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nñúh&% ã óê d dl mZ d dlmZ d dlmZmZmZ d dlZ d dl
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d « Z e ej0 « G d d « « Z G d d« Zy)é )Ú annotations)ÚIterable)Ú TYPE_CHECKINGÚLiteralÚcastN)Úcache_readonlyÚdoc)Ú
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is_integerÚ is_list_like)ÚPositionalIndexer)Ú DataFrameÚSeries)Úgroupbyc óv e Zd ZdZed d« Z d dZd dZddZddZ ddZ
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)ÚGroupByIndexingMixinz<
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Mixin for adding ._positional_selector to GroupBy.
|
c ór t r%t t j | « }t |« S | }t |« S )aÌ
|
|
Return positional selection for each group.
|
|
``groupby._positional_selector[i:j]`` is similar to
|
``groupby.apply(lambda x: x.iloc[i:j])``
|
but much faster and preserves the original index and order.
|
|
``_positional_selector[]`` is compatible with and extends :meth:`~GroupBy.head`
|
and :meth:`~GroupBy.tail`. For example:
|
|
- ``head(5)``
|
- ``_positional_selector[5:-5]``
|
- ``tail(5)``
|
|
together return all the rows.
|
|
Allowed inputs for the index are:
|
|
- An integer valued iterable, e.g. ``range(2, 4)``.
|
- A comma separated list of integers and slices, e.g. ``5``, ``2, 4``, ``2:4``.
|
|
The output format is the same as :meth:`~GroupBy.head` and
|
:meth:`~GroupBy.tail`, namely
|
a subset of the ``DataFrame`` or ``Series`` with the index and order preserved.
|
|
Returns
|
-------
|
Series
|
The filtered subset of the original Series.
|
DataFrame
|
The filtered subset of the original DataFrame.
|
|
See Also
|
--------
|
DataFrame.iloc : Purely integer-location based indexing for selection by
|
position.
|
GroupBy.head : Return first n rows of each group.
|
GroupBy.tail : Return last n rows of each group.
|
GroupBy.nth : Take the nth row from each group if n is an int, or a
|
subset of rows, if n is a list of ints.
|
|
Notes
|
-----
|
- The slice step cannot be negative.
|
- If the index specification results in overlaps, the item is not duplicated.
|
- If the index specification changes the order of items, then
|
they are returned in their original order.
|
By contrast, ``DataFrame.iloc`` can change the row order.
|
- ``groupby()`` parameters such as as_index and dropna are ignored.
|
|
The differences between ``_positional_selector[]`` and :meth:`~GroupBy.nth`
|
with ``as_index=False`` are:
|
|
- Input to ``_positional_selector`` can include
|
one or more slices whereas ``nth``
|
just handles an integer or a list of integers.
|
- ``_positional_selector`` can accept a slice relative to the
|
last row of each group.
|
- ``_positional_selector`` does not have an equivalent to the
|
``nth()`` ``dropna`` parameter.
|
|
Examples
|
--------
|
>>> df = pd.DataFrame([["a", 1], ["a", 2], ["a", 3], ["b", 4], ["b", 5]],
|
... columns=["A", "B"])
|
>>> df.groupby("A")._positional_selector[1:2]
|
A B
|
1 a 2
|
4 b 5
|
|
>>> df.groupby("A")._positional_selector[1, -1]
|
A B
|
1 a 2
|
2 a 3
|
4 b 5
|
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ó&ó:8ó ó ó (ðT ò.ó ð.ð ò=ó ñ=r r c ó e Zd ZddZddZy)r c ó || _ y r ©Úgroupby_object©r rV s r Ú__init__z"GroupByPositionalSelector.__init__ú ó
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Ø ,Õr c ón | j j |« }| j j |« S )a
|
Select by positional index per group.
|
|
Implements GroupBy._positional_selector
|
|
Parameters
|
----------
|
arg : PositionalIndexer | tuple
|
Allowed values are:
|
- int
|
- int valued iterable such as list or range
|
- slice with step either None or positive
|
- tuple of integers and slices
|
|
Returns
|
-------
|
Series
|
The filtered subset of the original groupby Series.
|
DataFrame
|
The filtered subset of the original groupby DataFrame.
|
|
See Also
|
--------
|
DataFrame.iloc : Integer-location based indexing for selection by position.
|
GroupBy.head : Return first n rows of each group.
|
GroupBy.tail : Return last n rows of each group.
|
GroupBy._positional_selector : Return positional selection for each group.
|
GroupBy.nth : Take the nth row from each group if n is an int, or a
|
subset of rows, if n is a list of ints.
|
)rV r3 Ú_mask_selected_objr0 s r Ú __getitem__z%GroupByPositionalSelector.__getitem__ý s1 ð> ×"Ñ"×EÑEÀcÓJØ×"Ñ"×5Ñ5°dÓ;Ð;r N©rV zgroupby.GroupByrJ ÚNone)r1 rK rJ úDataFrame | Series)rN rO rP rX r\ rR r r r r ø s ó-ô <r r c ó6 e Zd ZdZddZ d ddZd dZy)
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Dynamically substituted for GroupBy.nth to enable both call and index
|
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