Removed white space

Author: Oscar D. Lara Yejas

R/pkg/R/DataFrame.R

@@ -2165,13 +2165,13 @@ setMethod("coltypes",
           function(x) {
             # Get the data types of the DataFrame by invoking dtypes() function
             types <- sapply(dtypes(x), function(x) {x[[2]]})
-            
+
             # Map Spark data types into R's data types using DATA_TYPES environment
             rTypes <- sapply(types, USE.NAMES=F, FUN=function(x) {
-              
+
               # Check for primitive types
               type <- PRIMITIVE_TYPES[[x]]
-              
+
               if (is.null(type)) {
                 # Check for complex types
                 for (t in names(COMPLEX_TYPES)) {
@@ -2180,19 +2180,19 @@ setMethod("coltypes",
                     break
                   }
                 }
-                
+
                 if (is.null(type)) {
                   stop(paste("Unsupported data type: ", x))
                 }
               }
               type
             })
-            
+
             # Find which types don't have mapping to R
             naIndices <- which(is.na(rTypes))
-            
+
             # Assign the original scala data types to the unmatched ones
             rTypes[naIndices] <- types[naIndices]
-            
+
             rTypes
           })

R/pkg/inst/tests/test_sparkSQL.R

@@ -1506,19 +1506,19 @@ test_that("with() on a DataFrame", {
 
 test_that("Method coltypes() to get R's data types of a DataFrame", {
   expect_equal(coltypes(irisDF), c(rep("numeric", 4), "character"))
-  
+
   data <- data.frame(c1=c(1,2,3),
                      c2=c(T,F,T),
                      c3=c("2015/01/01 10:00:00", "2015/01/02 10:00:00", "2015/01/03 10:00:00"))
-  
+
   schema <- structType(structField("c1", "byte"),
                        structField("c3", "boolean"),
                        structField("c4", "timestamp"))
-  
+
   # Test primitive types
   DF <- createDataFrame(sqlContext, data, schema)
   expect_equal(coltypes(DF), c("integer", "logical", "POSIXct"))
-  
+
   # Test complex types
   x <- createDataFrame(sqlContext, list(list(as.environment(
     list("a"="b", "c"="d", "e"="f")))))