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ci/code_checks.sh

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RET=$(($RET + $?)) ; echo $MSG "DONE"
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MSG='Validate correct capitalization among titles in documentation' ; echo $MSG
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$BASE_DIR/scripts/validate_rst_title_capitalization.py $BASE_DIR/doc/source/development/contributing.rst
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$BASE_DIR/scripts/validate_rst_title_capitalization.py $BASE_DIR/doc/source/development/contributing.rst $BASE_DIR/doc/source/reference
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RET=$(($RET + $?)) ; echo $MSG "DONE"
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fi

doc/source/development/code_style.rst

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Patterns
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========
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foo.__class__
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-------------
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Using foo.__class__
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-------------------
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pandas uses 'type(foo)' instead 'foo.__class__' as it is making the code more
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Concatenated strings
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--------------------
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f-strings
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~~~~~~~~~
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Using f-strings
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~~~~~~~~~~~~~~~
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pandas uses f-strings formatting instead of '%' and '.format()' string formatters.
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doc/source/development/contributing.rst

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under Windows. For details please refer to the
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`official virtualenv user guide <https://virtualenv.pypa.io/en/stable/userguide/#activate-script>`__
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Use an ENV_DIR of your choice. We'll use ~\virtualenvs\pandas-dev where
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Use an ENV_DIR of your choice. We'll use ~\\virtualenvs\\pandas-dev where
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'~' is the folder pointed to by either $env:USERPROFILE (Powershell) or
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%USERPROFILE% (cmd.exe) environment variable. Any parent directories
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should already exist.

doc/source/development/extending.rst

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.. _extending.extension.operator:
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:class:`~pandas.api.extensions.ExtensionArray` Operator Support
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:class:`~pandas.api.extensions.ExtensionArray` operator support
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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.. versionadded:: 0.24.0

doc/source/development/policies.rst

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.. _policies.version:
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Version Policy
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Version policy
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~~~~~~~~~~~~~~
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These policies do not apply to features marked as **experimental** in the documentation.
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pandas may change the behavior of experimental features at any time.
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Python Support
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Python support
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~~~~~~~~~~~~~~
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pandas will only drop support for specific Python versions (e.g. 3.6.x, 3.7.x) in

doc/source/development/roadmap.rst

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.. _roadmap.evolution:
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Roadmap Evolution
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Roadmap evolution
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-----------------
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pandas continues to evolve. The direction is primarily determined by community

doc/source/getting_started/intro_tutorials/09_timeseries.rst

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pd.read_csv("../data/air_quality_no2_long.csv", parse_dates=["datetime"])
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Why are these :class:`pandas.Timestamp` objects useful. Let’s illustrate the added
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Why are these :class:`pandas.Timestamp` objects useful? Let’s illustrate the added
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air_quality["datetime"].min(), air_quality["datetime"].max()
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Using :class:`pandas.Timestamp` for datetimes enable us to calculate with date
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Using :class:`pandas.Timestamp` for datetimes enables us to calculate with date
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information and make them comparable. Hence, we can use this to get the
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length of our time series:
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<div class="d-flex flex-row gs-torefguide">
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<span class="badge badge-info">To user guide</span>
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The different time concepts supported by pandas are explained in the user guide section on :ref:`time related concepts <timeseries.overview>`.
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The various time concepts supported by pandas are explained in the user guide section on :ref:`time related concepts <timeseries.overview>`.
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.. raw:: html
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An overview of the existing date properties is given in the
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:ref:`time and date components overview table <timeseries.components>`. More details about the ``dt`` accessor
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to return datetime like properties is explained in a dedicated section on the :ref:`dt accessor <basics.dt_accessors>`.
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to return datetime like properties are explained in a dedicated section on the :ref:`dt accessor <basics.dt_accessors>`.
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.. raw:: html
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<div class="d-flex flex-row gs-torefguide">
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<span class="badge badge-info">To user guide</span>
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More details on the power of time series ``resampling`` is provided in the user gudie section on :ref:`resampling <timeseries.resampling>`.
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More details on the power of time series ``resampling`` is provided in the user guide section on :ref:`resampling <timeseries.resampling>`.
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- Valid date strings can be converted to datetime objects using
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``to_datetime`` function or as part of read functions.
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- Datetime objects in pandas supports calculations, logical operations
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- Datetime objects in pandas support calculations, logical operations
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- A ``DatetimeIndex`` contains these date-related properties and
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<div class="d-flex flex-row gs-torefguide">
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A full overview on time series is given in the pages on :ref:`time series and date functionality <timeseries>`.
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A full overview on time series is given on the pages on :ref:`time series and date functionality <timeseries>`.
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doc/source/reference/frame.rst

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DataFrame.merge
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Time series-related
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Time Series-related
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~~~~~~~~~~~~~~~~~~~
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.. autosummary::
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:toctree: api/

doc/source/reference/indexing.rst

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DatetimeIndex
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Time/Date components
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Time/date components
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~~~~~~~~~~~~~~~~~~~~
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.. autosummary::
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:toctree: api/

doc/source/reference/series.rst

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Series.product
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Function application, GroupBy & window
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.. autosummary::
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Time Series-related
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:toctree: api/

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