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Removing remaining documentation referrences to reshape

ggpcp stated it was using reshape::melt, but it is actually
using reshape2::melt.

The scale arguments to ggorder and ggstructure had a scale
argument that was no longer used (corresponding argument in
ggpcp removed in 030fadf.
Removed this argument (and its documentation which referenced
reshape).
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BrianDiggs committed Apr 13, 2012
1 parent a4b2a99 commit f4333c87d5f1c220ff81c9e692d1f2a037a32269
Showing with 11 additions and 18 deletions.
  1. +3 −0 NEWS
  2. +5 −9 R/templates.r
  3. +1 −4 man/ggorder.Rd
  4. +1 −1 man/ggpcp.Rd
  5. +1 −4 man/ggstructure.Rd
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3 NEWS
@@ -1,3 +1,6 @@
+* `ggstructure` and `ggorder`, which call `ggpcp`, no longer have a
+ `scale` argument since `ggpcp` does not have one.
+
* built in datasets have been checked to make sure they use characters,
factors and ordered factors appropriately
View
@@ -2,7 +2,7 @@
#'
#' One way to think about a parallel coordinates plot, is as plotting
#' the data after it has been transformed to gain a new variable. This
-#' function does this using \code{\link[reshape]{melt}}.
+#' function does this using \code{\link[reshape2]{melt}}.
#'
#' This gives us enormous flexibility as we have separated out the
#' type of drawing (lines by tradition) and can now use any of the existing
@@ -148,13 +148,11 @@ ggmissing <- function(data, avoid="stack", order=TRUE, missing.only = TRUE) {
#' A plot which aims to reveal gross structural anomalies in the data.
#'
#' @param data data set to plot
-#' @param scale type of scaling to use. See \code{\link[reshape]{rescaler}}
-#' for options
#' @export
#' @examples
#' ggstructure(mtcars)
-ggstructure <- function(data, scale = "rank") {
- ggpcp(data, scale=scale) +
+ggstructure <- function(data) {
+ ggpcp(data) +
aes_string(y="ROWID", fill="value", x="variable") +
geom_tile() +
scale_y_continuous("row number", expand = c(0, 1)) +
@@ -164,11 +162,9 @@ ggstructure <- function(data, scale = "rank") {
#' A plot to investigate the order in which observations were recorded.
#'
#' @param data data set to plot
-#' @param scale type of scaling to use. See \code{\link[reshape]{rescaler}}
-#' for options
#' @export
-ggorder <- function(data, scale="rank") {
- ggpcp(data, scale="rank") +
+ggorder <- function(data) {
+ ggpcp(data) +
aes_string(x="ROWID", group="variable", y="value") +
facet_grid(. ~ variable) +
geom_line() +
View
@@ -2,13 +2,10 @@
\alias{ggorder}
\title{A plot to investigate the order in which observations were recorded.}
\usage{
- ggorder(data, scale = "rank")
+ ggorder(data)
}
\arguments{
\item{data}{data set to plot}
-
- \item{scale}{type of scaling to use. See
- \code{\link[reshape]{rescaler}} for options}
}
\description{
A plot to investigate the order in which observations
View
@@ -16,7 +16,7 @@
One way to think about a parallel coordinates plot, is as
plotting the data after it has been transformed to gain a
new variable. This function does this using
- \code{\link[reshape]{melt}}.
+ \code{\link[reshape2]{melt}}.
}
\details{
This gives us enormous flexibility as we have separated
View
@@ -2,13 +2,10 @@
\alias{ggstructure}
\title{A plot which aims to reveal gross structural anomalies in the data.}
\usage{
- ggstructure(data, scale = "rank")
+ ggstructure(data)
}
\arguments{
\item{data}{data set to plot}
-
- \item{scale}{type of scaling to use. See
- \code{\link[reshape]{rescaler}} for options}
}
\description{
A plot which aims to reveal gross structural anomalies in

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