# -*- coding: utf-8 -*-
from pandas import DataFrame
from pandas_ta.utils import get_offset, verify_series
[docs]def donchian(high, low, lower_length=None, upper_length=None, offset=None, **kwargs):
"""Indicator: Donchian Channels (DC)"""
# Validate arguments
lower_length = int(lower_length) if lower_length and lower_length > 0 else 20
upper_length = int(upper_length) if upper_length and upper_length > 0 else 20
lower_min_periods = int(kwargs["lower_min_periods"]) if "lower_min_periods" in kwargs and kwargs["lower_min_periods"] is not None else lower_length
upper_min_periods = int(kwargs["upper_min_periods"]) if "upper_min_periods" in kwargs and kwargs["upper_min_periods"] is not None else upper_length
_length = max(lower_length, lower_min_periods, upper_length, upper_min_periods)
high = verify_series(high, _length)
low = verify_series(low, _length)
offset = get_offset(offset)
if high is None or low is None: return
# Calculate Result
lower = low.rolling(lower_length, min_periods=lower_min_periods).min()
upper = high.rolling(upper_length, min_periods=upper_min_periods).max()
mid = 0.5 * (lower + upper)
# Handle fills
if "fillna" in kwargs:
lower.fillna(kwargs["fillna"], inplace=True)
mid.fillna(kwargs["fillna"], inplace=True)
upper.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
lower.fillna(method=kwargs["fill_method"], inplace=True)
mid.fillna(method=kwargs["fill_method"], inplace=True)
upper.fillna(method=kwargs["fill_method"], inplace=True)
# Offset
if offset != 0:
lower = lower.shift(offset)
mid = mid.shift(offset)
upper = upper.shift(offset)
# Name and Categorize it
lower.name = f"DCL_{lower_length}_{upper_length}"
mid.name = f"DCM_{lower_length}_{upper_length}"
upper.name = f"DCU_{lower_length}_{upper_length}"
mid.category = upper.category = lower.category = "volatility"
# Prepare DataFrame to return
data = {lower.name: lower, mid.name: mid, upper.name: upper}
dcdf = DataFrame(data)
dcdf.name = f"DC_{lower_length}_{upper_length}"
dcdf.category = mid.category
return dcdf
donchian.__doc__ = \
"""Donchian Channels (DC)
Donchian Channels are used to measure volatility, similar to
Bollinger Bands and Keltner Channels.
Sources:
https://www.tradingview.com/wiki/Donchian_Channels_(DC)
Calculation:
Default Inputs:
lower_length=upper_length=20
LOWER = low.rolling(lower_length).min()
UPPER = high.rolling(upper_length).max()
MID = 0.5 * (LOWER + UPPER)
Args:
high (pd.Series): Series of 'high's
low (pd.Series): Series of 'low's
lower_length (int): The short period. Default: 20
upper_length (int): The short period. Default: 20
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.DataFrame: lower, mid, upper columns.
"""