Python for Data Analysis
本课程教授如何使用Python进行商业数据处理与分析。内容涵盖Python基础语法、NumPy数值计算、Pandas数据处理、数据清洗与预处理、数据合并与重塑、分组聚合与透视表、时间序列处理等核心技能。课程采用项目驱动式教学，结合电商、金融、营销等真实商业数据集，培养学生从数据获取、清洗、探索到分析报告输出的完整数据分析能力，为机器学习和数据可视化课程打下编程基础。
This course teaches data processing and analysis using Python in business contexts. Topics include Python fundamentals, NumPy numerical computing, Pandas data manipulation, data cleaning and preprocessing, data merging and reshaping, groupby and pivot tables, and time series handling. Using project-based learning with real business datasets from e-commerce, finance, and marketing, students develop end-to-end data analysis skills from data acquisition and cleaning to exploration and reporting.
选取某电商平台用户行为日志数据集（包含浏览、加购、收藏、购买等行为数据），使用Pandas进行数据清洗与预处理，分析用户活跃时段、转化漏斗、复购率、用户分层等关键指标，探究用户购买行为的影响因素，识别高价值用户特征，最终输出包含数据洞察和运营建议的完整分析报告，并提交可复现的Python代码。
Analyze an e-commerce user behavior log dataset containing browsing, carting, favoriting, and purchase actions. Use Pandas for data cleaning and preprocessing. Analyze key metrics including active time periods, conversion funnels, repurchase rates, and user segmentation. Explore factors influencing purchase behavior and identify high-value user characteristics. Submit a complete analysis report with insights and operational recommendations, along with reproducible Python code.