Source code for pandas_ta.volume.obv

# -*- coding: utf-8 -*-
from pandas_ta import Imports
from pandas_ta.utils import get_offset, signed_series, verify_series


[docs]def obv(close, volume, talib=None, offset=None, **kwargs): """Indicator: On Balance Volume (OBV)""" # Validate arguments close = verify_series(close) volume = verify_series(volume) offset = get_offset(offset) mode_tal = bool(talib) if isinstance(talib, bool) else True # Calculate Result if Imports["talib"] and mode_tal: from talib import OBV obv = OBV(close, volume) else: signed_volume = signed_series(close, initial=1) * volume obv = signed_volume.cumsum() # Offset if offset != 0: obv = obv.shift(offset) # Handle fills if "fillna" in kwargs: obv.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: obv.fillna(method=kwargs["fill_method"], inplace=True) # Name and Categorize it obv.name = f"OBV" obv.category = "volume" return obv
obv.__doc__ = \ """On Balance Volume (OBV) On Balance Volume is a cumulative indicator to measure buying and selling pressure. Sources: https://www.tradingview.com/wiki/On_Balance_Volume_(OBV) https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/on-balance-volume-obv/ https://www.motivewave.com/studies/on_balance_volume.htm Calculation: signed_volume = signed_series(close, initial=1) * volume obv = signed_volume.cumsum() Args: close (pd.Series): Series of 'close's volume (pd.Series): Series of 'volume's talib (bool): If TA Lib is installed and talib is True, Returns the TA Lib version. Default: True offset (int): How many periods to offset the result. Default: 0 Kwargs: fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method Returns: pd.Series: New feature generated. """