Data NULL #173.

R/datastep.R

@@ -180,7 +180,9 @@ e$output <- list()
 #' other techniques for processing your data.  While there is no 
 #' built-in restriction on the number of rows, performance of the
 #' \code{datastep} can become unacceptable with a large number of rows.
-#' @param data The data to step through.
+#' @param data The data to step through.  This parameter is required. Valid
+#' values are a data frame or a NULL. In the case of a NULL, you must include
+#' at least one \code{output()} function in the steps.
 #' @param steps The operations to perform on the data.  This parameter is 
 #' specified as a set of R statements contained within 
 #' curly braces. If no steps are desired, pass empty curly braces.
@@ -530,6 +532,26 @@ e$output <- list()
 #' # 2  A05  23    F   G01 Group1   1   1
 #' # 3  A02  20    M   G02 Group2   1   1
 #' # 4  A04  11    M   G03 Group3   1   1
+#' 
+#' # Example #8: Data NULL
+#' 
+#' # Create new dataset using output() functions.
+#' res <- datastep(NULL, 
+#'                 {
+#'                   ID <- 10
+#'                   Item <- "Pencil"
+#'                   output()
+#' 
+#'                   ID <- 20
+#'                   Item <- "Scissors"
+#'                   output()
+#'                 })
+#'  
+#' # View results
+#' res
+#' #   ID      Item
+#' # 1  10   Pencil
+#' # 2  20 Scissors
 #' @import dplyr
 #' @export
 datastep <- function(data, steps, keep = NULL,
@@ -548,14 +570,18 @@ datastep <- function(data, steps, keep = NULL,
                      log = TRUE, 
                      subset = NULL) {
 
-  if (!"data.frame" %in% class(data))
-    stop("input data must be inherited from data.frame")
+  if (!is.null(data)) {
+    if (!"data.frame" %in% class(data))
+      stop("input data must be inherited from data.frame")
+  }
 
 
   if (!is.null(retain)) {
     if (!"list" %in% class(retain))
       stop("retain parameter value must be of class 'list'")
 
+  } else {
+    data <- data.frame() 
   }
 
   if (!is.null(attrib)) {
@@ -587,16 +613,15 @@ datastep <- function(data, steps, keep = NULL,
   merge_by <- tryCatch({if (typeof(merge_by) %in% c("character", "NULL")) merge_by else omby},
                    error = function(cond) {omby})
 
-
-  # Capture number of starting columns
-  startcols <- ncol(data)
-
   # Put code in a variable for safe-keeping
   code <- substitute(steps, env = environment())
 
   # Determine if there is an output function
   hout <- has_output(deparse(code))
 
+  # Capture number of starting columns
+  startcols <- ncol(data)
+
   # Give warning if there are no rows and no output()
   if (hout == FALSE & nrow(data) == 0) {
     warning("Input dataset has no rows.") 

docs/pkgdown.yml

@@ -10,7 +10,7 @@ articles:
   libr-faq: libr-faq.html
   libr-management: libr-management.html
   libr: libr.html
-last_built: 2024-11-05T01:57Z
+last_built: 2024-11-05T03:56Z
 urls:
   reference: https://libr.r-sassy.org/reference
   article: https://libr.r-sassy.org/articles

tests/testthat/test-datastep.R

@@ -1833,3 +1833,38 @@ test_that("ds52: subset clause works.", {
   expect_equal(mean(df$cyl), 8)
 
 })
+
+
+test_that("ds36: output works with NULL dataset.", {
+
+  d1 <- datastep(NULL, {
+
+    bork <- 1
+    fork <- "one"
+    output()
+
+    bork <- 2
+    fork <- "two"
+    output()
+
+  })
+
+  # print(d1)
+  # print(attributes(d1))
+  # print(attributes(d1$fork))
+  d1
+
+  expect_equal(nrow(d1), 2)
+  expect_equal(ncol(d1), 2)
+  expect_equal(names(d1), c("bork", "fork"))
+  expect_equal(d1[[1, 1]], 1)
+  # if ("factor" %in% class(d1[[2, 2]]))
+  #   expect_equal(d1[[2, 2]], 2)
+  # else
+  #   expect_equal(d1[[2, 2]], "two")
+
+  expect_error(datastep(NULL, {a <- 1 }))
+
+})
+
+