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-rw-r--r--doc/source/reference/arrays.scalars.rst8
1 files changed, 4 insertions, 4 deletions
diff --git a/doc/source/reference/arrays.scalars.rst b/doc/source/reference/arrays.scalars.rst
index 75daf2a08..62e22146a 100644
--- a/doc/source/reference/arrays.scalars.rst
+++ b/doc/source/reference/arrays.scalars.rst
@@ -41,7 +41,7 @@ of the flexible itemsize array types (:class:`string`,
pointer for the platform. All the number types can be obtained
using bit-width names as well.
-.. [#] However, array scalars are immutable, so that none of the array
+.. [#] However, array scalars are immutable, so none of the array
scalar attributes are settable.
.. _arrays.scalars.character-codes:
@@ -91,7 +91,7 @@ Python Boolean scalar.
.. tip:: The default data type in Numpy is :class:`float_`.
-In the tables below, ``platform?`` means that the type may not
+In the tables below, ``platform?`` means that the type may not be
available on all platforms. Compatibility with different C or Python
types is indicated: two types are compatible if their data is of the
same size and interpreted in the same way.
@@ -144,7 +144,7 @@ Floating-point numbers:
:class:`longfloat` compatible: C long float ``'g'``
:class:`float32` 32 bits
:class:`float64` 64 bits
-:class:`float96` 92 bits, platform?
+:class:`float96` 96 bits, platform?
:class:`float128` 128 bits, platform?
=================== ============================= ===============
@@ -171,7 +171,7 @@ Any Python object:
.. note::
The data actually stored in :term:`object arrays <object array>`
- (*i.e.* arrays having dtype :class:`object_`) are references to
+ (*i.e.*, arrays having dtype :class:`object_`) are references to
Python objects, not the objects themselves. Hence, object arrays
behave more like usual Python :class:`lists <list>`, in the sense
that their contents need not be of the same Python type.