numpy · mattip · Aug 4, 2023 · Aug 4, 2023
diff --git a/doc/source/reference/arrays.dtypes.rst b/doc/source/reference/arrays.dtypes.rst
@@ -176,16 +176,16 @@ Built-in Python types
     Several python types are equivalent to a corresponding
     array scalar when used to generate a :class:`dtype` object:
 
-    ================  ===============
-    :class:`int`      :class:`int\_`
-    :class:`bool`     :class:`bool\_`
-    :class:`float`    :class:`float\_`
-    :class:`complex`  :class:`cfloat`
-    :class:`bytes`    :class:`bytes\_`
-    :class:`str`      :class:`str\_`
-    :class:`buffer`   :class:`void`
-    (all others)      :class:`object_`
-    ================  ===============
+    ===================      ===============
+    :class:`int`             :class:`int\_`
+    :class:`bool`            :class:`bool\_`
+    :class:`float`           :class:`float\_`
+    :class:`complex`         :class:`cfloat`
+    :class:`bytes`           :class:`bytes\_`
+    :class:`str`             :class:`str\_`
+    :class:`memoryview`      :class:`void`
+    (all others)             :class:`object_`
+    ===================      ===============
 
     Note that ``str_`` corresponds to UCS4 encoded unicode strings, while
     ``string_`` is an alias to ``bytes_``. The name ``np.unicode_`` is also

diff --git a/doc/source/reference/arrays.interface.rst b/doc/source/reference/arrays.interface.rst
@@ -179,7 +179,7 @@ This approach to the interface consists of the object having an
 
    **offset** (optional)
        An integer offset into the array data region. This can only be
-       used when data is ``None`` or returns a :class:`buffer`
+       used when data is ``None`` or returns a :class:`memoryview`
        object.
 
        **Default**: ``0``.

diff --git a/doc/source/reference/arrays.ndarray.rst b/doc/source/reference/arrays.ndarray.rst
@@ -26,7 +26,7 @@ changes made in one :class:`ndarray` may be visible in another. That
 is, an ndarray can be a *"view"* to another ndarray, and the data it
 is referring to is taken care of by the *"base"* ndarray. ndarrays can
 also be views to memory owned by Python :class:`strings <str>` or
-objects implementing the :class:`buffer` or :ref:`array
+objects implementing the :class:`memoryview` or :ref:`array
 <arrays.interface>` interfaces.