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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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Data-driven stock quant investment with Python Part 1

DeepingSauce

입문

초급

중급이상

판다스

Pandas

Investment

Quant

Orientation

System Trading Definition & Basic Composition

Pandas Core Data Types: Series and DataFrame

Weapon for Dissecting Data, Pandas API

Analyzing by Grouping, Split - Apply - Combine

How to combine multiple datasets?

Communicative Power Far Exceeding Numbers, Visualization

Apply learnings directly in the Final project! Financial statement based backtesting

Summary & Wrap-up