/tapy

Technical Indicators for the Pandas' Dataframes

Primary LanguagePythonMIT LicenseMIT

tapy

Technical Indicators for the Pandas' Dataframes

Documentation: https://pandastechindicators.readthedocs.io/en/latest/

Installation

pip install -U tapy

Example

>>> import pandas as pd
>>> from tapy import Indicators
>>> df = pd.read_csv('EURUSD60.csv')
>>> i= Indicators(df)
>>> i.accelerator_oscillator(column_name='AC')
>>> i.sma()
>>> df = i.df
>>> df.tail()
            Date   Time     Open     High      Low    Close  Volume        AC       sma
3723  2019.09.20  16:00  1.10022  1.10105  1.10010  1.10070    2888 -0.001155  1.101296
3724  2019.09.20  17:00  1.10068  1.10193  1.10054  1.10184    6116 -0.000820  1.101158
3725  2019.09.20  18:00  1.10186  1.10194  1.10095  1.10144    3757 -0.000400  1.101056
3726  2019.09.20  19:00  1.10146  1.10215  1.10121  1.10188    3069  0.000022  1.101216
3727  2019.09.20  20:00  1.10184  1.10215  1.10147  1.10167    1224  0.000388  1.101506

Available Indicators

  1. Accelerator Oscillator (AC)
  2. Accumulation/Distribution (A/D)
  3. Alligator
  4. Average True Range (ATR)
  5. Awesome Oscillator (AO)
  6. Bears Power
  7. Bollinger Bands
  8. Bulls Power
  9. Commodity Channel Index (CCI)
  10. DeMarker (DeM)
  11. Exponential Moving Average (EMA)
  12. Force Index (FRC)
  13. Fractals
  14. Gator Oscillator
  15. Ichimoku Kinko Hyo
  16. Market Facilitation Index (BW MFI)
  17. Momentum
  18. Money Flow Index (MFI)
  19. Moving Average Convergence/Divergence (MACD)
  20. Simple Moving Average (SMA)
  21. Smoothed Moving Average (SMMA)