Merge pull request #19911 from DimitriPapadopoulos/codespell

DOC: Typos found by codespell

6 files changed, 8 insertions, 8 deletions

diff --git a/doc/source/user/basics.creation.rst b/doc/source/user/basics.creation.rst
index 5fb4f66f6..84ff1c30e 100644
--- a/doc/source/user/basics.creation.rst
+++ b/doc/source/user/basics.creation.rst
@@ -115,7 +115,7 @@ examples are shown::
 Note: best practice for :func:`numpy.arange` is to use integer start, end, and
 step values. There are some subtleties regarding ``dtype``. In the second
 example, the ``dtype`` is defined. In the third example, the array is
-``dtype=float`` to accomodate the step size of ``0.1``. Due to roundoff error,
+``dtype=float`` to accommodate the step size of ``0.1``. Due to roundoff error,
 the ``stop`` value is sometimes included. 
 
 :func:`numpy.linspace` will create arrays with a specified number of elements, and
diff --git a/doc/source/user/c-info.how-to-extend.rst b/doc/source/user/c-info.how-to-extend.rst
index ebb4b7518..96727a177 100644
--- a/doc/source/user/c-info.how-to-extend.rst
+++ b/doc/source/user/c-info.how-to-extend.rst
@@ -433,7 +433,7 @@ writeable). The syntax is
 
         The requirements flag allows specification of what kind of
         array is acceptable. If the object passed in does not satisfy
-        this requirements then a copy is made so that thre returned
+        this requirements then a copy is made so that the returned
         object will satisfy the requirements. these ndarray can use a
         very generic pointer to memory.  This flag allows specification
         of the desired properties of the returned array object. All
diff --git a/doc/source/user/c-info.python-as-glue.rst b/doc/source/user/c-info.python-as-glue.rst
index 8643d0dd1..2798aa08a 100644
--- a/doc/source/user/c-info.python-as-glue.rst
+++ b/doc/source/user/c-info.python-as-glue.rst
@@ -1115,7 +1115,7 @@ SWIG
 Simplified Wrapper and Interface Generator (SWIG) is an old and fairly
 stable method for wrapping C/C++-libraries to a large variety of other
 languages. It does not specifically understand NumPy arrays but can be
-made useable with NumPy through the use of typemaps. There are some
+made usable with NumPy through the use of typemaps. There are some
 sample typemaps in the numpy/tools/swig directory under numpy.i together
 with an example module that makes use of them. SWIG excels at wrapping
 large C/C++ libraries because it can (almost) parse their headers and
diff --git a/doc/source/user/how-to-how-to.rst b/doc/source/user/how-to-how-to.rst
index 13d2b405f..cdf1ad5c3 100644
--- a/doc/source/user/how-to-how-to.rst
+++ b/doc/source/user/how-to-how-to.rst
@@ -102,7 +102,7 @@ knowledge).
 
 We distinguish both tutorials and how-tos from `Explanations`, which are
 deep dives intended to give understanding rather than immediate assistance,
-and `References`, which give complete, autoritative data on some concrete
+and `References`, which give complete, authoritative data on some concrete
 part of NumPy (like its API) but aren't obligated to paint a broader picture.
 
 For more on tutorials, see :doc:`content/tutorial-style-guide`
diff --git a/doc/source/user/misc.rst b/doc/source/user/misc.rst
index f0a7f5e4c..316473151 100644
--- a/doc/source/user/misc.rst
+++ b/doc/source/user/misc.rst
@@ -143,7 +143,7 @@ Only a survey of the choices. Little detail on how each works.
  - Plusses:
 
    - part of Python standard library
-   - good for interfacing to existing sharable libraries, particularly
+   - good for interfacing to existing shareable libraries, particularly
      Windows DLLs
    - avoids API/reference counting issues
    - good numpy support: arrays have all these in their ctypes
diff --git a/doc/source/user/numpy-for-matlab-users.rst b/doc/source/user/numpy-for-matlab-users.rst
index ed0be82a0..21e23482a 100644
--- a/doc/source/user/numpy-for-matlab-users.rst
+++ b/doc/source/user/numpy-for-matlab-users.rst
@@ -313,11 +313,11 @@ Linear algebra equivalents
 
    * - ``a(:,find(v > 0.5))``
      - ``a[:,np.nonzero(v > 0.5)[0]]``
-     - extract the columms of ``a`` where vector v > 0.5
+     - extract the columns of ``a`` where vector v > 0.5
 
    * - ``a(:,find(v>0.5))``
      - ``a[:, v.T > 0.5]``
-     - extract the columms of ``a`` where column vector v > 0.5
+     - extract the columns of ``a`` where column vector v > 0.5
 
    * - ``a(a<0.5)=0``
      - ``a[a < 0.5]=0``
@@ -819,6 +819,6 @@ found in the `topical software page <https://scipy.org/topical-software.html>`__
 See
 `List of Python software: scripting
 <https://en.wikipedia.org/wiki/List_of_Python_software#Embedded_as_a_scripting_language>`_
-for a list of softwares that use Python as a scripting language
+for a list of software that use Python as a scripting language
 
 MATLAB® and SimuLink® are registered trademarks of The MathWorks, Inc.