Cleaning up R code and adding RStudio project.

.gitignore

@@ -1,2 +1,3 @@
 *.html
 .Rhistory
+.Rproj.user

REDCapRITS.Rproj

@@ -0,0 +1,16 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+AutoAppendNewline: Yes
+StripTrailingWhitespace: Yes

REDCap_split.r

@@ -1,7 +1,6 @@
-# v0.0.0
 #' Split REDCap repeating instruments table into multiple tables
 #'
-#' This will take a raw data frame from REDCap and split it into a base table
+#' This will take a raw \code{data.frame} from REDCap and split it into a base table
 #' and give individual tables for each repeating instrument. Metadata
 #' is used to determine which fields should be included in each resultant table.
 #'
@@ -12,7 +11,7 @@
 #' \dontrun{
 #' library(jsonlite)
 #' library(RCurl)
-#' 
+#'
 #' # Get the metadata
 #' result.meta <- postForm(
 #'     api_url,
@@ -20,7 +19,7 @@
 #'     content = 'metadata',
 #'     format = 'json'
 #' )
-#' 
+#'
 #' # Get the records
 #' result.record <- postForm(
 #'     uri = api_url,
@@ -35,7 +34,7 @@
 #'     exportDataAccessGroups = 'false',
 #'     returnFormat = 'json'
 #' )
-#' 
+#'
 #' records <- fromJSON(result.record)
 #' metadata <- fromJSON(result.meta)
 #'
@@ -45,43 +44,46 @@
 #' @export
 REDCap_split <- function(records, metadata) {
 
-	# Check to see if there were any repeating instruments
+  stopifnot(all(sapply(list(records,metadata), inherits, "data.frame")))
 
-	if (!any(names(records) == "redcap_repeat_instrument")) {
+  # Check to see if there were any repeating instruments
 
-		warning("There are no repeating instruments.\n")
+  if (!any(names(records) == "redcap_repeat_instrument")) {
 
-		return(list(records))
+    message("There are no repeating instruments in this data.")
 
-	}
+    return(list(records))
 
-	# Clean the metadata
-	metadata <- metadata[metadata["field_type"] != "descriptive", 1:4]
+  }
 
-	# Identify the subtables in the data
-	subtables <- unique(records["redcap_repeat_instrument"])
-	subtables <- subtables[subtables != ""]
+  # Clean the metadata
+  metadata <-
+    metadata[metadata$field_type != "descriptive", c("field_name", "form_name")]
 
-	# Split the table based on instrument
-	out <- split.data.frame(records, records["redcap_repeat_instrument"])
+  # Identify the subtables in the data
+  subtables <- unique(records$redcap_repeat_instrument)
+  subtables <- subtables[subtables != ""]
 
-	# Delete the variables that are not relevant
-	for (i in names(out)) {
+  # Split the table based on instrument
+  out <- split.data.frame(records, records$redcap_repeat_instrument)
 
-		if (i == "") {
+  # Delete the variables that are not relevant
+  for (i in names(out)) {
 
-			out[[which(names(out) == "")]] <-
-				out[[which(names(out) == "")]][metadata[`!`(metadata[,2] %in% subtables), 1]]
+    if (i == "") {
 
-		} else {
+      out[[which(names(out) == "")]] <-
+        out[[which(names(out) == "")]][metadata[!metadata[,2] %in% subtables, 1]]
 
-			out[[i]] <-
-				out[[i]][c(names(records[1:3]),metadata[metadata[,2] == i, 1])]
+    } else {
 
-		}
+      out[[i]] <-
+        out[[i]][c(names(records[1:3]),metadata[metadata[,2] == i, 1])]
 
-	}
+    }
 
-	return(out)
+  }
+
+  return(out)
 
 }