diff --git a/python-package/xgboost/core.py b/python-package/xgboost/core.py
index 4693cc419..8159bea57 100644
--- a/python-package/xgboost/core.py
+++ b/python-package/xgboost/core.py
@@ -351,6 +351,14 @@ class DMatrix(object):
             None, defaults to np.nan.
         weight : list or numpy 1-D array , optional
             Weight for each instance.
+
+            .. note:: For ranking task, weights are per-group.
+
+                In ranking task, one weight is assigned to each group (not each data
+                point). This is because we only care about the relative ordering of
+                data points within each group, so it doesn't make sense to assign
+                weights to individual data points.
+
         silent : boolean, optional
             Whether print messages during construction
         feature_names : list, optional
@@ -655,6 +663,13 @@ class DMatrix(object):
         ----------
         weight : array like
             Weight for each data point
+
+            .. note:: For ranking task, weights are per-group.
+
+                In ranking task, one weight is assigned to each group (not each data
+                point). This is because we only care about the relative ordering of
+                data points within each group, so it doesn't make sense to assign
+                weights to individual data points.
         """
         self.set_float_info('weight', weight)
 
@@ -666,6 +681,13 @@ class DMatrix(object):
         ----------
         weight : array like
             Weight for each data point in numpy 2D array
+
+            .. note:: For ranking task, weights are per-group.
+
+                In ranking task, one weight is assigned to each group (not each data
+                point). This is because we only care about the relative ordering of
+                data points within each group, so it doesn't make sense to assign
+                weights to individual data points.
         """
         self.set_float_info_npy2d('weight', weight)
 
diff --git a/python-package/xgboost/sklearn.py b/python-package/xgboost/sklearn.py
index 20f5747e2..8825173d4 100644
--- a/python-package/xgboost/sklearn.py
+++ b/python-package/xgboost/sklearn.py
@@ -885,7 +885,7 @@ class XGBRanker(XGBModel):
             Whether to print messages while running boosting.
         objective : string
             Specify the learning task and the corresponding learning objective.
-            Only "rank:pairwise" is supported currently.
+            The objective name must start with "rank:".
         booster: string
             Specify which booster to use: gbtree, gblinear or dart.
         nthread : int
@@ -999,13 +999,29 @@ class XGBRanker(XGBModel):
         group : array_like
             group size of training data
         sample_weight : array_like
-            instance weights
+            group weights
+
+            .. note:: Weights are per-group for ranking tasks
+
+                In ranking task, one weight is assigned to each group (not each data
+                point). This is because we only care about the relative ordering of
+                data points within each group, so it doesn't make sense to assign
+                weights to individual data points.
+
         eval_set : list, optional
             A list of (X, y) tuple pairs to use as a validation set for
             early-stopping
         sample_weight_eval_set : list, optional
             A list of the form [L_1, L_2, ..., L_n], where each L_i is a list of
-            instance weights on the i-th validation set.
+            group weights on the i-th validation set.
+
+            .. note:: Weights are per-group for ranking tasks
+
+                In ranking task, one weight is assigned to each group (not each data
+                point). This is because we only care about the relative ordering of
+                data points within each group, so it doesn't make sense to assign
+                weights to individual data points.
+
         eval_group : list of arrays, optional
             A list that contains the group size corresponds to each
             (X, y) pair in eval_set