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Common financial technical indicators implemented in Pandas.

Project description

FinTA (Financial Technical Analysis)

License: LGPL v3 PyPI Build Status

Common financial technical indicators implemented in Pandas.

This is work in progress, bugs are expected and results of indicators might not be correct.

Supported indicators:

['SMA', 'SMM', 'EMA', 'DEMA', 'TEMA', 'TRIMA', 'TRIX', 'AMA', 'LWMA', 'VAMA', 'VIDYA', 'ER', 'KAMA', 'ZLEMA', 'WMA', 'HMA', 'VWAP', 'SMMA', 'ALMA', 'MAMA', 'FRAMA', 'MACD', 'PPO', 'VW_MACD', 'MOM', 'ROC', 'RSI', 'IFT_RSI', 'SWI', 'TR', 'ATR', 'SAR', 'BBANDS', 'BBWIDTH', 'PERCENT_B', 'KC', 'DO', 'DMI', 'ADX', 'PIVOTS', 'STOCH', 'STOCHD', 'STOCHRSI', 'WILLIAMS', 'UO', 'AO', 'MI', 'VORTEX', 'KST', 'TSI', 'TP', 'ADL', 'CHAIKIN', 'MFI', 'OBV', 'WOBV', 'VZO', 'EFI', 'CFI', 'EBBP', 'EMV', 'CCI', 'COPP', 'BASP', 'BASPN', 'CMO', 'CHANDELIER', 'QSTICK', 'TMF', 'WTO', 'FISH', 'ICHIMOKU', 'APZ', 'VR', 'SQZMI', 'VPT', 'FVE', 'VFI']

Dependencies:

  • python (3.4+)
  • pandas (0.21.1+)

TA class is very well documented and there should be no trouble exploring it and using with your data. Each class method expects proper ohlc data as input.

Install:

pip install finta

or latest development version:

pip install git+git://github.com/peerchemist/finta.git

Import

from finta import TA

Prepare data to use with finta:

finta expects properly formated ohlc DataFrame, with column names in lowercase: ["open", "high", "low", close"] and ["volume"] for indicators that expect ohlcv input.

To prepare the DataFrame into ohlc format you can do something as following:

standardize column names of your source

df.columns = ["date", 'close', 'volume']

set index on the date column, which is requirement to sort it by time periods

df.set_index('date', inplace=True)

select only price column, resample by time period and return daily ohlc (you can choose different time period)

ohlc = df["close"].resample("24h").ohlc()

ohlc() method applied on the Series above will automatically format the dataframe in format expected by the library so resulting ohlc Series is ready to use.


Examples:

will return Pandas Series object with the Simple moving average for 42 periods

TA.SMA(ohlc, 42)

will return Pandas Series object with "Awesome oscillator" values

TA.AO(ohlc)

expects ["volume"] column as input

TA.OBV(ohlc)

will return Series with Bollinger Bands columns [BB_UPPER, BB_LOWER]

TA.BBANDS(ohlc)

will return Series with calculated BBANDS values but will use KAMA instead of MA for calculation, other types of Moving Averages are allowed as well.

TA.BBANDS(ohlc, TA.KAMA(ohlc, 20))


I welcome pull requests with new indicators or fixes for existing ones. Please submit only indicators that belong in public domain and are royalty free.

Contributing

  1. Fork it (https://github.com/peerchemist/finta/fork)
  2. Study how it's implemented.
  3. Create your feature branch (git checkout -b my-new-feature).
  4. Commit your changes (git commit -am 'Add some feature').
  5. Push to the branch (git push origin my-new-feature).
  6. Create a new Pull Request.

Donate

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Peercoin: PRn448Km1ZJ2BhdPQfiSS3q4Af2vkjwwvH

Project details


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