How to use Pandas for financial data analysis

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This is the edited live video from the LLM Application Experience Sharing Session with knowledge sharer Kang Byung-jin :)

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Datarian's Pandas basic course with over 10,000 cumulative students and rich online/offline lecture experience. Learn Pandas, Python's representative data analysis library, systematically with official documentation. You can also improve your proficiency by learning theories and solving problems in parallel.

This course starts very easily from ETF basics, stock&bond&gold basics, and economic basics, covering everything from the fundamental concepts of monthly dividend ETFs to advanced strategies and real-world market application. Investing without prior learning is like crossing a bridge precariously while blindfolded. Please be sure to learn beforehand before investing.

This course is a course to learn data analysis methods using the Pandas library. You will learn practical application methods by learning the library and analyzing sample data in parallel.

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

In this class, you will learn about the principles and methods of analyzing and processing various types of financial data using Python's Pandas library, apply them to situations you may encounter in the real world, and ultimately learn how to implement backtesting based on financial statement data (based on Kang Hwan-guk's book, "You Can Do Quant Investment"). As a result, you can break away from being a "passive investor" who simply follows what others say without verifying or basing the investment logic, and become a "self-directed and active investor" who can freely extract various elements necessary for strategy implementation from data and quantitatively analyze them using Python and Pandas.

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