jorisvandenbossche commented on a change in pull request #1:
URL: https://github.com/apache/arrow-cookbook/pull/1#discussion_r686021413
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File path: python/source/create.rst
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+======================
+Creating Arrow Objects
+======================
+
+Recipes related to the creation of Arrays, Tables,
+Tensors and all other Arrow entities.
+
+.. contents::
+
+Create Table from Plain Types
+=============================
+
+Arrow allows fast zero copy creation of arrow arrays
+from numpy and pandas arrays and series, but it's also
+possible to create Arrow Arrays and Tables from
+plain Python structures.
+
+the :func:`pyarrow.table` function allows creation of Tables
+from a variety of inputs, including plain python objects
+
+.. testcode::
+
+ import pyarrow as pa
+
+ table = pa.table({
+ "col1": [1, 2, 3, 4, 5],
+ "col2": ["a", "b", "c", "d", "e"]
+ })
+
+ print(table)
+
+.. testoutput::
+
+ pyarrow.Table
+ col1: int64
+ col2: string
+
+.. note::
+
+ All values provided in the dictionary will be passed to
+ :func:`pyarrow.array` for conversion to Arrow arrays,
+ and will benefit from zero copy behaviour when possible.
+
+Store Categorical Data
+======================
+
+Arrow provides the :class:`pyarrow.DictionaryArray` type
+to represent categorical data without the cost of
+storing and repeating the categories over and over. This can reduce memory use
+when columns might have large values (such as text).
+
+If you have an array containing repeated categorical data,
+it is possible to convert it to a :class:`pyarrow.DictionaryArray`
+using :meth:`pyarrow.Array.dictionary_encode`
+
+.. testcode::
+
+ arr = pa.array(["red", "green", "blue", "blue", "green", "red"])
+
+ categorical = arr.dictionary_encode()
+ print(categorical)
+
+.. testoutput::
+
+ ...
+ -- dictionary:
+ [
+ "red",
+ "green",
+ "blue"
+ ]
+ -- indices:
+ [
+ 0,
+ 1,
+ 2,
+ 2,
+ 1,
+ 0
+ ]
+
+If you already know the categories and indices then you can skip the encode
+step and directly create the ``DictionaryArray`` using
+:meth:`pyarrow.DictionaryArray.from_arrays`
Review comment:
Might also be worth mentioning that pyarrow also supports creating a
DictionaryArray directly from a pandas.Categorical, in case you would have that
already.
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