Metadata-Version: 2.0
Name: pandas-market-calendars
Version: 0.6
Summary: Market and exchange trading calendars for pandas
Home-page: https://github.com/rsheftel/pandas_market_calendars
Author: Ryan Sheftel
Author-email: rsheftel@alumni.upenn.edu
License: MIT
Keywords: trading exchanges markets OTC datetime holiday business days
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Dist: pandas (>=0.18)
Requires-Dist: six
Requires-Dist: toolz

pandas_market_calendars
=======================
Market calendars to use with pandas for trading applications.

.. image:: https://travis-ci.org/rsheftel/pandas_market_calendars.svg?branch=master
    :target: https://travis-ci.org/rsheftel/pandas_market_calendars

.. image:: https://coveralls.io/repos/github/rsheftel/pandas_market_calendars/badge.svg?branch=master
    :target: https://coveralls.io/github/rsheftel/pandas_market_calendars?branch=master

Documentation
-------------
http://pandas_market_calendars.readthedocs.io/en/latest/

Overview
--------
The Pandas package is widely used in finance and specifically for time series analysis. It includes excellent
functionality for generating sequences of dates and capabilities for custom holiday calendars, but as an explicit
design choice it does not include the actual holiday calendars for specific exchanges or OTC markets.

The pandas_market_calendars package looks to fill that role with the holiday, late open and early close calendars
for specific exchanges and OTC conventions. pandas_market_calendars also adds several functions to manipulate the
market calendars and includes a date_range function to create a pandas DatetimeIndex including only the datetimes
when the markets are open.

This package is a fork of the Zipline package from Quantopian and extracts just the relevant parts. All credit for
their excellent work to Quantopian.

Installation
------------
``pip install pandas_market_calendars``

Quick Start
-----------
.. code:: python

    import pandas_market_calendars as mcal
    nyse = mcal.get_calendar('NYSE')


.. code:: python

    early = nyse.schedule(start_date='2012-07-01', end_date='2012-07-10')
    early


.. parsed-literal::

                      market_open             market_close
    =========== ========================= =========================
     2012-07-02 2012-07-02 13:30:00+00:00 2012-07-02 20:00:00+00:00
     2012-07-03 2012-07-03 13:30:00+00:00 2012-07-03 17:00:00+00:00
     2012-07-05 2012-07-05 13:30:00+00:00 2012-07-05 20:00:00+00:00
     2012-07-06 2012-07-06 13:30:00+00:00 2012-07-06 20:00:00+00:00
     2012-07-09 2012-07-09 13:30:00+00:00 2012-07-09 20:00:00+00:00
     2012-07-10 2012-07-10 13:30:00+00:00 2012-07-10 20:00:00+00:00


.. code:: python

    mcal.date_range(early, frequency='1D')




.. parsed-literal::

    DatetimeIndex(['2012-07-02 20:00:00+00:00', '2012-07-03 17:00:00+00:00',
                   '2012-07-05 20:00:00+00:00', '2012-07-06 20:00:00+00:00',
                   '2012-07-09 20:00:00+00:00', '2012-07-10 20:00:00+00:00'],
                  dtype='datetime64[ns, UTC]', freq=None)



.. code:: python

    mcal.date_range(early, frequency='1H')




.. parsed-literal::

    DatetimeIndex(['2012-07-02 14:30:00+00:00', '2012-07-02 15:30:00+00:00',
                   '2012-07-02 16:30:00+00:00', '2012-07-02 17:30:00+00:00',
                   '2012-07-02 18:30:00+00:00', '2012-07-02 19:30:00+00:00',
                   '2012-07-02 20:00:00+00:00', '2012-07-03 14:30:00+00:00',
                   '2012-07-03 15:30:00+00:00', '2012-07-03 16:30:00+00:00',
                   '2012-07-03 17:00:00+00:00', '2012-07-05 14:30:00+00:00',
                   '2012-07-05 15:30:00+00:00', '2012-07-05 16:30:00+00:00',
                   '2012-07-05 17:30:00+00:00', '2012-07-05 18:30:00+00:00',
                   '2012-07-05 19:30:00+00:00', '2012-07-05 20:00:00+00:00',
                   '2012-07-06 14:30:00+00:00', '2012-07-06 15:30:00+00:00',
                   '2012-07-06 16:30:00+00:00', '2012-07-06 17:30:00+00:00',
                   '2012-07-06 18:30:00+00:00', '2012-07-06 19:30:00+00:00',
                   '2012-07-06 20:00:00+00:00', '2012-07-09 14:30:00+00:00',
                   '2012-07-09 15:30:00+00:00', '2012-07-09 16:30:00+00:00',
                   '2012-07-09 17:30:00+00:00', '2012-07-09 18:30:00+00:00',
                   '2012-07-09 19:30:00+00:00', '2012-07-09 20:00:00+00:00',
                   '2012-07-10 14:30:00+00:00', '2012-07-10 15:30:00+00:00',
                   '2012-07-10 16:30:00+00:00', '2012-07-10 17:30:00+00:00',
                   '2012-07-10 18:30:00+00:00', '2012-07-10 19:30:00+00:00',
                   '2012-07-10 20:00:00+00:00'],
                  dtype='datetime64[ns, UTC]', freq=None)

Future
------
This package is open sourced under the MIT license. Everyone is welcome to add more exchanges or OTC markets, confirm
or correct the existing calendars, and generally do whatever they desire with this code.


