is not reached
+      sum(a_col, na.rm = na_rm)
+    } else {fill}
+  }
+
+  col_totals <- lapply(dat, col_vec) %>%
+    as.data.frame(stringsAsFactors = FALSE) %>%
     stats::setNames(names(dat))
-  dplyr::bind_rows(dat, col_totals)
+
+  col_totals[nrow(col_totals), min(which(!unlist(lapply(col_totals, is.numeric))))] <- "Total" # replace final row, first non-numeric column with "Total"
+  dplyr::bind_rows(clean_dat %>%
+                     stats::setNames(names(dat)), col_totals)
+
 }
 
 #' @title Append a totals column to a data.frame.
 #'
 #' @description
-#' This function excludes the first column of the input data.frame, assuming that it contains a descriptive variable not to be summed.
+#' This function excludes non-numeric columns of the input data.frame, e.g., a first column with a descriptive variable not to be summed.
 #'
-#' @param dat an input data.frame with numeric values in all columns beyond the first.
+#' @param dat an input data.frame with at least one numeric column.
 #' @param na.rm should missing values (including NaN) be omitted from the calculations?
-#' @return Returns a data.frame with a totals column, consisting of "Total" in the first row and row sums in the others.
+#' @return Returns a data.frame with a totals column containing row-wise sums.
 #' @export
 #' @examples
 #' library(dplyr) # for the %>% pipe
@@ -38,8 +52,14 @@ add_totals_row <- function(dat, na.rm = TRUE){
 #'   add_totals_col
 
 add_totals_col <- function(dat, na.rm = TRUE){
-  check_all_cols_after_first_are_numeric(dat)
-  row_totals <- data.frame(Total = rowSums(dat[-1], na.rm = na.rm))
-  dplyr::bind_cols(dat, row_totals)
+
+  clean_dat <- clean_names(dat) # bad names will make select_if choke
+  if(dim(dplyr::select_if(clean_dat, is.numeric))[2] == 0){stop("data.frame must contain at least one column of class numeric")}
+  row_totals <- clean_dat %>%
+    dplyr::select_if(is.numeric) %>%
+    dplyr::transmute(Total = rowSums(., na.rm = na.rm))
+
+  dplyr::bind_cols(dat, row_totals) %>%
+    stats::setNames(c(names(dat), "Total")) # put back original names
 }
 

tests/testthat/test-add-totals.R

@@ -10,13 +10,6 @@ dat <- data.frame(a = c(rep(c("big", "small", "big"), 3)),
 ct <- dat %>%
   crosstab(a, b)
 
-
-test_that("error thrown if column beyond the first is not numeric", {
-  expect_error(add_totals_row(dat %>% select(b, a)),
-               "all columns after the first one must be numeric")
-  expect_error(add_totals_col(dat %>% select(b, a)),
-               "all columns after the first one must be numeric")
-})
 
 
 test_that("totals row is correct", {
@@ -74,3 +67,32 @@ test_that("both functions work with a single column", {
   expect_error(single_col %>% add_totals_row(), NA) # from http://stackoverflow.com/a/30068233
   expect_error(single_col %>% add_totals_row(), NA)
 })
+
+
+
+
+dat <- data.frame(
+  a = c("hi", "lo"),
+  b = c(1, 2),
+  c = c(5, 10),
+  d = c("big", "small"),
+  e = c(20, NA),
+  stringsAsFactors = FALSE
+)
+
+test_that("na.rm value gets passed through", {
+
+})
+
+
+test_that("error thrown if no columns are numeric", {
+
+})
+
+test_that("works with non-numeric columns mixed in", {
+
+})
+
+test_that("column names are passed through", {
+
+})