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DOC: remove rplot seaborn equivalent example figures (pandas-dev#13954)
* DOC: remove rplot seaborn equivalent examples (removed from docs in pandas-dev#13855) * DOC: fix some doc build errors
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doc/source/dsintro.rst

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@@ -943,7 +943,7 @@ Panel4D (Experimental)
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.. warning::
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In 0.19.0 ``Panel4D` is deprecated and will be removed in a future version. The recommended way to represent these types of n-dimensional data are with the `xarray package <http://xarray.pydata.org/en/stable/>`__. Pandas provides a :meth:`~Panel4D.to_xarray` method to automate this conversion.
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In 0.19.0 ``Panel4D`` is deprecated and will be removed in a future version. The recommended way to represent these types of n-dimensional data are with the `xarray package <http://xarray.pydata.org/en/stable/>`__. Pandas provides a :meth:`~Panel4D.to_xarray` method to automate this conversion.
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``Panel4D`` is a 4-Dimensional named container very much like a ``Panel``, but
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having 4 named dimensions. It is intended as a test bed for more N-Dimensional named
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.. warning::
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In 0.19.0 ``PanelND` is deprecated and will be removed in a future version. The recommended way to represent these types of n-dimensional data are with the `xarray package <http://xarray.pydata.org/en/stable/>`__.
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In 0.19.0 ``PanelND`` is deprecated and will be removed in a future version. The recommended way to represent these types of n-dimensional data are with the `xarray package <http://xarray.pydata.org/en/stable/>`__.
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PanelND is a module with a set of factory functions to enable a user to construct N-dimensional named
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containers like Panel4D, with a custom set of axis labels. Thus a domain-specific container can easily be

doc/source/io.rst

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you can end up with column(s) with mixed dtypes. For example,
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.. ipython:: python
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:okwarning:
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:okwarning:
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df = pd.DataFrame({'col_1':range(500000) + ['a', 'b'] + range(500000)})
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df.to_csv('foo')
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mixed_df = pd.read_csv('foo')
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mixed_df['col_1'].apply(type).value_counts()
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mixed_df['col_1'].dtype
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df = pd.DataFrame({'col_1':range(500000) + ['a', 'b'] + range(500000)})
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df.to_csv('foo')
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mixed_df = pd.read_csv('foo')
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mixed_df['col_1'].apply(type).value_counts()
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mixed_df['col_1'].dtype
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will result with `mixed_df` containing an ``int`` dtype for certain chunks
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of the column, and ``str`` for others due to the mixed dtypes from the

doc/source/whatsnew/v0.19.0.txt

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from pandas.compat import StringIO
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.. _whatsnew_0190.enhancements.read_csv_dupe_col_names_support:
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:ref:`Duplicate column names <io.dupe_names>` are now supported in :func:`read_csv` whether
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they are in the file or passed in as the ``names`` parameter (:issue:`7160`, :issue:`9424`)
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pandas/tseries/tdi.py

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Make the interval closed with respect to the given frequency to
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the 'left', 'right', or both sides (None)
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Notes
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-----
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2 of start, end, or periods must be specified
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Returns
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-------
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rng : TimedeltaIndex
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Notes
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-----
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2 of start, end, or periods must be specified.
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To learn more about the frequency strings, please see `this link
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<http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases>`__.
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"""

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