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DOC: indexing/v0.15.0 docs
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doc/source/indexing.rst

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should be avoided. See :ref:`Returning a View versus Copy
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<indexing.view_versus_copy>`
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.. warning::
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In 0.15.0 ``Index`` has internaly been refactored to no longer sub-class ``ndarray``
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but instead subclass ``PandasObject``, similarly to the rest of the pandas objects. This should be
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a transparent change with only very limited API implications (See the :ref:`Internal Refactoring <whatsnew_0150.refactoring>`)
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See the :ref:`cookbook<cookbook.selection>` for some advanced strategies
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Different Choices for Indexing (``loc``, ``iloc``, and ``ix``)
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.. versionadded:: 0.15.0
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``set_names``, ``set_levels``, and ``set_labels`` also take an optional
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``set_names``, ``set_levels``, and ``set_labels`` also take an optional
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`level`` argument
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.. ipython:: python

doc/source/v0.15.0.txt

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- :ref:`Bug Fixes <whatsnew_0150.bug_fixes>`
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.. warning::
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In 0.15.0 ``Index`` has internaly been refactored to no longer sub-class ``ndarray``
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but instead subclass ``PandasObject``, similarly to the rest of the pandas objects. This change allows very easy sub-classing and creation of new index types. This should be
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a transparent change with only very limited API implications (See the :ref:`Internal Refactoring <whatsnew_0150.refactoring>`)
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.. _whatsnew_0150.api:
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API changes
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dta files with strings longer than 244 characters raises a ``ValueError``. (:issue:`7858`)
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.. _whatsnew_0150.refactoring:
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Internal Refactoring
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~~~~~~~~~~~~~~~~~~~~
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In 0.15.0 ``Index`` has internaly been refactored to no longer sub-class ``ndarray``
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but instead subclass ``PandasObject``, similarly to the rest of the pandas objects. This change allows very easy sub-classing and creation of new index types. This should be
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a transparent change with only very limited API implications (:issue:`5080`,:issue:`7439`,:issue:`7796`)
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- pickles <= 0.8.0 may not work if they contain MultiIndexes.
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- you may need to unpickle < 0.15.0 pickles using ``pd.read_pickle`` rather than ``pickle.load``. See :ref:`pickle docs <io.pickle>`
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- boolean comparisons of ``DatetimeIndex`` that have ``NaT`` with ``ndarray`` ONLY work if the ndarray is on the right-handle side. An example of this limited case is:
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.. ipython:: python
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idx = pd.DatetimeIndex(['2014-01-01', pd.NaT])
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arr = np.array([np.datetime64('2014-02-01 00:00Z'),np.datetime64('2014-02-01 00:00Z')])
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idx>arr
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idx<=arr
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arr<=idx
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arr>idx
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- ``:func:`~pandas.core.index.MultiIndex.repeat` now is available
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.. _whatsnew_0150.cat:
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Categoricals in Series/DataFrame

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