Pandas 基础

Lesson Overview

In "Python Quant Trading Lab" → "Python 金融数据处理", this lesson "Pandas 基础" builds knowledge you can apply immediately.

Pandas的Series是带索引的一列，DataFrame组织多列；按标签与按位置选择不同。时间索引须排序且唯一，不能用行号冒充交易时间。 读CSV→查看列名/类型/行数→解析UTC→排序去重→设置索引→只选择需要列；保留原始文件和清洗报告。 本课作业：运行pandas_lab.py，另用三行close=100/102/101写出行数、首个收益缺失原因和最后SMA2。

Core Concepts

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

• ▸Pandas的Series是带索引的一列，DataFrame组织多列；按标签与按位置选择不同。时间索引须排序且唯一，不能用行号冒充交易时间。
• ▸读CSV→查看列名/类型/行数→解析UTC→排序去重→设置索引→只选择需要列；保留原始文件和清洗报告。
• ▸本课作业：运行pandas_lab.py，另用三行close=100/102/101写出行数、首个收益缺失原因和最后SMA2。

Practical Application

After studying, complete the companion practice lesson 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 "Python 金融数据处理"—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 Pandas 基础 on your own.