DataFrame with inline stock statistics support.
Project description
Stock Statistics/Indicators Calculation Helper
==============================================
.. image:: https://travis-ci.org/jealous/stockstats.svg
:target: https://travis-ci.org/jealous/stockstats
.. image:: https://coveralls.io/repos/jealous/stockstats/badge.svg
:target: https://coveralls.io/github/jealous/stockstats
.. image:: https://img.shields.io/pypi/v/stockstats.svg
:target: https://pypi.python.org/pypi/stockstats
VERSION: 0.1.4
Introduction
------------
Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with
inline stock statistics/indicators support.
Supported statistics/indicators are:
- change (in percent)
- delta
- permutation (zero based)
- log return
- max in range
- min in range
- middle = (close + high + low) / 3
- SMA: simple moving average
- EMA: exponential moving average
- MSTD: moving standard deviation
- MVAR: moving variance
- RSV: raw stochastic value
- RSI: relative strength index
- KDJ: Stochastic oscillator
- Bolling: including upper band and lower band.
- MACD: moving average convergence divergence. Including signal and histogram.
- CR:
- line cross check, cross up or cross down.
Installation
------------
``pip install stockstats``
License
-------
`BSD`_
Tutorial
--------
- Initialize the ``StockDataFrame`` with the ``retype`` function which
convert a ``pandas.DataFrame`` to a ``StockDataFrame``.
.. code-block:: python
stock = StockDataFrame.retype(pd.read_csv('stock.csv'))
- There are some shortcuts for frequent used statistics/indicators like
``kdjk``, ``boll_hb``, ``macd``, etc.
- The indicators/statistics are generated on the fly when they are accessed.
If you are accessing through ``Series``, it may return not found error.
The fix is to explicitly initialize it by accessing it like below:
.. code-block:: python
_ = stock['macd']
# or
stock.get('macd')
- Using get item to access the indicators. The item name following the
pattern: ``{columnName_window_statistics}``.
Some statistics/indicators has their short cut. See examples below:
.. code-block:: python
# volume delta against previous day
stock['volume_delta']
# open delta against next 2 day
stock['open_2_d']
# open price change (in percent) between today and the day before yesterday
# 'r' stands for rate.
stock['open_-2_r']
# CR indicator, including 5, 10, 20 days moving average
stock['cr']
stock['cr-ma1']
stock['cr-ma2']
stock['cr-ma3']
# volume max of three days ago, yesterday and two days later
stock['volume_-3,2,-1_max']
# volume min between 3 days ago and tomorrow
stock['volume_-3~1_min']
# KDJ, default to 9 days
stock['kdjk']
stock['kdjd']
stock['kdjj']
# three days KDJK cross up 3 days KDJD
stock['kdj_3_xu_kdjd_3']
# 2 days simple moving average on open price
stock['open_2_sma']
# MACD
stock['macd']
# MACD signal line
stock['macds']
# MACD histogram
stock['macdh']
# bolling, including upper band and lower band
stock['boll']
stock['boll_ub']
stock['boll_lb']
# close price less than 10.0 in 5 days count
stock['close_10.0_le_5_c']
# CR MA2 cross up CR MA1 in 20 days count
stock['cr-ma2_xu_cr-ma1_20_c']
# 6 days RSI
stock['rsi_6']
# 12 days RSI
stock['rsi_12']
To file issue, please visit:
https://github.com/jealous/stockstats
Contact author:
- Cedric Zhuang <jealous@163.com>
.. _BSD: LICENSE.txt
.. _test.py: test.py
==============================================
.. image:: https://travis-ci.org/jealous/stockstats.svg
:target: https://travis-ci.org/jealous/stockstats
.. image:: https://coveralls.io/repos/jealous/stockstats/badge.svg
:target: https://coveralls.io/github/jealous/stockstats
.. image:: https://img.shields.io/pypi/v/stockstats.svg
:target: https://pypi.python.org/pypi/stockstats
VERSION: 0.1.4
Introduction
------------
Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with
inline stock statistics/indicators support.
Supported statistics/indicators are:
- change (in percent)
- delta
- permutation (zero based)
- log return
- max in range
- min in range
- middle = (close + high + low) / 3
- SMA: simple moving average
- EMA: exponential moving average
- MSTD: moving standard deviation
- MVAR: moving variance
- RSV: raw stochastic value
- RSI: relative strength index
- KDJ: Stochastic oscillator
- Bolling: including upper band and lower band.
- MACD: moving average convergence divergence. Including signal and histogram.
- CR:
- line cross check, cross up or cross down.
Installation
------------
``pip install stockstats``
License
-------
`BSD`_
Tutorial
--------
- Initialize the ``StockDataFrame`` with the ``retype`` function which
convert a ``pandas.DataFrame`` to a ``StockDataFrame``.
.. code-block:: python
stock = StockDataFrame.retype(pd.read_csv('stock.csv'))
- There are some shortcuts for frequent used statistics/indicators like
``kdjk``, ``boll_hb``, ``macd``, etc.
- The indicators/statistics are generated on the fly when they are accessed.
If you are accessing through ``Series``, it may return not found error.
The fix is to explicitly initialize it by accessing it like below:
.. code-block:: python
_ = stock['macd']
# or
stock.get('macd')
- Using get item to access the indicators. The item name following the
pattern: ``{columnName_window_statistics}``.
Some statistics/indicators has their short cut. See examples below:
.. code-block:: python
# volume delta against previous day
stock['volume_delta']
# open delta against next 2 day
stock['open_2_d']
# open price change (in percent) between today and the day before yesterday
# 'r' stands for rate.
stock['open_-2_r']
# CR indicator, including 5, 10, 20 days moving average
stock['cr']
stock['cr-ma1']
stock['cr-ma2']
stock['cr-ma3']
# volume max of three days ago, yesterday and two days later
stock['volume_-3,2,-1_max']
# volume min between 3 days ago and tomorrow
stock['volume_-3~1_min']
# KDJ, default to 9 days
stock['kdjk']
stock['kdjd']
stock['kdjj']
# three days KDJK cross up 3 days KDJD
stock['kdj_3_xu_kdjd_3']
# 2 days simple moving average on open price
stock['open_2_sma']
# MACD
stock['macd']
# MACD signal line
stock['macds']
# MACD histogram
stock['macdh']
# bolling, including upper band and lower band
stock['boll']
stock['boll_ub']
stock['boll_lb']
# close price less than 10.0 in 5 days count
stock['close_10.0_le_5_c']
# CR MA2 cross up CR MA1 in 20 days count
stock['cr-ma2_xu_cr-ma1_20_c']
# 6 days RSI
stock['rsi_6']
# 12 days RSI
stock['rsi_12']
To file issue, please visit:
https://github.com/jealous/stockstats
Contact author:
- Cedric Zhuang <jealous@163.com>
.. _BSD: LICENSE.txt
.. _test.py: test.py
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
stockstats-0.1.4.zip
(15.9 kB
view hashes)