numpy
diff --git a/‎doc/source/user/basics.copies.rst
Lines changed: 2 additions & 0 deletions b/‎doc/source/user/basics.copies.rst
Lines changed: 2 additions & 0 deletions
diff --git a/‎doc/source/user/basics.indexing.rst
Lines changed: 5 additions & 1 deletion b/‎doc/source/user/basics.indexing.rst
Lines changed: 5 additions & 1 deletion
@@ -39,6 +39,8 @@ do not reflect on the original array. Making a copy is slower and
 memory-consuming but sometimes necessary. A copy can be forced by using
 :meth:`.ndarray.copy`.
 
+.. _indexing-operations:
+
 Indexing operations
 ===================
 
 
@@ -28,6 +28,7 @@ Note that in Python, ``x[(exp1, exp2, ..., expN)]`` is equivalent to
 ``x[exp1, exp2, ..., expN]``; the latter is just syntactic sugar
 for the former.
 
+.. _basic-indexing:
 
 Basic indexing
 --------------
@@ -88,6 +89,7 @@ that is subsequently indexed by 2.
     rapidly changing location in memory. This difference represents a
     great potential for confusion.
 
+.. _slicing-and-striding:
 
 Slicing and striding
 ^^^^^^^^^^^^^^^^^^^^
@@ -226,6 +228,7 @@ concepts to remember include:
 .. index::
    pair: ndarray; view
 
+.. _dimensional-indexing-tools:
 
 Dimensional indexing tools
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -470,6 +473,7 @@ such an array with an image with shape (ny, nx) with dtype=np.uint8
 lookup table) will result in an array of shape (ny, nx, 3) where a
 triple of RGB values is associated with each pixel location.
 
+.. _boolean-indexing:
 
 Boolean array indexing
 ^^^^^^^^^^^^^^^^^^^^^^
@@ -851,7 +855,7 @@ For this reason, it is possible to use the output from the
 :meth:`np.nonzero() <ndarray.nonzero>` function directly as an index since
 it always returns a tuple of index arrays.
 
-Because the special treatment of tuples, they are not automatically
+Because of the special treatment of tuples, they are not automatically
 converted to an array as a list would be. As an example: ::
 
  >>> z[[1, 1, 1, 1]]  # produces a large array