diff --git a/R-package/NAMESPACE b/R-package/NAMESPACE
index ac74b8434..a1d296d80 100644
--- a/R-package/NAMESPACE
+++ b/R-package/NAMESPACE
@@ -16,6 +16,7 @@ export(xgb.save)
 export(xgb.save.raw)
 export(xgb.train)
 export(xgboost)
+exportMethods(nrow)
 exportMethods(predict)
 import(methods)
 importClassesFrom(Matrix,dgCMatrix)
@@ -52,4 +53,3 @@ importFrom(stringr,str_match)
 importFrom(stringr,str_replace)
 importFrom(stringr,str_split)
 importFrom(stringr,str_trim)
-import(vcd)
diff --git a/R-package/R/getinfo.xgb.DMatrix.R b/R-package/R/getinfo.xgb.DMatrix.R
index 6e291fe62..26523699a 100644
--- a/R-package/R/getinfo.xgb.DMatrix.R
+++ b/R-package/R/getinfo.xgb.DMatrix.R
@@ -4,6 +4,15 @@ setClass('xgb.DMatrix')
 #' 
 #' Get information of an xgb.DMatrix object
 #' 
+#' The information can be one of the following:
+#' 
+#' \itemize{
+#'     \item \code{label}: label Xgboost learn from ;
+#'     \item \code{weight}: to do a weight rescale ;
+#'     \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
+#'     \item \code{nrow}: number of rows of the \code{xgb.DMatrix}.
+#' }
+#' 
 #' @examples
 #' data(agaricus.train, package='xgboost')
 #' train <- agaricus.train
@@ -19,7 +28,9 @@ getinfo <- function(object, ...){
     UseMethod("getinfo")
 }
 
-#' @param object Object of class "xgb.DMatrix"
+
+
+#' @param object Object of class \code{xgb.DMatrix}
 #' @param name the name of the field to get
 #' @param ... other parameters
 #' @rdname getinfo
diff --git a/R-package/R/nrow.xgb.DMatrix.R b/R-package/R/nrow.xgb.DMatrix.R
new file mode 100644
index 000000000..9ea039764
--- /dev/null
+++ b/R-package/R/nrow.xgb.DMatrix.R
@@ -0,0 +1,19 @@
+setGeneric("nrow")
+
+#' @title Number of xgb.DMatrix rows
+#' @description \code{nrow} return the number of rows present in the \code{xgb.DMatrix}.
+#' @param x Object of class \code{xgb.DMatrix}
+#' 
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' train <- agaricus.train
+#' dtrain <- xgb.DMatrix(train$data, label=train$label)
+#' stopifnot(nrow(dtrain) == nrow(train$data))
+#' 
+#' @export
+setMethod("nrow",
+          signature = "xgb.DMatrix",
+          definition = function(x) {
+            xgb.numrow(x)
+          }
+)
diff --git a/R-package/R/setinfo.xgb.DMatrix.R b/R-package/R/setinfo.xgb.DMatrix.R
index 579d9fbcf..61019d8e2 100644
--- a/R-package/R/setinfo.xgb.DMatrix.R
+++ b/R-package/R/setinfo.xgb.DMatrix.R
@@ -2,6 +2,15 @@
 #' 
 #' Set information of an xgb.DMatrix object
 #' 
+#' It can be one of the following:
+#' 
+#' \itemize{
+#'     \item \code{label}: label Xgboost learn from ;
+#'     \item \code{weight}: to do a weight rescale ;
+#'     \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
+#'     \item \code{group}.
+#' }
+#' 
 #' @examples
 #' data(agaricus.train, package='xgboost')
 #' train <- agaricus.train
diff --git a/R-package/R/xgboost.R b/R-package/R/xgboost.R
index f20b260c9..1007cb91d 100644
--- a/R-package/R/xgboost.R
+++ b/R-package/R/xgboost.R
@@ -45,7 +45,7 @@
 #' train <- agaricus.train
 #' test <- agaricus.test
 #' bst <- xgboost(data = train$data, label = train$label, max.depth = 2, 
-#'                eta = 1, nthread = 2, nround = 2,objective = "binary:logistic")
+#'                eta = 1, nthread = 2, nround = 2, objective = "binary:logistic")
 #' pred <- predict(bst, test$data)
 #' 
 #' @export
diff --git a/R-package/man/getinfo.Rd b/R-package/man/getinfo.Rd
index 37e0ad0be..618d0d44b 100644
--- a/R-package/man/getinfo.Rd
+++ b/R-package/man/getinfo.Rd
@@ -11,7 +11,7 @@ getinfo(object, ...)
 \S4method{getinfo}{xgb.DMatrix}(object, name)
 }
 \arguments{
-\item{object}{Object of class "xgb.DMatrix"}
+\item{object}{Object of class \code{xgb.DMatrix}}
 
 \item{...}{other parameters}
 
@@ -20,6 +20,16 @@ getinfo(object, ...)
 \description{
 Get information of an xgb.DMatrix object
 }
+\details{
+The information can be one of the following:
+
+\itemize{
+    \item \code{label}: label Xgboost learn from ;
+    \item \code{weight}: to do a weight rescale ;
+    \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
+    \item \code{nrow}: number of rows of the \code{xgb.DMatrix}.
+}
+}
 \examples{
 data(agaricus.train, package='xgboost')
 train <- agaricus.train
diff --git a/R-package/man/nrow-xgb.DMatrix-method.Rd b/R-package/man/nrow-xgb.DMatrix-method.Rd
new file mode 100644
index 000000000..953e620bf
--- /dev/null
+++ b/R-package/man/nrow-xgb.DMatrix-method.Rd
@@ -0,0 +1,22 @@
+% Generated by roxygen2 (4.1.0): do not edit by hand
+% Please edit documentation in R/nrow.xgb.DMatrix.R
+\docType{methods}
+\name{nrow,xgb.DMatrix-method}
+\alias{nrow,xgb.DMatrix-method}
+\title{Number of xgb.DMatrix rows}
+\usage{
+\S4method{nrow}{xgb.DMatrix}(x)
+}
+\arguments{
+\item{x}{Object of class \code{xgb.DMatrix}}
+}
+\description{
+\code{nrow} return the number of rows present in the \code{xgb.DMatrix}.
+}
+\examples{
+data(agaricus.train, package='xgboost')
+train <- agaricus.train
+dtrain <- xgb.DMatrix(train$data, label=train$label)
+stopifnot(nrow(dtrain) == nrow(train$data))
+}
+
diff --git a/R-package/man/setinfo.Rd b/R-package/man/setinfo.Rd
index 4ed262b46..9512f1dfb 100644
--- a/R-package/man/setinfo.Rd
+++ b/R-package/man/setinfo.Rd
@@ -22,6 +22,16 @@ setinfo(object, ...)
 \description{
 Set information of an xgb.DMatrix object
 }
+\details{
+It can be one of the following:
+
+\itemize{
+    \item \code{label}: label Xgboost learn from ;
+    \item \code{weight}: to do a weight rescale ;
+    \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
+    \item \code{group}.
+}
+}
 \examples{
 data(agaricus.train, package='xgboost')
 train <- agaricus.train
diff --git a/R-package/man/xgboost.Rd b/R-package/man/xgboost.Rd
index cb9da74f7..a0ec42a9b 100644
--- a/R-package/man/xgboost.Rd
+++ b/R-package/man/xgboost.Rd
@@ -59,7 +59,7 @@ data(agaricus.test, package='xgboost')
 train <- agaricus.train
 test <- agaricus.test
 bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
-               eta = 1, nthread = 2, nround = 2,objective = "binary:logistic")
+               eta = 1, nthread = 2, nround = 2, objective = "binary:logistic")
 pred <- predict(bst, test$data)
 }