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DOC: fix doc build warnings (pandas-dev#15505)
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doc/source/advanced.rst

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@@ -965,6 +965,7 @@ The different indexing operation can potentially change the dtype of a ``Series`
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res
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.. ipython:: python
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series2 = pd.Series([True])
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series2.dtype
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res = series2.reindex_like(series1)

doc/source/basics.rst

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@@ -1889,7 +1889,7 @@ gotchas
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Performing selection operations on ``integer`` type data can easily upcast the data to ``floating``.
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The dtype of the input data will be preserved in cases where ``nans`` are not introduced (starting in 0.11.0)
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See also :ref:`Support for integer ``NA`` <gotchas.intna>`
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See also :ref:`Support for integer NA <gotchas.intna>`
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.. ipython:: python
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doc/source/contributing.rst

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@@ -461,7 +461,7 @@ C (cpplint)
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*pandas* uses the `Google <https://google.github.io/styleguide/cppguide.html>`_
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standard. Google provides an open source style checker called ``cpplint``, but we
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use a fork of it that can be found `here <https://github.com/cpplint/cpplint>`_.
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use a fork of it that can be found `here <https://github.com/cpplint/cpplint>`__.
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Here are *some* of the more common ``cpplint`` issues:
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- we restrict line-length to 80 characters to promote readability
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To make your commits compliant with this standard, you can install the
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`ClangFormat <http://clang.llvm.org/docs/ClangFormat.html>`_ tool, which can be
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downloaded `here <http://llvm.org/builds/>`_. To configure, in your home directory,
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downloaded `here <http://llvm.org/builds/>`__. To configure, in your home directory,
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run the following command::
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clang-format style=google -dump-config > .clang-format
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pytest pandas/tests/[test-module].py::[TestClass]
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pytest pandas/tests/[test-module].py::[TestClass]::[test_method]
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For more, see the `pytest<http://doc.pytest.org/en/latest/>`_ documentation.
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For more, see the `pytest <http://doc.pytest.org/en/latest/>`_ documentation.
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.. versionadded:: 0.20.0
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doc/source/install.rst

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@@ -282,7 +282,7 @@ Optional Dependencies
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okay.)
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* `BeautifulSoup4`_ and `lxml`_
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* `BeautifulSoup4`_ and `html5lib`_ and `lxml`_
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* Only `lxml`_, although see :ref:`HTML Table Parsing <gotchas.html>`
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* Only `lxml`_, although see :ref:`HTML Table Parsing <io.html.gotchas>`
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for reasons as to why you should probably **not** take this approach.
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.. warning::

doc/source/io.rst

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.. warning::
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We **highly encourage** you to read the :ref:`HTML Table Parsing gotchas<io.html.gotchas>`
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We **highly encourage** you to read the :ref:`HTML Table Parsing gotchas <io.html.gotchas>`
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below regarding the issues surrounding the BeautifulSoup4/html5lib/lxml parsers.
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.. versionadded:: 0.12.0
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Supported Data Types
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++++++++++++++++++++
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''''''''''''''''''''
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Pandas supports all these `BigQuery data types <https://cloud.google.com/bigquery/data-types>`__:
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``STRING``, ``INTEGER`` (64bit), ``FLOAT`` (64 bit), ``BOOLEAN`` and
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``TIMESTAMP`` (microsecond precision). Data types ``BYTES`` and ``RECORD``
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are not supported.
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Integer and boolean ``NA`` handling
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'''''''''''''''''''''''''''''''''''
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.. versionadded:: 0.20
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.. _io.bigquery_deps:
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Dependencies
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++++++++++++
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''''''''''''
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This module requires following additional dependencies:
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doc/source/whatsnew/v0.20.0.txt

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@@ -120,7 +120,7 @@ Notably, a new numerical index, ``UInt64Index``, has been created (:issue:`14937
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- Bug in ``pd.unique()`` in which unsigned 64-bit integers were causing overflow (:issue:`14915`)
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- Bug in ``pd.value_counts()`` in which unsigned 64-bit integers were being erroneously truncated in the output (:issue:`14934`)
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.. _whatsnew_0200.enhancements.groupy_categorical
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.. _whatsnew_0200.enhancements.groupy_categorical:
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GroupBy on Categoricals
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^^^^^^^^^^^^^^^^^^^^^^^

pandas/core/generic.py

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_shared_docs['to_excel'] = """
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Write %(klass)s to an excel sheet
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%(versionadded_to_excel)s
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Parameters
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----------
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excel_writer : string or ExcelWriter object

pandas/io/html.py

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Notes
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-----
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Before using this function you should read the :ref:`gotchas about the
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HTML parsing libraries <html-gotchas>`.
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HTML parsing libraries <io.html.gotchas>`.
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Expect to do some cleanup after you call this function. For example, you
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might need to manually assign column names if the column names are

pandas/io/json/normalize.py

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path to records is ['foo', 'bar']
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meta_prefix : string, default None
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errors : {'raise', 'ignore'}, default 'raise'
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* ignore : will ignore KeyError if keys listed in meta are not
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always present
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* raise : will raise KeyError if keys listed in meta are not
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always present
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* 'ignore' : will ignore KeyError if keys listed in meta are not
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always present
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* 'raise' : will raise KeyError if keys listed in meta are not
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always present
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.. versionadded:: 0.20.0
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pandas/io/parsers.py

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If True and parse_dates is enabled, pandas will attempt to infer the format
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of the datetime strings in the columns, and if it can be inferred, switch
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to a faster method of parsing them. In some cases this can increase the
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parsing speed by ~5-10x.
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parsing speed by 5-10x.
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keep_date_col : boolean, default False
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If True and parse_dates specifies combining multiple columns then
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keep the original columns.
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Return TextFileReader object for iteration or getting chunks with
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``get_chunk()``.
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chunksize : int, default None
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Return TextFileReader object for iteration. `See IO Tools docs for more
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information
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<http://pandas.pydata.org/pandas-docs/stable/io.html#io-chunking>`_ on
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``iterator`` and ``chunksize``.
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Return TextFileReader object for iteration.
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See the `IO Tools docs
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<http://pandas.pydata.org/pandas-docs/stable/io.html#io-chunking>`_
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for more information on ``iterator`` and ``chunksize``.
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compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, default 'infer'
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For on-the-fly decompression of on-disk data. If 'infer', then use gzip,
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bz2, zip or xz if filepath_or_buffer is a string ending in '.gz', '.bz2',

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