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DOC: NumericIndex #42706

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b34da22
DOC: NumericIndex
topper-123 Jul 25, 2021
fc8a75e
Make NumericIndex public
topper-123 Aug 6, 2021
15870f5
fix doc example
topper-123 Aug 6, 2021
a9965b0
clean-ups
topper-123 Aug 6, 2021
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@topper-123
topper-123 committed Aug 6, 2021
commit a9965b0fae9d2e13ee37c3b8325a38ae7fab56c7
24 changes: 12 additions & 12 deletions doc/source/user_guide/advanced.rst
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Expand Up @@ -7,7 +7,7 @@ MultiIndex / advanced indexing
******************************

This section covers :ref:`indexing with a MultiIndex <advanced.hierarchical>`
and :ref:`other advanced indexing features <indexing.index_types>`.
and :ref:`other advanced indexing features <advanced.index_types>`.

See the :ref:`Indexing and Selecting Data <indexing>` for general indexing documentation.

Expand Down Expand Up @@ -738,7 +738,7 @@ faster than fancy indexing.
%timeit ser.iloc[indexer]
%timeit ser.take(indexer)

.. _indexing.index_types:
.. _advanced.index_types:

Index types
-----------
Expand All @@ -749,7 +749,7 @@ and documentation about ``TimedeltaIndex`` is found :ref:`here <timedeltas.index

In the following sub-sections we will highlight some other index types.

.. _indexing.categoricalindex:
.. _advanced.categoricalindex:

CategoricalIndex
~~~~~~~~~~~~~~~~
Expand Down Expand Up @@ -846,7 +846,7 @@ values **not** in the categories, similarly to how you can reindex **any** panda
In [1]: pd.concat([df4, df5])
TypeError: categories must match existing categories when appending

.. _indexing.rangeindex:
.. _advanced.rangeindex:

Int64Index and RangeIndex
~~~~~~~~~~~~~~~~~~~~~~~~~
Expand All @@ -855,7 +855,7 @@ Int64Index and RangeIndex

In pandas 2.0, :class:`NumericIndex` will become the default index type for numeric types
instead of ``Int64Index``, ``Float64Index`` and ``UInt64Index`` and those index types
will be removed. See :ref:`here <indexing.numericindex>` for more.
will be removed. See :ref:`here <advanced.numericindex>` for more.
``RangeIndex`` however, will not be removed, as it represents an optimized version of an integer index.

:class:`Int64Index` is a fundamental basic index in pandas. This is an immutable array
Expand All @@ -864,7 +864,7 @@ implementing an ordered, sliceable set.
:class:`RangeIndex` is a sub-class of ``Int64Index`` that provides the default index for all ``NDFrame`` objects.
``RangeIndex`` is an optimized version of ``Int64Index`` that can represent a monotonic ordered set. These are analogous to Python `range types <https://docs.python.org/3/library/stdtypes.html#typesseq-range>`__.

.. _indexing.float64index:
.. _advanced.float64index:

Float64Index
~~~~~~~~~~~~
Expand All @@ -873,7 +873,7 @@ Float64Index

In pandas 2.0, :class:`NumericIndex` will become the default index type for numeric types
instead of ``Int64Index``, ``Float64Index`` and ``UInt64Index`` and those index types
will be removed. See :ref:`here <indexing.numericindex>` for more.
will be removed. See :ref:`here <advanced.numericindex>` for more.
``RangeIndex`` however, will not be removed, as it represents an optimized version of an integer index.

By default a :class:`Float64Index` will be automatically created when passing floating, or mixed-integer-floating values in index creation.
Expand Down Expand Up @@ -971,7 +971,7 @@ If you need integer based selection, you should use ``iloc``:
dfir.iloc[0:5]


.. _indexing.numericindex:
.. _advanced.numericindex:

NumericIndex
~~~~~~~~~~~~
Expand All @@ -982,16 +982,16 @@ NumericIndex

In pandas 2.0, :class:`NumericIndex` will become the default index type for numeric types
instead of ``Int64Index``, ``Float64Index`` and ``UInt64Index`` and those index types
will be removed. See :ref:`here <indexing.numericindex>` for more.
will be removed.
``RangeIndex`` however, will not be removed, as it represents an optimized version of an integer index.

:class:`NumericIndex` is an index type that can hold data of any numpy int/uint/float dtype. For example:

.. ipython:: python

index = pd.NumericIndex([1, 2, 4, 5], dtype="int8")
index
ser = pd.Series(range(4), index=index)
idx = pd.NumericIndex([1, 2, 4, 5], dtype="int8")
idx
ser = pd.Series(range(4), index=idx)
ser

``NumericIndex`` works the same way as the existing ``Int64Index``, ``Float64Index`` and
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2 changes: 1 addition & 1 deletion doc/source/user_guide/categorical.rst
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Expand Up @@ -1141,7 +1141,7 @@ Categorical index
``CategoricalIndex`` is a type of index that is useful for supporting
indexing with duplicates. This is a container around a ``Categorical``
and allows efficient indexing and storage of an index with a large number of duplicated elements.
See the :ref:`advanced indexing docs <indexing.categoricalindex>` for a more detailed
See the :ref:`advanced indexing docs <advanced.categoricalindex>` for a more detailed
explanation.

Setting the index will create a ``CategoricalIndex``:
Expand Down
2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.13.0.rst
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Expand Up @@ -310,7 +310,7 @@ Float64Index API change

- Added a new index type, ``Float64Index``. This will be automatically created when passing floating values in index creation.
This enables a pure label-based slicing paradigm that makes ``[],ix,loc`` for scalar indexing and slicing work exactly the
same. See :ref:`the docs<indexing.float64index>`, (:issue:`263`)
same. See :ref:`the docs<advanced.float64index>`, (:issue:`263`)

Construction is by default for floating type values.

Expand Down
2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.16.1.rst
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Expand Up @@ -168,7 +168,7 @@ values NOT in the categories, similarly to how you can reindex ANY pandas index.
ordered=False, name='B',
dtype='category')
See the :ref:`documentation <indexing.categoricalindex>` for more. (:issue:`7629`, :issue:`10038`, :issue:`10039`)
See the :ref:`documentation <advanced.categoricalindex>` for more. (:issue:`7629`, :issue:`10038`, :issue:`10039`)

.. _whatsnew_0161.enhancements.sample:

Expand Down
20 changes: 10 additions & 10 deletions doc/source/whatsnew/v1.4.0.rst
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Expand Up @@ -20,9 +20,8 @@ Enhancements
More flexible numeric dtypes for indexes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Until now, it has only been possible to create numeric indexes with int64/float64/uint64 dtypes,
but not with lower bit sizes (int32, int8, uint32, uint8 etc). It is now possible to create
an index of any numpy dtype using the new :class:`NumericIndex` (:issue:`41153`):
Until now, it has only been possible to create numeric indexes with int64/float64/uint64 dtypes.
It is now possible to create an index of any numpy int/uint/float dtype using the new :class:`NumericIndex` index type (:issue:`41153`):

.. ipython:: python

Expand All @@ -32,7 +31,7 @@ an index of any numpy dtype using the new :class:`NumericIndex` (:issue:`41153`)

In order to maintain backwards compatibility, calls to the base :class:`Index` will in
pandas 1.x. return :class:`Int64Index`, :class:`UInt64Index` and :class:`Float64Index`.
For example, notice that the code below returns an ``Int64Index`` with dtype ``int64``:
For example, the code below returns an ``Int64Index`` with dtype ``int64``:

.. code-block:: ipython

Expand All @@ -42,7 +41,8 @@ For example, notice that the code below returns an ``Int64Index`` with dtype ``i
For the duration of Pandas 1.x, in order to maintain backwards compatibility, all
operations that until now have returned :class:`Int64Index`, :class:`UInt64Index` and
:class:`Float64Index` will continue to so. This means, that in order to use
``NumericIndex``, you will have to call it explicitly. For example:
``NumericIndex``, you will have to call ``NumericIndex`` explicitly. For example the below series
will have an ``Int64Index``:

.. code-block:: ipython

Expand All @@ -52,16 +52,16 @@ operations that until now have returned :class:`Int64Index`, :class:`UInt64Index

Instead if you want to use a ``NumericIndex``, you should do:

.. code-block:: ipython
.. ipython:: python

In [2]: ser = pd.Series([1, 2, 3], index=pd.NumericIndex([1, 2, 3], dtype="int8"))
In [3]: ser.index
NumericIndex([1, 2, 3], dtype='int8')
idx = pd.NumericIndex([1, 2, 3], dtype="int8")
ser = pd.Series([1, 2, 3], index=idx)
ser.index

In Pandas 2.0, :class:`NumericIndex` will become the default numeric index type and
``Int64Index``, ``UInt64Index`` and ``Float64Index`` will be removed.

See :ref:`here <indexing.numericindex>` for more.
See :ref:`here <advanced.numericindex>` for more.

.. _whatsnew_140.enhancements.enhancement2:

Expand Down