Python Quantitative Finance & Stock Analysis Course (Pandas, NumPy, SciPy) 🐍 - Python OOP for Finance: Building a Stock Analysis Class to Manage Individual Securities | Part 10 🛠️

@MattMacarty ## 🐍 Python OOP for Finance: Building a Stock Analysis Class to Manage Individual Securities | Part 10 Welcome to **Part 10**—the start of **Section 2** in the Python Stock Analysis Course! We are shifting focus from macro-level analysis (multiple stocks) to building a robust, reusable framework for **individual security analysis**. This video introduces **Object-Oriented Programming (OOP)** by teaching you how to build a `Stock` class in Python. This class acts as a container for all the data and methods related to a single stock (e.g., Apple, Microsoft), streamlining future analysis and making your code much cleaner. You will learn how to write a flexible `get_data` method that can either load data from a local CSV file or perform a fresh API download. ### 🎯 Key Learning Outcomes: 1. **Object-Oriented Design:** Transition to **OOP** by defining the foundational `Stock` class. 2. **Class Initialization:** Set up the `__init__` method to accept key properties like **ticker symbol**, **API key**, start **date**, and a **folder path** for stored data. 3. **Flexible Data Loading:** Create the powerful **`get_data` method** with conditional logic to prioritize loading existing data from a local CSV file before falling back to a fresh API call (using the EOD Historical Data API) if the file is not found. 4. **Data Cleaning:** Implement data formatting steps inside the class, including converting the index to a **DatetimeIndex** and rounding prices to two decimal places. ### ⏱️ Video Chapters (Jump Ahead!): 0:00 - Introduction & Transition to **Individual Security Analysis** 0:33 - Setting up Imports and Defining the Default Time Period 1:22 - Defining the **`Stock` Class** 1:32 - Initializing the Class (`__init__`) with Symbol, Key, Date, and Folder 2:37 - **Writing the `get_data` Method** (The core function for data acquisition) 3:01 - **Logic: Check for Data in Local Folder (CSV)** 4:44 - **Logic: Downloading Data via EOD API** (If local file is missing) 5:14 - Setting the Datetime Index and Cleaning the DataFrame 5:45 - Returning the Data and Storing it as a Class Property 6:03 - Testing the Initialization and Data Retrieval 6:50 - Preview of Part 11: Adding more **Data Transformations** to the class ### 🔗 Course Series & Resources: * **Part 9 (Stock Screener):** [https://youtu.be/oVKevwdOl4A](https://youtu.be/oVKevwdOl4A) * **Get the Code:** https://github.com/mjmacarty/python-stock-analysis ***Disclaimer: This video is for educational purposes only. The information provided should not be construed as investment advice. *** \#PythonOOP \#ObjectOrientedProgramming \#PythonClass \#StockAnalysisClass \#PythonForFinance \#EODHistoricalData \#DataAcquisition \#Part10