Replace tabs with spaces

R/autoplot.r

@@ -10,12 +10,12 @@
 #' @export
 #' @seealso \code{\link{ggplot}} and \code{\link{fortify}}
 autoplot <- function(object, ...) {
-	UseMethod("autoplot")
+  UseMethod("autoplot")
 }
 
 #' @S3method autoplot default
 autoplot.default <- function(object, ...) {
-	error.msg <- paste("Objects of type",class(object),"not supported by autoplot.  Please use qplot() or ggplot() instead.\n")
-	stop(error.msg, call.=FALSE)
+  error.msg <- paste("Objects of type",class(object),"not supported by autoplot.  Please use qplot() or ggplot() instead.\n")
+  stop(error.msg, call.=FALSE)
 }
 

R/ggplot2.r

@@ -36,13 +36,13 @@ NULL
 #' This dataset was produced from US economic time series data available from \url{http://research.stlouisfed.org/fred2}.
 #' 
 #' \itemize{
-#' 	\item date.  Month of data collection
+#'   \item date.  Month of data collection
 #' 
-#' 	\item psavert, personal savings rate, \url{http://research.stlouisfed.org/fred2/series/PSAVERT/}
-#' 	\item pce, personal consumption expenditures, in billions of dollars, \url{http://research.stlouisfed.org/fred2/series/PCE}
-#' 	\item unemploy, number of unemployed in thousands, \url{http://research.stlouisfed.org/fred2/series/UNEMPLOY}
-#' 	\item uempmed, median duration of unemployment, in week, \url{http://research.stlouisfed.org/fred2/series/UEMPMED}
-#' 	\item pop, total population, in thousands, \url{http://research.stlouisfed.org/fred2/series/POP}
+#'   \item psavert, personal savings rate, \url{http://research.stlouisfed.org/fred2/series/PSAVERT/}
+#'   \item pce, personal consumption expenditures, in billions of dollars, \url{http://research.stlouisfed.org/fred2/series/PCE}
+#'   \item unemploy, number of unemployed in thousands, \url{http://research.stlouisfed.org/fred2/series/UNEMPLOY}
+#'   \item uempmed, median duration of unemployment, in week, \url{http://research.stlouisfed.org/fred2/series/UEMPMED}
+#'   \item pop, total population, in thousands, \url{http://research.stlouisfed.org/fred2/series/POP}
 #' 
 #' }
 #'
@@ -111,15 +111,15 @@ NULL
 #' Movies were selected for inclusion if they had a known length and had been rated by at least one imdb user.  The data set contains the following fields:
 #' 
 #' \itemize{
-#' 	\item title.  Title of the movie.
-#' 	\item year.  Year of release.
-#' 	\item budget.  Total budget (if known) in US dollars
-#' 	\item length.  Length in minutes.
-#' 	\item rating.  Average IMDB user rating.
-#' 	\item votes.  Number of IMDB users who rated this movie.
-#' 	\item r1-10.  Multiplying by ten gives percentile (to nearest 10\%) of users who rated this movie a 1.
-#' 	\item mpaa.  MPAA rating.
-#' 	\item action, animation, comedy, drama, documentary, romance, short.  Binary variables representing if movie was classified as belonging to that genre.
+#'   \item title.  Title of the movie.
+#'   \item year.  Year of release.
+#'   \item budget.  Total budget (if known) in US dollars
+#'   \item length.  Length in minutes.
+#'   \item rating.  Average IMDB user rating.
+#'   \item votes.  Number of IMDB users who rated this movie.
+#'   \item r1-10.  Multiplying by ten gives percentile (to nearest 10\%) of users who rated this movie a 1.
+#'   \item mpaa.  MPAA rating.
+#'   \item action, animation, comedy, drama, documentary, romance, short.  Binary variables representing if movie was classified as belonging to that genre.
 #' }
 #' 
 #' @docType data

R/stat-sum.r

@@ -15,12 +15,12 @@
 #' # By default, all categorical variables in the plot form grouping
 #' # variables, and the default behavior in stat_sum is to show the
 #' # proportion. Specifying stat_sum with no group identifier leads to
-#' # a plot which is not meaningful:	
+#' # a plot which is not meaningful:
 #' d + stat_sum()
-#' # To correct this problem and achieve a more desirable plot, we need	
-#' # to specify which group the proportion is to be calculated over.	
-#' # There are several ways to do this:	
-#'	
+#' # To correct this problem and achieve a more desirable plot, we need
+#' # to specify which group the proportion is to be calculated over.
+#' # There are several ways to do this:
+#'
 #' # by overall proportion
 #' d + stat_sum(aes(group = 1))
 #' d + stat_sum(aes(group = 1)) + scale_size(range = c(3, 10))