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authorAmrit K <amrit110@gmail.com>2021-11-15 19:23:34 -0500
committerAmrit K <amrit110@gmail.com>2021-11-15 19:23:34 -0500
commit76e6409d2d7cbcc88a804560cfb765f365531858 (patch)
tree800e75270a0eefb3d14990ae707ec0754736977f
parentc87959a0095ff52f1fdfc6423f29c42be46cdf40 (diff)
downloadnumpy-76e6409d2d7cbcc88a804560cfb765f365531858.tar.gz
Update doc with better wording
-rw-r--r--doc/source/user/basics.creation.rst9
1 files changed, 4 insertions, 5 deletions
diff --git a/doc/source/user/basics.creation.rst b/doc/source/user/basics.creation.rst
index f54ac5c71..a02cc8889 100644
--- a/doc/source/user/basics.creation.rst
+++ b/doc/source/user/basics.creation.rst
@@ -75,11 +75,10 @@ assign a new type that satisfies all of the array elements involved in
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 (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.
+The default NumPy behavior is to create arrays in either 32 or 64-bit signed
+integers (platform dependent) or double precision floating point numbers,
+int32/int64 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.
2) Intrinsic NumPy array creation functions
===========================================