Introduction to Donchian Channel

import time
import threading
from datetime import datetime
from typing import Dict, Optional
import pandas as pd
import warnings
warnings.filterwarnings("ignore")

from ibapi.client import EClient
from ibapi.wrapper import EWrapper
from ibapi.contract import Contract
from ibapi.order import Order
from ibapi.common import BarData

def donchian_channel(df: pd.DataFrame, period: int = 30) -> pd.DataFrame:
    """
    Calculate the Donchian Channel for a given DataFrame.

    The Donchian Channel is a trend-following indicator that plots the highest high and 
    the lowest low over a specified period, along with a middle line that is the average 
    of the upper and lower bands. This indicator is often used to identify breakouts 
    and determine potential trading signals.

    Parameters
    ----------
    df : pandas.DataFrame
        A DataFrame containing at least the following columns:
        - 'high': The high prices of the asset.
        - 'low': The low prices of the asset.
        - 'close': The closing prices of the asset (not used directly in calculations but 
          generally present in the data).
          
    period : int, optional
        The number of periods to calculate the channel. Default is 30.
        This period determines the look-back window for the highest high 
        and the lowest low.

    Returns
    -------
    pandas.DataFrame
        The original DataFrame with three additional columns:
        - 'upper': The upper band of the Donchian Channel (highest high over the period).
        - 'lower': The lower band of the Donchian Channel (lowest low over the period).
        - 'mid': The middle line, which is the average of the upper and lower bands.

    Examples
    --------
    >>> data = {
    ...     'high': [10, 12, 13, 14, 15, 13, 11, 10, 12, 14],
    ...     'low': [8, 7, 6, 5, 8, 7, 6, 5, 6, 7],
    ...     'close': [9, 10, 12, 13, 14, 12, 10, 9, 11, 13]
    ... }
    >>> df = pd.DataFrame(data)
    >>> donchian_channel(df, period=5)
       high  low  close  upper  lower   mid
    0    10    8    9.0    NaN    NaN   NaN
    1    12    7   10.0    NaN    NaN   NaN
    2    13    6   12.0    NaN    NaN   NaN
    3    14    5   13.0    NaN    NaN   NaN
    4    15    8   14.0   15.0    5.0  10.0
    5    13    7   12.0   15.0    5.0  10.0
    6    11    6   10.0   15.0    5.0  10.0
    7    10    5    9.0   15.0    5.0  10.0
    8    12    6   11.0   15.0    5.0  10.0
    9    14    7   13.0   14.0    5.0   9.5
    """
    # Calculate the upper band (highest high over the period)
    df["upper"] = df["high"].rolling(window=period).max()

    # Calculate the lower band (lowest low over the period)
    df["lower"] = df["low"].rolling(window=period).min()
    
    # Optional: Calculate the middle line (average of upper and lower bands)
    df["mid"] = (df["upper"] + df["lower"]) / 2
    
    return df

This is a third-party open-source library. It is not associated, supported, or managed by Interactive Brokers, completely independent. And if you’re using Pandas with your IB API or your trading apps, Interactive Brokers cannot help or offer support with Pandas specifically.

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