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| author | Amrit K <amrit110@gmail.com> | 2021-04-24 13:33:01 -0400 |
|---|---|---|
| committer | Amrit K <amrit110@gmail.com> | 2021-04-24 13:37:26 -0400 |
| commit | c87959a0095ff52f1fdfc6423f29c42be46cdf40 (patch) | |
| tree | 27b60cd9a8150dea92be8ffc4cc4ac6a414d557f /doc/source | |
| parent | af9e94c64d3baa3f8b4fce957e2df0be8576a76e (diff) | |
| download | numpy-c87959a0095ff52f1fdfc6423f29c42be46cdf40.tar.gz | |
DOC: clarify doc about default int type on windows
Update documentation to clarify that integer arrays created
are of type int32 on windows platform. See #18540.
Diffstat (limited to 'doc/source')
| -rw-r--r-- | doc/source/user/basics.creation.rst | 3 |
1 files changed, 2 insertions, 1 deletions
diff --git a/doc/source/user/basics.creation.rst b/doc/source/user/basics.creation.rst index ccd6de184..f54ac5c71 100644 --- a/doc/source/user/basics.creation.rst +++ b/doc/source/user/basics.creation.rst @@ -76,7 +76,8 @@ the computation, here ``uint32`` and ``int32`` can both be represented in as ``int64``. The default NumPy behavior is to create arrays in either 64-bit signed -integers or double precision floating point numbers, ``int64`` and +integers (32-bit signed integers on Windows platform) or double precision +floating point numbers, ``int64`` (``int32`` on Windows platform) and ``float``, respectively. If you expect your arrays to be a certain type, then you need to specify the ``dtype`` while you create the array. |