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DOC: fix some sphinx syntax warnings (#19962)
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doc/source/merging.rst

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@@ -152,7 +152,7 @@ functionality below.
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Set logic on the other axes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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When gluing together multiple ``DataFrame``s, you have a choice of how to handle
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When gluing together multiple DataFrames, you have a choice of how to handle
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the other axes (other than the one being concatenated). This can be done in
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the following three ways:
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@@ -636,7 +636,7 @@ key combination:
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Here is a more complicated example with multiple join keys. Only the keys
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appearing in ``left`` and ``right`` are present (the intersection), since
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``how='inner'```by default.
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``how='inner'`` by default.
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.. ipython:: python
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@@ -721,7 +721,7 @@ either the left or right tables, the values in the joined table will be
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labels=['left', 'right'], vertical=False);
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plt.close('all');
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Here is another example with duplicate join keys in ``DataFrame``s:
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Here is another example with duplicate join keys in DataFrames:
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.. ipython:: python
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doc/source/tutorials.rst

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@@ -180,13 +180,13 @@ Video Tutorials
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- `Pandas From The Ground Up <https://www.youtube.com/watch?v=5JnMutdy6Fw>`_
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(2015) (2:24)
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`GitHub repo <https://github.com/brandon-rhodes/pycon-pandas-tutorial>`_
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`GitHub repo <https://github.com/brandon-rhodes/pycon-pandas-tutorial>`__
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- `Introduction Into Pandas <https://www.youtube.com/watch?v=-NR-ynQg0YM>`_
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(2016) (1:28)
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`GitHub repo <https://github.com/chendaniely/2016-pydata-carolinas-pandas>`_
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`GitHub repo <https://github.com/chendaniely/2016-pydata-carolinas-pandas>`__
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- `Pandas: .head() to .tail() <https://www.youtube.com/watch?v=7vuO9QXDN50>`_
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(2016) (1:26)
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`GitHub repo <https://github.com/TomAugspurger/pydata-chi-h2t>`_
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`GitHub repo <https://github.com/TomAugspurger/pydata-chi-h2t>`__
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Various Tutorials

doc/source/visualization.rst

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@@ -870,7 +870,7 @@ Andrews Curves
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Andrews curves allow one to plot multivariate data as a large number
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of curves that are created using the attributes of samples as coefficients
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for Fourier series, see the `Wikipedia entry<https://en.wikipedia.org/wiki/Andrews_plot>`_
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for Fourier series, see the `Wikipedia entry <https://en.wikipedia.org/wiki/Andrews_plot>`__
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for more information. By coloring these curves differently for each class
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it is possible to visualize data clustering. Curves belonging to samples
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of the same class will usually be closer together and form larger structures.
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~~~~~~~~~~~~~~~~~~~~
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Parallel coordinates is a plotting technique for plotting multivariate data,
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see the `Wikipedia entry<https://en.wikipedia.org/wiki/Parallel_coordinates>`_
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see the `Wikipedia entry <https://en.wikipedia.org/wiki/Parallel_coordinates>`__
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for an introduction.
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Parallel coordinates allows one to see clusters in data and to estimate other statistics visually.
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Using parallel coordinates points are represented as connected line segments.
@@ -962,7 +962,7 @@ all time-lag separations. If time series is non-random then one or more of the
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autocorrelations will be significantly non-zero. The horizontal lines displayed
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in the plot correspond to 95% and 99% confidence bands. The dashed line is 99%
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confidence band. See the
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`Wikipedia entry<https://en.wikipedia.org/wiki/Correlogram>`_ for more about
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`Wikipedia entry <https://en.wikipedia.org/wiki/Correlogram>`__ for more about
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autocorrelation plots.
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.. ipython:: python
@@ -1032,7 +1032,7 @@ unit interval). The point in the plane, where our sample settles to (where the
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forces acting on our sample are at an equilibrium) is where a dot representing
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our sample will be drawn. Depending on which class that sample belongs it will
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be colored differently.
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See the R package `Radviz<https://cran.r-project.org/web/packages/Radviz/>`_
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See the R package `Radviz <https://cran.r-project.org/web/packages/Radviz/>`__
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for more information.
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**Note**: The "Iris" dataset is available `here <https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/iris.csv>`__.

doc/source/whatsnew/v0.23.0.txt

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@@ -117,7 +117,7 @@ resetting indexes. See the :ref:`Sorting by Indexes and Values
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# Sort by 'second' (index) and 'A' (column)
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df_multi.sort_values(by=['second', 'A'])
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.. _whatsnew_0230.enhancements.timedelta_mod
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.. _whatsnew_0230.enhancements.timedelta_mod:
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Timedelta mod method
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^^^^^^^^^^^^^^^^^^^^
@@ -756,7 +756,7 @@ Removal of prior version deprecations/changes
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- The ``Panel4D`` and ``PanelND`` classes have been removed (:issue:`13776`)
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- The ``Panel`` class has dropped the ``to_long`` and ``toLong`` methods (:issue:`19077`)
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- The options ``display.line_with`` and ``display.height`` are removed in favor of ``display.width`` and ``display.max_rows`` respectively (:issue:`4391`, :issue:`19107`)
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- The ``labels`` attribute of the ``Categorical`` class has been removed in favor of :attribute:`Categorical.codes` (:issue:`7768`)
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- The ``labels`` attribute of the ``Categorical`` class has been removed in favor of :attr:`Categorical.codes` (:issue:`7768`)
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- The ``flavor`` parameter have been removed from func:`to_sql` method (:issue:`13611`)
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- The modules ``pandas.tools.hashing`` and ``pandas.util.hashing`` have been removed (:issue:`16223`)
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- The top-level functions ``pd.rolling_*``, ``pd.expanding_*`` and ``pd.ewm*`` have been removed (Deprecated since v0.18).

pandas/core/frame.py

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@@ -116,8 +116,8 @@
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- if `axis` is 1 or `'columns'` then `by` may contain column
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levels and/or index labels
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.. versionchanged:: 0.23.0
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Allow specifying index or column level names.""",
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.. versionchanged:: 0.23.0
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Allow specifying index or column level names.""",
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versionadded_to_excel='',
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optional_labels="""labels : array-like, optional
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New labels / index to conform the axis specified by 'axis' to.""",

pandas/core/window.py

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@@ -416,11 +416,11 @@ class Window(_Window):
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A ragged (meaning not-a-regular frequency), time-indexed DataFrame
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>>> df = pd.DataFrame({'B': [0, 1, 2, np.nan, 4]},
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....: index = [pd.Timestamp('20130101 09:00:00'),
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....: pd.Timestamp('20130101 09:00:02'),
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....: pd.Timestamp('20130101 09:00:03'),
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....: pd.Timestamp('20130101 09:00:05'),
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....: pd.Timestamp('20130101 09:00:06')])
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... index = [pd.Timestamp('20130101 09:00:00'),
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... pd.Timestamp('20130101 09:00:02'),
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... pd.Timestamp('20130101 09:00:03'),
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... pd.Timestamp('20130101 09:00:05'),
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... pd.Timestamp('20130101 09:00:06')])
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>>> df
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B

pandas/io/json/json.py

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@@ -348,7 +348,7 @@ def read_json(path_or_buf=None, orient=None, typ='frame', dtype=True,
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to denote a missing :class:`Index` name, and the subsequent
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:func:`read_json` operation cannot distinguish between the two. The same
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limitation is encountered with a :class:`MultiIndex` and any names
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beginning with 'level_'.
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beginning with ``'level_'``.
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See Also
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--------

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