changed to data.frame instead of as.data.frame

which allows check.names = FALSE, which - I hope - closes #76

R/crosstab.R

@@ -44,7 +44,7 @@ crosstab <- function(...) UseMethod("crosstab")
 #' @rdname crosstab
 #' @export
 crosstab.default <- function(vec1, vec2, percent = "none", show_na = TRUE, ...){
-
+  
   if(!mode(vec1) %in% c("logical", "numeric", "character", "list") | is.matrix(vec1)){
     stop("vec1 must be a vector of type logical, numeric, character, list, or factor")}
   if(!mode(vec2) %in% c("logical", "numeric", "character","list") | is.matrix(vec2)){
@@ -53,20 +53,20 @@ crosstab.default <- function(vec1, vec2, percent = "none", show_na = TRUE, ...){
   if(! percent %in% c("none", "row", "col", "all")){stop("'percent' must be one of 'none', 'row', 'col', or 'all'")}
 
   if(length(vec1) != length(vec2)){ stop("the two vectors are not the same length")}
-
+  
   dat <- data.frame(vec1 = vec1,
                     vec2 = vec2,
                     stringsAsFactors = FALSE)
 
   dat_col_names <- names(dat)
-
+  
   if(is.null(names(vec1))) {
     var_name <- deparse(substitute(vec1))
   } else {
     var_name <- names(vec1)
   }
-
-
+  
+  
   if(!show_na){
     dat <- dat[!is.na(dat[[1]]) & !is.na(dat[[2]]), ]
   }
@@ -75,15 +75,15 @@ crosstab.default <- function(vec1, vec2, percent = "none", show_na = TRUE, ...){
   tabl <- dat %>%
     dplyr::count_(dat_col_names) %>%
     dplyr::ungroup()
-
-
+  
+  
   # replace NA with string NA_ in vec2 to avoid invalid col name after spreading
   # if this col is a factor, need to add that level to the factor
   if(is.factor(tabl[[2]])){
     levels(tabl[[2]]) <- c(levels(tabl[[2]]), "NA_")
   }
   tabl[2][is.na(tabl[2])] <- "NA_"
-
+  
   # spread to wide, ungroup() for cleanliness of result, and rename 1st col
   result <- tabl %>%
     tidyr::spread_(dat_col_names[[2]], "n", fill = 0) %>%
@@ -106,27 +106,27 @@ crosstab.data.frame <- function(.data, ...){
   # collect dots
   dots <- as.list(substitute(list(...)))[-1L] #
   n <- length(dots)
-
+  
   # select columns from .data
   columns <- dots[1:2]
   if(dots[[1]] == dots[[2]]){stop("the same column name is specified for both input variables.  Use tabyl() for tabulating a single variable")}
 
   x <- list()
   x[[deparse(columns[[1]])]] <- .data[,deparse(columns[[1]])]
   x[[deparse(columns[[2]])]] <- .data[,deparse(columns[[2]])]
-  x <- as.data.frame(x,
-                     stringsAsFactors = FALSE,
-                     check.names = FALSE) # preserve bad input names
+  x <- data.frame(x,
+                  stringsAsFactors = FALSE,
+                  check.names = FALSE) # preserve bad input names
 
   # create args list to use with do.call
   arguments <- list()
-
+  
   if(n > 2) arguments <- dots[3:n]
-
+  
   arguments$vec1 <- x[1]
   arguments$vec2 <- x[2]
 
   do.call(crosstab.default,
           args = arguments)
-
+  
 }

R/tabyl.R

@@ -108,9 +108,10 @@ tabyl.data.frame <- function(.data, ...){
   columns <- dots[1]
   x <- list()
   x[[deparse(columns[[1]])]] <- .data[, deparse(columns[[1]])]
-  x <- as.data.frame(x,
-                     stringsAsFactors = is.factor(x[[1]]),
-                     check.names = FALSE) # preserve bad input names
+
+  x <- data.frame(x,
+                  stringsAsFactors = is.factor(x[[1]]),
+                  check.names = FALSE) # preserve bad input names
 
   # create args list to use with do.call
   arguments <- list()