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DOC: Distinguish between different types of boolean indexing #10492 #36869

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Merged
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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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14 changes: 14 additions & 0 deletions doc/source/user_guide/indexing.rst
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Expand Up @@ -933,6 +933,20 @@ and :ref:`Advanced Indexing <advanced>` you may select along more than one axis

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

``iloc`` distinguishes between different types of boolean indexing. If the type of boolean indexing is ``Series``,
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iloc supports two kinds of boolean indexing.

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If the indexer is a boolean Series, ...

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Done.

an error will be raised. For instance, in the following example, ``df.iloc[sr.values, 1]`` is ok.
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what type of error?

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I see below it's a ValueError, just say that here

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Also you need two backticks around ValueError

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Done.

This type of boolean indexing is array. But ``df.iloc[sr, 1]`` would raise ValueError.

.. ipython:: python

df = pd.DataFrame([[1, 2], [3, 4], [5, 6]], list('abc'), ['column_1', 'column_2'])
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make the column names 'A', 'B' (to make this look a bit cleaner)

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Done.

sr = (df['column_1'] > 2)
sr

df.loc[sr, df.columns[1]]

df.iloc[sr.values, 1]

.. _indexing.basics.indexing_isin:

Indexing with isin
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