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.
"""