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Oct 8, 2020
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DOC: Distinguish between different types of boolean indexing #10492 #36869

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DOC: Distinguish between different types of boolean indexing #10492
junjunjunk Oct 4, 2020
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DOC: change styles of document addition.
junjunjunk Oct 5, 2020
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Merge remote-tracking branch 'upstream/master' into is10492
Oct 5, 2020
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DOC: remove unnecessary whitespace.
junjunjunk Oct 5, 2020
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DOC: change style of the example
junjunjunk Oct 6, 2020
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Merge remote-tracking branch 'upstream/master' into is10492
Oct 6, 2020
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DOC: remove unnecessary whitespace.
junjunjunk Oct 6, 2020
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DOC: change styles of document addition & fix variable name.
junjunjunk Oct 6, 2020
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Merge remote-tracking branch 'upstream/master' into is10492
Oct 6, 2020
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18 changes: 18 additions & 0 deletions doc/source/user_guide/indexing.rst
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Expand Up @@ -933,6 +933,24 @@ and :ref:`Advanced Indexing <advanced>` you may select along more than one axis

df2.loc[criterion & (df2['b'] == 'x'), 'b':'c']

.. warning::

``iloc`` supports two kinds of boolean indexing. If the indexer is a boolean ``Series``,
an error will be raised. For instance, in the following example, ``df.iloc[sr.values, 1]`` is ok.
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sr -> s

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Thanks for the quick review! I forgot to fix the doc. Done.

This type of boolean indexing is array. But ``df.iloc[sr, 1]`` would raise ``ValueError``.
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"is array" -> "is using an array". Alternatively, "The boolean indexer is an array."
sr -> s

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Done.


.. ipython:: python

df = pd.DataFrame([[1, 2], [3, 4], [5, 6]],
index=list('abc'),
columns=['A', 'B'])
s = (df['A'] > 2)
s

df.loc[s, 'B']

df.iloc[s.values, 1]

.. _indexing.basics.indexing_isin:

Indexing with isin
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