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Removed references to v0.17 in docs and doc strings.
Also removes a reference to 0.13.
1 parent 29a9f63 commit 8c85ab2

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doc/source/basics.rst

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@@ -1738,11 +1738,6 @@ description.
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Sorting
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-------
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.. warning::
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The sorting API is substantially changed in 0.17.0, see :ref:`here <whatsnew_0170.api_breaking.sorting>` for these changes.
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In particular, all sorting methods now return a new object by default, and **DO NOT** operate in-place (except by passing ``inplace=True``).
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There are two obvious kinds of sorting that you may be interested in: sorting
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by label and sorting by actual values.
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@@ -1829,8 +1824,6 @@ faster than sorting the entire Series and calling ``head(n)`` on the result.
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s.nsmallest(3)
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s.nlargest(3)
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.. versionadded:: 0.17.0
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``DataFrame`` also has the ``nlargest`` and ``nsmallest`` methods.
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.. ipython:: python
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------
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The main types stored in pandas objects are ``float``, ``int``, ``bool``,
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``datetime64[ns]`` and ``datetime64[ns, tz]`` (in >= 0.17.0), ``timedelta[ns]``,
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``datetime64[ns]`` and ``datetime64[ns, tz]``, ``timedelta[ns]``,
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``category`` and ``object``. In addition these dtypes have item sizes, e.g.
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``int64`` and ``int32``. See :ref:`Series with TZ <timeseries.timezone_series>`
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for more detail on ``datetime64[ns, tz]`` dtypes.

doc/source/categorical.rst

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@@ -632,8 +632,6 @@ To get a single value `Series` of type ``category`` pass in a list with a single
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String and datetime accessors
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. versionadded:: 0.17.1
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The accessors ``.dt`` and ``.str`` will work if the ``s.cat.categories`` are of an appropriate
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type:
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doc/source/computation.rst

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@@ -206,8 +206,6 @@ Window Functions
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functions and are now deprecated. These are replaced by using the :class:`~pandas.core.window.Rolling`, :class:`~pandas.core.window.Expanding` and :class:`~pandas.core.window.EWM`. objects and a corresponding method call.
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The deprecation warning will show the new syntax, see an example :ref:`here <whatsnew_0180.window_deprecations>`
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You can view the previous documentation
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`here <http://pandas.pydata.org/pandas-docs/version/0.17.1/computation.html#moving-rolling-statistics-moments>`__
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For working with data, a number of windows functions are provided for
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computing common *window* or *rolling* statistics. Among these are count, sum,

doc/source/contributing.rst

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@@ -877,12 +877,12 @@ directive is used. The sphinx syntax for that is:
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.. code-block:: rst
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.. versionadded:: 0.17.0
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.. versionadded:: 0.21.0
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This will put the text *New in version 0.17.0* wherever you put the sphinx
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This will put the text *New in version 0.21.0* wherever you put the sphinx
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directive. This should also be put in the docstring when adding a new function
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or method (`example <https://github.com/pandas-dev/pandas/blob/v0.16.2/pandas/core/generic.py#L1959>`__)
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or a new keyword argument (`example <https://github.com/pandas-dev/pandas/blob/v0.16.2/pandas/core/frame.py#L1171>`__).
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or method (`example <https://github.com/pandas-dev/pandas/blob/v0.20.2/pandas/core/frame.py#L1495>`__)
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or a new keyword argument (`example <https://github.com/pandas-dev/pandas/blob/v0.20.2/pandas/core/generic.py#L568>`__).
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Contributing your changes to *pandas*
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=====================================

doc/source/ecosystem.rst

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@@ -146,7 +146,10 @@ API
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`pandas-datareader <https://github.com/pydata/pandas-datareader>`__
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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``pandas-datareader`` is a remote data access library for pandas. ``pandas.io`` from pandas < 0.17.0 is now refactored/split-off to and importable from ``pandas_datareader`` (PyPI:``pandas-datareader``). Many/most of the supported APIs have at least a documentation paragraph in the `pandas-datareader docs <https://pandas-datareader.readthedocs.io/en/latest/>`_:
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``pandas-datareader`` is a remote data access library for pandas (PyPI:``pandas-datareader``).
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It is based on functionality that was located in ``pandas.io.data`` and ``pandas.io.wb`` but was
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split off in v0.19.
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See more in the `pandas-datareader docs <https://pandas-datareader.readthedocs.io/en/latest/>`_:
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The following data feeds are available:
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doc/source/gotchas.rst

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@@ -47,8 +47,6 @@ The ``+`` symbol indicates that the true memory usage could be higher, because
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pandas does not count the memory used by values in columns with
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``dtype=object``.
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.. versionadded:: 0.17.1
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Passing ``memory_usage='deep'`` will enable a more accurate memory usage report,
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that accounts for the full usage of the contained objects. This is optional
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as it can be expensive to do this deeper introspection.

doc/source/indexing.rst

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@@ -1632,8 +1632,6 @@ Missing values
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.. _indexing.missing:
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.. versionadded:: 0.17.1
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.. important::
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Even though ``Index`` can hold missing values (``NaN``), it should be avoided

doc/source/io.rst

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@@ -2689,11 +2689,6 @@ of sheet names can simply be passed to ``read_excel`` with no loss in performanc
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# equivalent using the read_excel function
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data = read_excel('path_to_file.xls', ['Sheet1', 'Sheet2'], index_col=None, na_values=['NA'])
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.. versionadded:: 0.17
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``read_excel`` can take an ``ExcelFile`` object as input
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.. _io.excel.specifying_sheets:
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Specifying Sheets
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Reading a ``MultiIndex``
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++++++++++++++++++++++++
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.. versionadded:: 0.17
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``read_excel`` can read a ``MultiIndex`` index, by passing a list of columns to ``index_col``
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and a ``MultiIndex`` column by passing a list of rows to ``header``. If either the ``index``
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or ``columns`` have serialized level names those will be read in as well by specifying
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Writing Excel Files to Memory
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+++++++++++++++++++++++++++++
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.. versionadded:: 0.17
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Pandas supports writing Excel files to buffer-like objects such as ``StringIO`` or
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``BytesIO`` using :class:`~pandas.io.excel.ExcelWriter`.
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.. versionadded:: 0.17
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Added support for Openpyxl >= 2.2
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``BytesIO`` using :class:`~pandas.io.excel.ExcelWriter`. Pandas also supports Openpyxl >= 2.2.
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.. code-block:: python
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optimizations in the io of the ``msgpack`` data. Since this is marked
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as an EXPERIMENTAL LIBRARY, the storage format may not be stable until a future release.
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As a result of writing format changes and other issues:
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+----------------------+------------------------+
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| Packed with | Can be unpacked with |
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+======================+========================+
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| pre-0.17 / Python 2 | any |
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+----------------------+------------------------+
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| pre-0.17 / Python 3 | any |
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+----------------------+------------------------+
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| 0.17 / Python 2 | - 0.17 / Python 2 |
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| | - >=0.18 / any Python |
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+----------------------+------------------------+
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| 0.17 / Python 3 | >=0.18 / any Python |
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+----------------------+------------------------+
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| 0.18 | >= 0.18 |
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+----------------------+------------------------+
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Reading (files packed by older versions) is backward-compatibile, except for files packed with 0.17 in Python 2, in which case only they can only be unpacked in Python 2.
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.. ipython:: python
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df = pd.DataFrame(np.random.rand(5,2),columns=list('AB'))
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If you see a subset of results being returned, upgrade to ``PyTables`` >= 3.2.
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Stores created previously will need to be rewritten using the updated version.
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.. warning::
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As of version 0.17.0, ``HDFStore`` will not drop rows that have all missing values by default. Previously, if all values (except the index) were missing, ``HDFStore`` would not write those rows to disk.
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.. ipython:: python
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:suppress:
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:okexcept:
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os.remove('store_tl.h5')
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As of version 0.17.0, HDFStore will no longer drop rows that are all missing by default. This behavior can be enabled by setting ``dropna=True``.
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HDFStore will by default not drop rows that are all missing. This behavior can be changed by setting ``dropna=True``.
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.. ipython:: python
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:suppress:
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Querying a Table
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++++++++++++++++
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.. warning::
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This query capabilities have changed substantially starting in ``0.13.0``.
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Queries from prior version are accepted (with a ``DeprecationWarning``) printed
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if its not string-like.
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``select`` and ``delete`` operations have an optional criterion that can
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be specified to select/delete only a subset of the data. This allows one
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to have a very large on-disk table and retrieve only a portion of the
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SAS Formats
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-----------
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.. versionadded:: 0.17.0
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The top-level function :func:`read_sas` can read (but not write) SAS
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`xport` (.XPT) and `SAS7BDAT` (.sas7bdat) format files were added in *v0.18.0*.
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`xport` (.XPT) and (since *v0.18.0*) `SAS7BDAT` (.sas7bdat) format files.
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SAS files only contain two value types: ASCII text and floating point
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values (usually 8 bytes but sometimes truncated). For xport files,

doc/source/merging.rst

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merge key only appears in ``'right'`` DataFrame, and ``both`` if the
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observation's merge key is found in both.
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- ``validate`` : string, default None.
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If specified, checks if merge is of specified type.
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The merge indicator
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``merge`` now accepts the argument ``indicator``. If ``True``, a Categorical-type column called ``_merge`` will be added to the output object that takes on values:
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``merge`` accepts the argument ``indicator``. If ``True``, a Categorical-type column called ``_merge`` will be added to the output object that takes on values:
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=================================== ================
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Observation Origin ``_merge`` value

doc/source/missing_data.rst

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Interpolation
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The ``limit_direction`` keyword argument was added.
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doc/source/remote_data.rst

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DataReader
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The sub-package ``pandas.io.data`` was deprecated in v.0.17 and removed in
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The sub-package ``pandas.io.data`` was removed in
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`v.0.19 <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#v0-19-0-october-2-2016>`__.
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Instead there has been created a separately installable
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doc/source/timeseries.rst

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Invalid Data
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.. note::
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In version 0.17.0, the default for ``to_datetime`` is now ``errors='raise'``, rather than ``errors='ignore'``. This means
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that invalid parsing will raise rather that return the original input as in previous versions.
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The default behavior, ``errors='raise'``, is to raise when unparseable:
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The default behavior, ``errors='raise'``, is to raise when unparseable:
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TZ Aware Dtypes
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``Series/DatetimeIndex`` with a timezone **naive** value are represented with a dtype of ``datetime64[ns]``.
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doc/source/visualization.rst

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@savefig bar_plot_ex.png
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You can also create these other plots using the methods ``DataFrame.plot.<kind>`` instead of providing the ``kind`` keyword argument. This makes it easier to discover plot methods and the specific arguments they use:
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.. ipython::

pandas/core/frame.py

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"right_only" for observations whose merge key only appears in 'right'
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validate : string, default None
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Abbreviations are allowed. `s` indicates `series` and `sp`
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pandas/core/generic.py

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axis : %(axes_single_arg)s, default 0
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Examples
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Examples
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pandas/core/indexes/base.py

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Examples

pandas/core/indexes/datetimelike.py

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