Merge pull request #19 from neuropsychology/0.0.7b

0.0.7b

NEWS.md

@@ -6,6 +6,7 @@
 ### Minor changes
 - Added [`CONTRIBUTING.md`](https://github.com/neuropsychology/psycho.R/blob/master/CONTRIBUTING.md)
 - Changed `format_digit`
+- Added `except` parameter to `normalize`
 
 
 # 0.0.6 (2017-12-07)

R/normalize.R

@@ -3,31 +3,52 @@
 #' Select numeric variables and normalize (Z-score) them.
 #'
 #' @param df Dataframe.
+#' @param except Character or list of characters of column names to be excluded from normalization.
 #'
 #' @return Dataframe.
 #'
 #' @examples
-#' df <- data.frame(Participant = as.factor(rep(1:50,each=2)),
-#'   Condition = base::rep_len(c("A", "B"), 100), V1 = rnorm(100, 30, .2),
-#'   V2 = runif(100, 3, 5))
+#' df <- data.frame(
+#'   Participant = as.factor(rep(1:50,each=2)),
+#'   Condition = base::rep_len(c("A", "B"), 100),
+#'   V1 = rnorm(100, 30, .2),
+#'   V2 = runif(100, 3, 5),
+#'   V3 = rnorm(100, 100, 10)
+#'   )
 #'
 #' dfZ <- normalize(df)
+#' dfZ <- normalize(df, except="V3")
+#' dfZ <- normalize(df, except=c("V1", "V2"))
 #'
 #' @author \href{https://dominiquemakowski.github.io/}{Dominique Makowski}
 #'
 #'
 #' @import purrr
 #' @import dplyr
 #' @export
-normalize <- function(df) {
+normalize <- function(df, except=NULL) {
+
+  # Remove exceptions
+  if(!is.null(except) && except %in% names(df)){
+    to_keep <- as.data.frame(df[except])
+    df <- df[!names(df) %in% c(except)]
+  }
+
+  # Remove non-numerics
   dfother <- purrr::discard(df, is.numeric)
   dfnum <- purrr::keep(df, is.numeric)
   dfnum <- as.data.frame(scale(dfnum))
+  # Add non-numerics
   if (is.null(ncol(dfother))) {
     df <- dfnum
   } else {
     df <- dplyr::bind_cols(dfother, dfnum)
   }
 
+  # Add exceptions
+  if(!is.null(except) && exists("to_keep")){
+    df <- dplyr::bind_cols(df, to_keep)
+  }
+
   return(df)
 }

tests/testthat/test-normalize.R

@@ -1,11 +1,24 @@
 context("normalize")
 
 test_that("Correct Value", {
-  x <- data.frame(x = c(8, 10, 12), y = c("a", "b", "c"))
-  x <- psycho::normalize(x)
-  testthat::expect_equal(mean(x$x), 0)
+  df <- data.frame(
+    V1 = rnorm(100, 30, .2),
+    V2 = runif(100, 3, 5),
+    V3 = rnorm(100, 100, 10)
+  )
+  dfZ <- normalize(df)
+  testthat::expect_equal(mean(dfZ$V1), 0)
+
+  df <- data.frame(
+    Participant = as.factor(rep(1:50,each=2)),
+    Condition = base::rep_len(c("A", "B"), 100),
+    V1 = rnorm(100, 30, .2),
+    V2 = runif(100, 3, 5),
+    V3 = rnorm(100, 100, 10)
+    )
+  dfZ <- normalize(df, except="V3")
+  testthat::expect_equal(mean(dfZ$V2), 0)
+  dfZ <- normalize(df, except=c("V1", "V2"))
+  testthat::expect_equal(mean(dfZ$V3), 0)
 
-  x <- data.frame(x = c(8, 10, 12))
-  x <- psycho::normalize(x)
-  testthat::expect_equal(mean(x$x), 0)
 })