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DOC: whatsnew typos
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doc/source/whatsnew/v0.20.0.txt

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@@ -368,7 +368,6 @@ Other Enhancements
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- ``pandas.io.json.json_normalize()`` gained the option ``errors='ignore'|'raise'``; the default is ``errors='raise'`` which is backward compatible. (:issue:`14583`)
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- ``pandas.io.json.json_normalize()`` with an empty ``list`` will return an empty ``DataFrame`` (:issue:`15534`)
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- ``pandas.io.json.json_normalize()`` has gained a ``sep`` option that accepts ``str`` to separate joined fields; the default is ".", which is backward compatible. (:issue:`14883`)
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- A new function has been added to a ``MultiIndex`` to facilitate :ref:`Removing Unused Levels <advanced.shown_levels>`. (:issue:`15694`)
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- :func:`MultiIndex.remove_unused_levels` has been added to facilitate :ref:`removing unused levels <advanced.shown_levels>`. (:issue:`15694`)
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- ``pd.read_csv()`` will now raise a ``ParserError`` error whenever any parsing error occurs (:issue:`15913`, :issue:`15925`)
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- ``pd.read_csv()`` now supports the ``error_bad_lines`` and ``warn_bad_lines`` arguments for the Python parser (:issue:`15925`)
@@ -678,9 +677,9 @@ New Behavior:
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Pandas Google BigQuery support has moved
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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pandas has split off Google BigQuery support into a separate package ``pandas-gbq``. You can ``pip install pandas-gbq`` to get it.
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The functionality of :func:`read_gbq` and :meth:`DataFrame.to_gbq` remain the same with the currently released version of ``pandas-gbq=0.1.3``.
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Documentation is now hosted `here <https://pandas-gbq.readthedocs.io/>`__ (:issue:`15347`)
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pandas has split off Google BigQuery support into a separate package ``pandas-gbq``. You can ``conda install pandas-gbq -c conda-forge`` or
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``pip install pandas-gbq`` to get it. The functionality of :func:`read_gbq` and :meth:`DataFrame.to_gbq` remain the same with the
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currently released version of ``pandas-gbq=0.1.4``. Documentation is now hosted `here <https://pandas-gbq.readthedocs.io/>`__ (:issue:`15347`)
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.. _whatsnew_0200.api_breaking.memory_usage:
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@@ -782,14 +781,16 @@ However, this example, which has a non-monotonic 2nd level,
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doesn't behave as desired.
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.. ipython:: python
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df = pd.DataFrame(
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{'value': [1, 2, 3, 4]},
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index=pd.MultiIndex(levels=[['a', 'b'], ['bb', 'aa']],
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labels=[[0, 0, 1, 1], [0, 1, 0, 1]]))
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df
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Previous Behavior:
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.. ipython:: python
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.. code-block:: python
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In [11]: df.sort_index()
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Out[11]:

pandas/indexes/multi.py

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@@ -1260,8 +1260,9 @@ def remove_unused_levels(self):
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MultiIndex(levels=[[0, 1], ['a', 'b']],
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labels=[[1, 1], [0, 1]])
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# the 0 from the first level is not represented
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# and can be removed
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The 0 from the first level is not represented
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and can be removed
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>>> i[2:].remove_unused_levels()
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MultiIndex(levels=[[1], ['a', 'b']],
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labels=[[0, 0], [0, 1]])

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