amol- commented on a change in pull request #63:
URL: https://github.com/apache/arrow-cookbook/pull/63#discussion_r701711836
##########
File path: python/source/create.rst
##########
@@ -7,6 +7,68 @@ Tensors and all other Arrow entities.
.. contents::
+Creating Arrays
+===============
+
+Arrow keeps data in continuous arrays optimised for memory footprint
+and SIMD analyses. In Python it's possible to build :class:`pyarrow.Array`
+starting from Python ``lists`` (or sequence types in general),
+``numpy`` arrays and ``pandas`` Series.
+
+.. testcode::
+
+ import pyarrow as pa
+
+ array = pa.array([1, 2, 3, 4, 5])
+
+.. testcode::
+
+ print(array)
+
+.. testoutput::
+
+ [
+ 1,
+ 2,
+ 3,
+ 4,
+ 5
+ ]
+
+Arrays can also provide a ``mask`` to specify which values should
Review comment:
It's something I struggled a bit with, I wasn't sure if I should have
explicitly mentioned that or not. Mostly for the reason that I would like to
expand that to support ``pyarrow.Array`` too as masks (
https://issues.apache.org/jira/browse/ARROW-13883 ). So in the end I thought
about not mentioning the constraint so that we don't leave behind a wrong
information when the constraint is lightened
##########
File path: python/source/create.rst
##########
@@ -7,6 +7,68 @@ Tensors and all other Arrow entities.
.. contents::
+Creating Arrays
+===============
+
+Arrow keeps data in continuous arrays optimised for memory footprint
+and SIMD analyses. In Python it's possible to build :class:`pyarrow.Array`
+starting from Python ``lists`` (or sequence types in general),
+``numpy`` arrays and ``pandas`` Series.
+
+.. testcode::
+
+ import pyarrow as pa
+
+ array = pa.array([1, 2, 3, 4, 5])
+
+.. testcode::
+
+ print(array)
+
+.. testoutput::
+
+ [
+ 1,
+ 2,
+ 3,
+ 4,
+ 5
+ ]
+
+Arrays can also provide a ``mask`` to specify which values should
+be considered nulls
+
+.. testcode::
+
+ import numpy as np
+
+ array = pa.array([1, 2, 3, 4, 5],
+ mask=np.array([True, False, True, False, True]))
+
+ print(array)
+
+.. testoutput::
+
+ [
+ null,
+ 2,
+ null,
+ 4,
+ null
+ ]
+
+When building arrays from ``numpy`` or ``pandas``, Arrow will leverage
+optimized code paths that rely on the internal in-memory representation
+of the data by ``numpy`` and ``pandas``
+
+.. testcode::
+
+ import numpy as np
+ import pandas
Review comment:
:+1:
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