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Merge pull request #11504 from scari/master
Fixed typos
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doc/source/advanced.rst

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@@ -686,7 +686,7 @@ values NOT in the categories, similarly to how you can reindex ANY pandas index.
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.. warning::
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Reshaping and Comparision operations on a ``CategoricalIndex`` must have the same categories
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Reshaping and Comparison operations on a ``CategoricalIndex`` must have the same categories
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or a ``TypeError`` will be raised.
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.. code-block:: python

doc/source/categorical.rst

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@@ -718,7 +718,7 @@ Old style constructor usage
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In earlier versions than pandas 0.15, a `Categorical` could be constructed by passing in precomputed
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`codes` (called then `labels`) instead of values with categories. The `codes` were interpreted as
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pointers to the categories with `-1` as `NaN`. This type of constructor useage is replaced by
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pointers to the categories with `-1` as `NaN`. This type of constructor usage is replaced by
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the special constructor :func:`Categorical.from_codes`.
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Unfortunately, in some special cases, using code which assumes the old style constructor usage

doc/source/enhancingperf.rst

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@@ -699,7 +699,7 @@ ol' Python.
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.. note::
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Using the ``'python'`` engine is generally *not* useful, except for testing
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other evaluation engines against it. You will acheive **no** performance
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other evaluation engines against it. You will achieve **no** performance
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benefits using :func:`~pandas.eval` with ``engine='python'`` and in fact may
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incur a performance hit.
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doc/source/indexing.rst

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@@ -97,7 +97,7 @@ of multi-axis indexing.
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axis is of integer type. ``.ix`` is the most general and will
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support any of the inputs in ``.loc`` and ``.iloc``. ``.ix`` also supports floating point
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label schemes. ``.ix`` is exceptionally useful when dealing with mixed positional
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and label based hierachical indexes.
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and label based hierarchical indexes.
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However, when an axis is integer based, ONLY
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label based access and not positional access is supported.
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.. warning::
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The chained assignment warnings / exceptions are aiming to inform the user of a possibly invalid
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assignment. There may be false positives; situations where a chained assignment is inadvertantly
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assignment. There may be false positives; situations where a chained assignment is inadvertently
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reported.

doc/source/io.rst

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@@ -2006,7 +2006,7 @@ file, and the ``sheetname`` indicating which sheet to parse.
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``ExcelFile`` class
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+++++++++++++++++++
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To faciliate working with multiple sheets from the same file, the ``ExcelFile``
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To facilitate working with multiple sheets from the same file, the ``ExcelFile``
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class can be used to wrap the file and can be be passed into ``read_excel``
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There will be a performance benefit for reading multiple sheets as the file is
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read into memory only once.

doc/source/remote_data.rst

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@@ -373,7 +373,7 @@ The first thing you need to do is to setup accesses to Google Analytics API. Fol
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#. rename it to ``client_secrets.json``
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#. move it to the ``pandas/io`` module directory
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The first time you use the :func:`read_ga` funtion, a browser window will open to ask you to authentify to the Google API. Do proceed.
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The first time you use the :func:`read_ga` function, a browser window will open to ask you to authentify to the Google API. Do proceed.
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Using the Google Analytics API
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

doc/source/timedeltas.rst

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.. versionadded:: 0.13
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Timedelta Series, ``TimedeltaIndex``, and ``Timedelta`` scalars can be converted to other 'frequencies' by dividing by another timedelta,
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or by astyping to a specific timedelta type. These operations yield Series and propogate ``NaT`` -> ``nan``.
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or by astyping to a specific timedelta type. These operations yield Series and propagate ``NaT`` -> ``nan``.
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Note that division by the numpy scalar is true division, while astyping is equivalent of floor division.
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.. ipython:: python

doc/source/visualization.rst

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plt.close('all')
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Using Layout and Targetting Multiple Axes
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Using Layout and Targeting Multiple Axes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The layout of subplots can be specified by ``layout`` keyword. It can accept

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