import pandas as pd

def calculate_macd(prices, fast_length=12, slow_length=26, signal_length=9):
    """
    Calculates the Moving Average Convergence Divergence (MACD) along with the Signal line.
    
    Parameters:
    - prices (pd.Series): A pandas Series containing the stock's closing prices.
    - fast_length (int): The length of the fast EMA. Defaults to 12.
    - slow_length (int): The length of the slow EMA. Defaults to 26.
    - signal_length (int): The length of the signal line. Defaults to 9.
    
    Returns:
    - pd.DataFrame: A DataFrame containing the MACD, Signal line, and MACD Histogram.
    """
    # Calculate the Fast and Slow EMAs
    ema_fast = prices.ewm(span=fast_length, adjust=False).mean()
    ema_slow = prices.ewm(span=slow_length, adjust=False).mean()
    
    # Calculate the MACD and Signal line
    macd = ema_fast - ema_slow
    signal_line = macd.ewm(span=signal_length, adjust=False).mean()
    macd_histogram = macd - signal_line
    
    macd_df = pd.DataFrame(data={
        'MACD': macd,
        'Signal_Line': signal_line,
        'MACD_Histogram': macd_histogram
    })
    
    return macd_df

if __name__ == "__main__":
    # Example usage
    data = {'Close': [22, 24, 23, 25, 26, 28, 27, 29, 30, 32, 31, 33]}
    prices = pd.Series(data['Close'])
    
    # User-defined parameters for MACD
    fast_length = 12
    slow_length = 26
    signal_length = 9
    
    # Calculate MACD
    macd_df = calculate_macd(prices, fast_length, slow_length, signal_length)
    
    print(macd_df)