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DOC: fix some doc build errors/warnings
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doc/source/install.rst

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@@ -267,11 +267,11 @@ Optional Dependencies
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installation.
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* Google's `python-gflags <http://code.google.com/p/python-gflags/>`__
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and `google-api-python-client <http://github.com/google/google-api-python-client>`__
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* Needed for :mod:`~pandas.io.gbq`
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* Needed for :mod:`~pandas.io.gbq`
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* `setuptools <https://pypi.python.org/pypi/setuptools/>`__
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* Needed for :mod:`~pandas.io.gbq` (specifically, it utilizes `pkg_resources`)
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* Needed for :mod:`~pandas.io.gbq` (specifically, it utilizes `pkg_resources`)
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* `httplib2 <http://pypi.python.org/pypi/httplib2>`__
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* Needed for :mod:`~pandas.io.gbq`
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* Needed for :mod:`~pandas.io.gbq`
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* One of the following combinations of libraries is needed to use the
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top-level :func:`~pandas.io.html.read_html` function:
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doc/source/io.rst

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@@ -3610,7 +3610,7 @@ below and the SQLAlchemy `documentation <http://docs.sqlalchemy.org/en/rel_0_9/c
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If you want to manage your own connections you can pass one of those instead:
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.. ipython:: python
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.. code-block:: python
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with engine.connect() as conn, conn.begin():
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data = pd.read_sql_table('data', conn)

doc/source/visualization.rst

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@@ -1649,6 +1649,7 @@ values, the resulting grid has two columns and two rows. A histogram is
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displayed for each cell of the grid.
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.. ipython:: python
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:okwarning:
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plt.figure()
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@@ -1680,6 +1681,7 @@ Example below is the same as previous except the plot is set to kernel density
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estimation. A ``seaborn`` example is included beneath.
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.. ipython:: python
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:okwarning:
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plt.figure()
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@@ -1706,6 +1708,7 @@ The plot below shows that it is possible to have two or more plots for the same
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data displayed on the same Trellis grid cell.
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.. ipython:: python
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:okwarning:
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plt.figure()
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@@ -1745,6 +1748,7 @@ Below is a similar plot but with 2D kernel density estimation plot superimposed,
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followed by a ``seaborn`` equivalent:
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.. ipython:: python
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:okwarning:
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plt.figure()
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the plots will be arranged in a column.
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.. ipython:: python
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:okwarning:
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plt.figure()
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@@ -1792,6 +1797,7 @@ the plots will be arranged in a column.
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If the first grouping attribute is not specified the plots will be arranged in a row.
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.. ipython:: python
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:okwarning:
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plt.figure()
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@@ -1816,6 +1822,7 @@ scale objects to specify these mappings. The list of scale classes is
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given below with initialization arguments for quick reference.
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.. ipython:: python
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:okwarning:
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plt.figure()
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doc/source/whatsnew/v0.17.0.txt

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@@ -13,13 +13,13 @@ users upgrade to this version.
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Highlights include:
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- Release the Global Interpreter Lock (GIL) on some cython operations, see :ref:`here <whatsnew_0170.gil>`
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- The default for ``to_datetime`` will now be to ``raise`` when presented with unparseable formats,
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previously this would return the original input, see :ref:`here <whatsnew_0170.api_breaking.to_datetime>`
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- The default for ``dropna`` in ``HDFStore`` has changed to ``False``, to store by default all rows even
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if they are all ``NaN``, see :ref:`here <whatsnew_0170.api_breaking.hdf_dropna>`
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- Support for ``Series.dt.strftime`` to generate formatted strings for datetime-likes, see :ref:`here <whatsnew_0170.strftime>`
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- Development installed versions of pandas will now have ``PEP440`` compliant version strings (:issue:`9518`)
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- Release the Global Interpreter Lock (GIL) on some cython operations, see :ref:`here <whatsnew_0170.gil>`
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- The default for ``to_datetime`` will now be to ``raise`` when presented with unparseable formats,
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previously this would return the original input, see :ref:`here <whatsnew_0170.api_breaking.to_datetime>`
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- The default for ``dropna`` in ``HDFStore`` has changed to ``False``, to store by default all rows even
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if they are all ``NaN``, see :ref:`here <whatsnew_0170.api_breaking.hdf_dropna>`
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- Support for ``Series.dt.strftime`` to generate formatted strings for datetime-likes, see :ref:`here <whatsnew_0170.strftime>`
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- Development installed versions of pandas will now have ``PEP440`` compliant version strings (:issue:`9518`)
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Check the :ref:`API Changes <whatsnew_0170.api>` and :ref:`deprecations <whatsnew_0170.deprecations>` before updating.
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@@ -448,6 +448,7 @@ from ``7``.
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.. ipython:: python
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:suppress:
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pd.set_option('display.precision', 6)
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@@ -481,9 +482,9 @@ Series with a ``CategoricalIndex`` (:issue:`10704`)
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- ``groupby`` using ``Categorical`` follows the same rule as ``Categorical.unique`` described above (:issue:`10508`)
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- ``NaT``'s methods now either raise ``ValueError``, or return ``np.nan`` or ``NaT`` (:issue:`9513`)
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=============================== ==============================================================
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=============================== ===============================================================
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Behavior Methods
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=============================== ===============================================================
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``return np.nan`` ``weekday``, ``isoweekday``
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``return NaT`` ``date``, ``now``, ``replace``, ``to_datetime``, ``today``
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``return np.datetime64('NaT')`` ``to_datetime64`` (unchanged)

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