[doc] Update references to NumPy (GH-22458) (GH-28749)

Numeric(al) Python to NumPy. It seems the old name hasn't been used for some time.
(cherry picked from commit c8bb24166e367d449158015cb9b1093f03c7175d)

Co-authored-by: Andre Delfino <adelfino@gmail.com>

diff --git a/Doc/faq/programming.rst b/Doc/faq/programming.rst
index 04d6592aeccdbe218085b34bc5186a0d33e5c2e0..4e04b10b0dae6cb4ff3e181d9cee911dbd22db61 100644 (file)
--- a/Doc/faq/programming.rst
+++ b/Doc/faq/programming.rst
@@ -1184,7 +1184,7 @@ difference is that a Python list can contain objects of many different types.
 
 The ``array`` module also provides methods for creating arrays of fixed types
 with compact representations, but they are slower to index than lists.  Also
-note that the Numeric extensions and others define array-like structures with
+note that NumPy and other third party packages define array-like structures with
 various characteristics as well.
 
 To get Lisp-style linked lists, you can emulate cons cells using tuples::

diff --git a/Doc/library/array.rst b/Doc/library/array.rst
index f2f7894e1bf0f0643c3fc0db9ff825e8c647fdac..f892d0983b6b37f7f08f5154549776a4542a543d 100644 (file)
--- a/Doc/library/array.rst
+++ b/Doc/library/array.rst
@@ -256,7 +256,6 @@ Examples::
       Packing and unpacking of External Data Representation (XDR) data as used in some
       remote procedure call systems.
 
-   `The Numerical Python Documentation <https://docs.scipy.org/doc/>`_
-      The Numeric Python extension (NumPy) defines another array type; see
-      http://www.numpy.org/ for further information about Numerical Python.
+   `NumPy <https://numpy.org/>`_
+      The NumPy package defines another array type.
 

diff --git a/Doc/library/functions.rst b/Doc/library/functions.rst
index 4f967825fcbbb1441faff62b0eb7ebe927afefa4..b17ca69760dbc81475d55c392b36f87e25a5d8bb 100644 (file)
--- a/Doc/library/functions.rst
+++ b/Doc/library/functions.rst
@@ -1513,14 +1513,12 @@ are always available.  They are listed here in alphabetical order.
 .. class:: slice(stop)
            slice(start, stop[, step])
 
-   .. index:: single: Numerical Python
-
    Return a :term:`slice` object representing the set of indices specified by
    ``range(start, stop, step)``.  The *start* and *step* arguments default to
    ``None``.  Slice objects have read-only data attributes :attr:`~slice.start`,
    :attr:`~slice.stop` and :attr:`~slice.step` which merely return the argument
    values (or their default).  They have no other explicit functionality;
-   however they are used by Numerical Python and other third party extensions.
+   however they are used by NumPy and other third party packages.
    Slice objects are also generated when extended indexing syntax is used.  For
    example: ``a[start:stop:step]`` or ``a[start:stop, i]``.  See
    :func:`itertools.islice` for an alternate version that returns an iterator.

diff --git a/Doc/tutorial/floatingpoint.rst b/Doc/tutorial/floatingpoint.rst
index 0c0eb526fa9ed6054231c2e7464b73beb5297146..b98de6e56a003191b5259a5f3d969224177b2cd6 100644 (file)
--- a/Doc/tutorial/floatingpoint.rst
+++ b/Doc/tutorial/floatingpoint.rst
@@ -158,7 +158,7 @@ which implements arithmetic based on rational numbers (so the numbers like
 1/3 can be represented exactly).
 
 If you are a heavy user of floating point operations you should take a look
-at the Numerical Python package and many other packages for mathematical and
+at the NumPy package and many other packages for mathematical and
 statistical operations supplied by the SciPy project. See <https://scipy.org>.
 
 Python provides tools that may help on those rare occasions when you really