数据清洗练习

Lesson Overview

In "Trading Data Analysis" → "数据清洗", this lesson "数据清洗练习" builds knowledge you can apply immediately.

数据清洗交付必须保留原始与清洗版本，能追溯每条被排除记录。计数对齐比“已经无缺失”更重要。 运行research_lab的数据检查→另建异常表→核输入=有效+重复+隔离→给两条人工复核建议。 本课作业：提交OHLCV清洗240/1/3计数，再对交易脏表记录重复键规则；为什么不能按收益金额去重？

Core Concepts

These points align with the video walkthrough—take notes as you watch.

• ▸数据清洗交付必须保留原始与清洗版本，能追溯每条被排除记录。计数对齐比“已经无缺失”更重要。
• ▸运行research_lab的数据检查→另建异常表→核输入=有效+重复+隔离→给两条人工复核建议。
• ▸本课作业：提交OHLCV清洗240/1/3计数，再对交易脏表记录重复键规则；为什么不能按收益金额去重？

Practical Application

After studying, complete the practice tasks below to move from understanding to doing.

• ▸Follow along in Jupyter or VS Code
• ▸Log how parameter changes affect backtest results
• ▸Submit a reproducible analysis notebook

FAQ

• ▸Q: How does this lesson fit the course? A: Part of "数据清洗"—follow the curriculum order.
• ▸Q: What do I need? A: Demo account and notes; quant lessons need a Python environment.
• ▸Q: How do I know I've mastered it? A: Pass the quiz and explain three key points of 数据清洗练习 on your own.