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Merge branch 'between-time-axis' of https://github.com/yrhooke/pandas into between-time-axis
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‎ci/appveyor-27.yaml

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- xlsxwriter
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# universal
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- cython
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- cython>=0.28.2
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- pytest
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- moto

‎ci/appveyor-36.yaml

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‎ci/circle-27-compat.yaml

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dependencies:
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- bottleneck=1.0.0
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- cython=0.28.2
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- jinja2=2.8
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- numexpr=2.4.4 # we test that we correctly don't use an unsupported numexpr
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‎ci/circle-35-ascii.yaml

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‎ci/circle-36-locale.yaml

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‎ci/circle-36-locale_slow.yaml

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‎ci/environment-dev.yaml

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‎ci/travis-27-locale.yaml

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‎ci/travis-27.yaml

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‎ci/travis-35-osx.yaml

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‎ci/travis-36-doc.yaml

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‎ci/travis-36-numpydev.yaml

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‎ci/travis-36-slow.yaml

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‎ci/travis-36.yaml

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‎ci/travis-37.yaml

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‎conda.recipe/meta.yaml

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- pip
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- numpy 1.11.*
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- numpy
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- python {{ python }}
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‎doc/source/api.rst

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Series.value_counts
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Series.compound
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‎doc/source/basics.rst

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dtypes
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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]``, ``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.
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For the most part, pandas uses NumPy arrays and dtypes for Series or individual
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columns of a DataFrame. The main types allowed in pandas objects are ``float``,
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``int``, ``bool``, and ``datetime64[ns]`` (note that NumPy does not support
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timezone-aware datetimes).
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In addition to NumPy's types, pandas :ref:`extends <extending.extension-types>`
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NumPy's type-system for a few cases.
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* :ref:`Categorical <categorical>`
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* :ref:`Datetime with Timezone <timeseries.timezone_series>`
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* :ref:`Period <timeseries.periods>`
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* :ref:`Interval <advanced.indexing.intervallindex>`
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Pandas uses the ``object`` dtype for storing strings.
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Finally, arbitrary objects may be stored using the ``object`` dtype, but should
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be avoided to the extent possible (for performance and interoperability with
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other libraries and methods. See :ref:`basics.object_conversion`).
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A convenient :attr:`~DataFrame.dtypes` attribute for DataFrame returns a Series
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with the data type of each column.

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