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| -rw-r--r-- | Doc/faq/programming.rst | 2 | ||||
| -rw-r--r-- | Doc/library/array.rst | 5 | ||||
| -rw-r--r-- | Doc/library/functions.rst | 4 | ||||
| -rw-r--r-- | Doc/tutorial/floatingpoint.rst | 2 |
4 files changed, 5 insertions, 8 deletions
diff --git a/Doc/faq/programming.rst b/Doc/faq/programming.rst index 76ae4d2..0b486d7 100644 --- a/Doc/faq/programming.rst +++ b/Doc/faq/programming.rst @@ -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:: diff --git a/Doc/library/array.rst b/Doc/library/array.rst index 7802073..ff3ec6b 100644 --- a/Doc/library/array.rst +++ b/Doc/library/array.rst @@ -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. diff --git a/Doc/library/functions.rst b/Doc/library/functions.rst index 7543fc4..c49bb0c 100644 --- a/Doc/library/functions.rst +++ b/Doc/library/functions.rst @@ -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. diff --git a/Doc/tutorial/floatingpoint.rst b/Doc/tutorial/floatingpoint.rst index 0c0eb52..b98de6e 100644 --- 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 |