diff --git a/libs/numpy/example/ndarray.cpp b/libs/numpy/example/ndarray.cpp
index 9bfd5dc5..3ab28f97 100644
--- a/libs/numpy/example/ndarray.cpp
+++ b/libs/numpy/example/ndarray.cpp
@@ -3,6 +3,8 @@
  *         The Python sequence could be any object whose __array__ method returns an array, or any (nested) sequence.
  *
  *  @todo Find a way to create a list explicitly
+ *	  
+
  *        
  */
 
@@ -23,11 +25,21 @@ int main(int argc, char **argv)
   np::ndarray example_tuple = np::array (tu) ; 
   // and from a list
   p::list l ;
-  l.append('a') ;
   np::ndarray example_list = np::array (l) ; 
   // Optionally, you can also specify a dtype
   np::dtype dt = np::dtype::get_builtin<int>();
   np::ndarray example_list1 = np::array (l,dt);
+  // You can also create an array by supplying data.First,create an integer array
+  int data[] = {1,2,3,4} ;
+  // Create a shape, and strides, needed by the function
+  p::tuple shape = p::make_tuple(2,2) ;
+  p::tuple strides = p::make_tuple(strides(data)) ; 
+  // The function also needs an owner, to keep track of the data array passed. Passing none is dangerous
+  p::object owner ;
+  // The from_data function takes the data array, datatype,shape,stride and owner as arguments
+  // and returns an ndarray
+  np::ndarray data_ex1 = np::from_data(data,dt, shape,strides,owner);
+
 }
 
 
diff --git a/libs/numpy/example/simple.cpp b/libs/numpy/example/simple.cpp
index d375b35c..b1f2dc3f 100644
--- a/libs/numpy/example/simple.cpp
+++ b/libs/numpy/example/simple.cpp
@@ -21,6 +21,8 @@ int main(int argc, char **argv)
   np::dtype dtype = np::dtype::get_builtin<float>();
   // Construct an array with the above shape and type
   np::ndarray a = np::zeros(shape, dtype);
+  // Construct an empty array with the above shape and dtype as well
+  np::ndarray b = np::empty(shape,dtype);
   // Print the array
   std::cout << "Original array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
   // Reshape the array into a 1D array