Source code for pandas_ta.trend.qstick

# -*- coding: utf-8 -*-
from pandas_ta.overlap import dema, ema, hma, rma, sma
from pandas_ta.utils import get_offset, non_zero_range, verify_series

[docs]def qstick(open_, close, length=None, offset=None, **kwargs): """Indicator: Q Stick""" # Validate Arguments length = int(length) if length and length > 0 else 10 ma = kwargs.pop("ma", "sma") open_ = verify_series(open_, length) close = verify_series(close, length) offset = get_offset(offset) if open_ is None or close is None: return # Calculate Result diff = non_zero_range(close, open_) if ma == "dema": qstick = dema(diff, length=length, **kwargs) elif ma == "ema": qstick = ema(diff, length=length, **kwargs) elif ma == "hma": qstick = hma(diff, length=length) elif ma == "rma": qstick = rma(diff, length=length) else: # "sma" qstick = sma(diff, length=length) # Offset if offset != 0: qstick = qstick.shift(offset) # Handle fills if "fillna" in kwargs: qstick.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: qstick.fillna(method=kwargs["fill_method"], inplace=True) # Name and Categorize it = f"QS_{length}" qstick.category = "trend" return qstick
qstick.__doc__ = \ """Q Stick The Q Stick indicator, developed by Tushar Chande, attempts to quantify and identify trends in candlestick charts. Sources: Calculation: Default Inputs: length=10 xMA is one of: sma (default), dema, ema, hma, rma qstick = xMA(close - open, length) Args: open (pd.Series): Series of 'open's close (pd.Series): Series of 'close's length (int): It's period. Default: 1 ma (str): The type of moving average to use. Default: None, which is 'sma' 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. """