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DOC: warning section on memory overflow when joining/merging dataframes on index with duplicate keys #14788

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Merged
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Dec 11, 2016
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DOC: warning section on memory overflow when joining/merging dataframes on index with duplicate keys #14788

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93a63a5
add doc regarding #14736
xgdgsc Dec 2, 2016
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remove blank line
xgdgsc Dec 2, 2016
06d4430
change index to keys , fix spaces and format
xgdgsc Dec 3, 2016
fb021fb
fix format
xgdgsc Dec 3, 2016
403b099
add example , change warning position
xgdgsc Dec 11, 2016
ee9fc60
fix format
xgdgsc Dec 11, 2016
7581ce0
change fig name, change sentence
xgdgsc Dec 11, 2016
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xgdgsc Dec 11, 2016
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23 changes: 23 additions & 0 deletions doc/source/merging.rst
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Expand Up @@ -692,6 +692,29 @@ either the left or right tables, the values in the joined table will be
p.plot([left, right], result,
labels=['left', 'right'], vertical=False);
plt.close('all');

Here is another example with duplicate join keys in DataFrames:

.. ipython:: python

left = pd.DataFrame({'A' : [1,2], 'B' : [2, 2]})

right = pd.DataFrame({'A' : [4,5,6], 'B': [2,2,2]})

result = pd.merge(left, right, on='B', how='outer')

.. ipython:: python
:suppress:

@savefig merging_merge_on_key_dup.png
p.plot([left, right], result,
labels=['left', 'right'], vertical=False);
plt.close('all');

.. warning::

Joining / merging on duplicate keys can cause a returned frame that is the multiplication of the row dimensions,
may result in memory overflow. It is the user' s responsibility to manage duplicate values in keys before joining large DataFrames.

.. _merging.indicator:

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