Python Quantitative Finance & Stock Analysis Course (Pandas, NumPy, SciPy) 🐍 - Python Pandas: Filter Time Series Data by Option Expiration & Low Volatility Duration | Part 13 📅

@MattMacarty ## 🐍 Python Pandas: Filter Time Series Data by Option Expiration & Low Volatility Duration | Part 13 Welcome to **Part 13** of the Python Stock Analysis Course! This video concludes Section 2 on Individual Security Analysis by adding advanced data filtering capabilities to our custom `Stock` class. You will learn how to create two methods that slice the stock's data, allowing you to focus your analysis only on days relevant to high-impact financial events or market conditions. ### 🎯 Key Learning Outcomes: 1. **Option Expiration Filter:** Implement logic to create a data mask that isolates the **Third Friday** of every month, which corresponds to the main monthly **Option Expiration** date. 2. **Date Filtering with Pandas:** Utilize **NumPy's `np.where`** and **Pandas' DatetimeIndex properties** (day and weekday) to accurately define the expiration mask. 3. **Low Volatility Duration:** Write a non-vectorized, iterative method to track the number of **consecutive days** since the last **Two Standard Deviation (2-