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authorCharles Harris <charlesr.harris@gmail.com>2020-12-13 14:14:49 -0700
committerGitHub <noreply@github.com>2020-12-13 14:14:49 -0700
commit3fe2d9d2627fc0f84aeed293ff8afa7c1f08d899 (patch)
tree2ea27fe06a19c39e8d7a5fe2f87cb7e05363247d /doc/source/reference/arrays.classes.rst
parent7d7e446fcbeeff70d905bde2eb0264a797488280 (diff)
parenteff302e5e8678fa17fb3d8156d49eb585b0876d9 (diff)
downloadnumpy-3fe2d9d2627fc0f84aeed293ff8afa7c1f08d899.tar.gz
Merge branch 'master' into fix-issue-10244
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