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author | luzpaz <luzpaz@users.noreply.github.com> | 2019-05-31 03:13:33 -0400 |
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committer | Matti Picus <matti.picus@gmail.com> | 2019-05-31 10:13:33 +0300 |
commit | 0c70787c04d7b0febacb14edfe214cb68d87b6c3 (patch) | |
tree | a518387f3e9134d753ac4d09009ab4764a8dd4b2 /numpy/doc | |
parent | 43465f725bc47a36f08c5e69a61c2702a97491b8 (diff) | |
download | numpy-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.py | 2 | ||||
-rw-r--r-- | numpy/doc/indexing.py | 5 |
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 |