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-rw-r--r--numpy/doc/subclassing.py4
1 files changed, 2 insertions, 2 deletions
diff --git a/numpy/doc/subclassing.py b/numpy/doc/subclassing.py
index 40522bb9c..9a339430b 100644
--- a/numpy/doc/subclassing.py
+++ b/numpy/doc/subclassing.py
@@ -97,7 +97,7 @@ Implications for subclassing
If we subclass ndarray, we need to deal not only with explicit
construction of our array type, but also :ref:`view-casting` or
-:ref:`new-from-template`. Numpy has the machinery to do this, and this
+:ref:`new-from-template`. NumPy has the machinery to do this, and this
machinery that makes subclassing slightly non-standard.
There are two aspects to the machinery that ndarray uses to support
@@ -523,7 +523,7 @@ Extra gotchas - custom ``__del__`` methods and ndarray.base
One of the problems that ndarray solves is keeping track of memory
ownership of ndarrays and their views. Consider the case where we have
created an ndarray, ``arr`` and have taken a slice with ``v = arr[1:]``.
-The two objects are looking at the same memory. Numpy keeps track of
+The two objects are looking at the same memory. NumPy keeps track of
where the data came from for a particular array or view, with the
``base`` attribute: