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authorMatti Picus <matti.picus@gmail.com>2020-10-24 17:51:49 +0300
committerGitHub <noreply@github.com>2020-10-24 17:51:49 +0300
commit444bbc9a787ab1d8a487085e75772db210a77699 (patch)
treeb15713ba24e6081b396c192105f9b76ae7ef287e /doc/source/reference/arrays.classes.rst
parentbeac56601587e26563d83b0a47cd0b1f006bf5d6 (diff)
parentb0f1cc13a04dd8225f6e6fb90604c7d8379aa3a3 (diff)
downloadnumpy-444bbc9a787ab1d8a487085e75772db210a77699.tar.gz
Merge pull request #17624 from eric-wieser/fix-refs
DOC: Tidy up references to str_ / bytes_
Diffstat (limited to 'doc/source/reference/arrays.classes.rst')
-rw-r--r--doc/source/reference/arrays.classes.rst8
1 files changed, 4 insertions, 4 deletions
diff --git a/doc/source/reference/arrays.classes.rst b/doc/source/reference/arrays.classes.rst
index c5563bddd..3a4ed2168 100644
--- a/doc/source/reference/arrays.classes.rst
+++ b/doc/source/reference/arrays.classes.rst
@@ -480,16 +480,16 @@ Character arrays (:mod:`numpy.char`)
The `chararray` class exists for backwards compatibility with
Numarray, it is not recommended for new development. Starting from numpy
1.4, if one needs arrays of strings, it is recommended to use arrays of
- `dtype` `object_`, `string_` or `unicode_`, and use the free functions
+ `dtype` `object_`, `bytes_` or `str_`, and use the free functions
in the `numpy.char` module for fast vectorized string operations.
-These are enhanced arrays of either :class:`string_` type or
-:class:`unicode_` type. These arrays inherit from the
+These are enhanced arrays of either :class:`str_` type or
+:class:`bytes_` type. These arrays inherit from the
:class:`ndarray`, but specially-define the operations ``+``, ``*``,
and ``%`` on a (broadcasting) element-by-element basis. These
operations are not available on the standard :class:`ndarray` of
character type. In addition, the :class:`chararray` has all of the
-standard :class:`string <str>` (and :class:`unicode`) methods,
+standard :class:`str` (and :class:`bytes`) methods,
executing them on an element-by-element basis. Perhaps the easiest
way to create a chararray is to use :meth:`self.view(chararray)
<ndarray.view>` where *self* is an ndarray of str or unicode