IITM sem 1, Python Assignment 2, Problem 7

# solution of Pruthwira Lenka for Python Assignment 2 > Problem 7
# in 1st trimester of IIT Madras Web MTech (Industrial AI) 2025
def simulate_sales(df: pd.DataFrame, n: int) -> list:
    """
    Simulate n future sales based on average price change.
    """
    np.random.seed(0)
    try:
        if 'OrderDate' in df.columns:
            last_price = df.sort_values(by='OrderDate')['Price'].iloc[-1]
            price_changes = df['Price'].diff()
        else:
            last_price = df['Price'].iloc[-1]
    except (IndexError, KeyError):
        last_price = 0.0

    if len(df) > 1:
        if 'OrderDate' in df.columns:
            price_changes = df.sort_values(by='OrderDate')['Price'].diff()
        else:
            price_changes = df['Price'].diff()

        mean_change = price_changes.mean()
        std_change = price_changes.std()

        if pd.isna(mean_change) or pd.isna(std_change) or std_change == 0:
            sim_mean = 0.0
            sim_std = 0.0
        else:
            sim_mean = mean_change
            sim_std = std_change
    else:
        sim_mean = 0.0
        sim_std = 5.0

    simulated_data = []
    current_price = last_price

    for _ in range(n):
        price_drift = np.random.normal(loc=sim_mean, scale=sim_std)
        current_price += price_drift

        quantity = np.random.randint(low=1, high=6)

        simulated_data.append((current_price, quantity))

    return simulated_data