Source code for pandas_ta.volume.pvi

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

[docs]def pvi(close, volume, length=None, initial=None, offset=None, **kwargs): """Indicator: Positive Volume Index (PVI)""" # Validate arguments length = int(length) if length and length > 0 else 1 # min_periods = int(kwargs["min_periods"]) if "min_periods" in kwargs and kwargs["min_periods"] is not None else length initial = int(initial) if initial and initial > 0 else 1000 close = verify_series(close, length) volume = verify_series(volume, length) offset = get_offset(offset) if close is None or volume is None: return # Calculate Result signed_volume = signed_series(volume, 1) pvi = roc(close=close, length=length) * signed_volume[signed_volume > 0].abs() pvi.fillna(0, inplace=True) pvi.iloc[0] = initial pvi = pvi.cumsum() # Offset if offset != 0: pvi = pvi.shift(offset) # Handle fills if "fillna" in kwargs: pvi.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: pvi.fillna(method=kwargs["fill_method"], inplace=True) # Name and Categorize it = f"PVI_{length}" pvi.category = "volume" return pvi
pvi.__doc__ = \ """Positive Volume Index (PVI) The Positive Volume Index is a cumulative indicator that uses volume change in an attempt to identify where smart money is active. Used in conjunction with NVI. Sources: Calculation: Default Inputs: length=1, initial=1000 ROC = Rate of Change roc = ROC(close, length) signed_volume = signed_series(volume, initial=1) pvi = signed_volume[signed_volume > 0].abs() * roc_ pvi.fillna(0, inplace=True) pvi.iloc[0]= initial pvi = pvi.cumsum() Args: close (pd.Series): Series of 'close's volume (pd.Series): Series of 'volume's length (int): The short period. Default: 13 initial (int): The short period. Default: 1000 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. """