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authorluzpaz <luzpaz@users.noreply.github.com>2019-05-31 03:13:33 -0400
committerMatti Picus <matti.picus@gmail.com>2019-05-31 10:13:33 +0300
commit0c70787c04d7b0febacb14edfe214cb68d87b6c3 (patch)
treea518387f3e9134d753ac4d09009ab4764a8dd4b2 /numpy/doc
parent43465f725bc47a36f08c5e69a61c2702a97491b8 (diff)
downloadnumpy-0c70787c04d7b0febacb14edfe214cb68d87b6c3.tar.gz
MAINT: Misc. typo fixes (#13664)
* DOC, MAINT: Misc. typo fixes Found via `codespell`
Diffstat (limited to 'numpy/doc')
-rw-r--r--numpy/doc/basics.py2
-rw-r--r--numpy/doc/indexing.py5
2 files changed, 4 insertions, 3 deletions
diff --git a/numpy/doc/basics.py b/numpy/doc/basics.py
index 61f5bf4ef..7946c6432 100644
--- a/numpy/doc/basics.py
+++ b/numpy/doc/basics.py
@@ -276,7 +276,7 @@ but gives 1874919424 (incorrect) for a 32-bit integer.
The behaviour of NumPy and Python integer types differs significantly for
integer overflows and may confuse users expecting NumPy integers to behave
similar to Python's ``int``. Unlike NumPy, the size of Python's ``int`` is
-flexible. This means Python integers may expand to accomodate any integer and
+flexible. This means Python integers may expand to accommodate any integer and
will not overflow.
NumPy provides `numpy.iinfo` and `numpy.finfo` to verify the
diff --git a/numpy/doc/indexing.py b/numpy/doc/indexing.py
index b752582c2..676015668 100644
--- a/numpy/doc/indexing.py
+++ b/numpy/doc/indexing.py
@@ -1,4 +1,5 @@
-"""==============
+"""
+==============
Array indexing
==============
@@ -107,7 +108,7 @@ arrays and thus greatly improve performance.
It is possible to use special features to effectively increase the
number of dimensions in an array through indexing so the resulting
-array aquires the shape needed for use in an expression or with a
+array acquires the shape needed for use in an expression or with a
specific function.
Index arrays