diff --git a/R/variance_thresholding.R b/R/variance_thresholding.R
index 7eb9ee0..f2ff3f0 100644
--- a/R/variance_thresholding.R
+++ b/R/variance_thresholding.R
@@ -6,7 +6,7 @@
 #' @param data tibble. The features to select from
 #' @param threshold double. The variance threshold
 #'
-#' @return vector. The indexes of selected features
+#' @return double vector. The indexes of selected features
 #' @export
 #' @examples
 #' data <- data.frame(x1=c(1,2,3,4,5), x2=c(0,0,0,0,0), x3=c(1,1,1,1,1))
@@ -22,15 +22,15 @@ variance_thresholding <- function(data, threshold = 0) {
   }
 
   selected_feature_indexes <- c()
-  i <- 1
-  for (name in names(data)) {
+  for (i in 1:length(names(data))) {
+    # Get variance of a column
     var_i <- stats::var(data[,i])
 
     if (var_i > threshold) {
+      # Add the column to the selected pile if
+      # its variance is above the threshold
       selected_feature_indexes <- c(selected_feature_indexes, i)
     }
-
-    i <- i + 1
   }
 
   selected_feature_indexes
diff --git a/tests/testthat/test-variance_thresholding.R b/tests/testthat/test-variance_thresholding.R
index 7211ad7..565c72d 100644
--- a/tests/testthat/test-variance_thresholding.R
+++ b/tests/testthat/test-variance_thresholding.R
@@ -15,7 +15,7 @@ testthat::test_that("relevant features remain", {
   )
 
   feature_indexes <- variance_thresholding(data)
-  testthat::expect_identical(feature_indexes, c(1, 4))
+  testthat::expect_equal(feature_indexes, c(1, 4))
 })
 
 #'
@@ -23,20 +23,28 @@ testthat::test_that("relevant features remain", {
 #'
 #' @NoRd
 testthat::test_that("appropriate features are dropped with higher threshold", {
-  data <- dplyr::tibble(
+  data_a <- dplyr::tibble(
     a = c(1,2,3),
     b = c(2,2,2),
     c = c('123', '123', '123'),
     d = c('123', '14', '1')
   )
 
-  feature_indexes <- variance_thresholding(data, threshold = 2)
-  testthat::expect_identical(feature_indexes, c(4))
+  feature_indexes_a <- variance_thresholding(data_a, threshold = 2)
+  testthat::expect_equal(feature_indexes_a, c(4))
+
+  data_b <- dplyr::tibble(
+    a = c(1,2,3),
+    b = c(2,2,2)
+  )
+
+  feature_indexes_b <- variance_thresholding(data_b, threshold = 100)
+  testthat::expect_equal(feature_indexes_b, NULL)
 })
 
 #'
 #' Make sure the function blows up when invalid inputs are past in for
-#' both the threshold and X 
+#' both the threshold and X
 #'
 #' @NoRd
 testthat::test_that("inputs checking", {