diff --git a/pydatastructs/trees/binary_trees.py b/pydatastructs/trees/binary_trees.py
index e197d63..b475e6c 100644
--- a/pydatastructs/trees/binary_trees.py
+++ b/pydatastructs/trees/binary_trees.py
@@ -61,7 +61,7 @@ class BinaryTree(object):
         obj.is_order_statistic = is_order_statistic
         return obj
 
-    def insert(self, key, data):
+    def insert(self, key, data=None):
         """
         Inserts data by the passed key using iterative
         algorithm.
@@ -206,7 +206,7 @@ class BinarySearchTree(BinaryTree):
                     self.right_size(self.tree[walk]) + 1)
                 walk = self.tree[walk].parent
 
-    def insert(self, key, data):
+    def insert(self, key, data=None):
         res = self.search(key)
         if res is not None:
             self.tree[res].data = data
@@ -715,7 +715,7 @@ class AVLTree(SelfBalancingBinaryTree):
             path.append(walk), path.append(last)
             walk = self.tree[walk].parent
 
-    def insert(self, key, data):
+    def insert(self, key, data=None):
         super(AVLTree, self).insert(key, data)
         self._balance_insertion(self.size - 1, self.tree[self.size-1].parent)
 
diff --git a/pydatastructs/trees/heaps.py b/pydatastructs/trees/heaps.py
index 9b6ed28..45d0bc4 100644
--- a/pydatastructs/trees/heaps.py
+++ b/pydatastructs/trees/heaps.py
@@ -440,7 +440,7 @@ class BinomialHeap(Heap):
             j += 1
         self.root_list = new_root_list
 
-    def insert(self, key, data):
+    def insert(self, key, data=None):
         """
         Inserts new node with the given key and data.
 
diff --git a/pydatastructs/trees/m_ary_trees.py b/pydatastructs/trees/m_ary_trees.py
index f0a4d38..75b6225 100644
--- a/pydatastructs/trees/m_ary_trees.py
+++ b/pydatastructs/trees/m_ary_trees.py
@@ -59,7 +59,7 @@ class MAryTree(object):
         obj.is_order_statistic = is_order_statistic
         return obj
 
-    def insert(self, key, data):
+    def insert(self, key, data=None):
         """
         Inserts data by the passed key using iterative
         algorithm.