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

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Numeric(al) Python to NumPy. It seems the old name hasn't been used for some time.
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Andre Delfino 2020-10-01 20:22:14 -03:00 committed by GitHub
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4 changed files with 5 additions and 8 deletions
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2
Doc/faq/programming.rst
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@ -1191,7 +1191,7 @@ 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::

5
Doc/library/array.rst
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@ -257,7 +257,6 @@ 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.

4
Doc/library/functions.rst
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@ -1512,14 +1512,12 @@ 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.

2
Doc/tutorial/floatingpoint.rst
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@ -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