Handling Data: Data Models and Wrangling

This lecture covers the fundamentals of handling data, including data models, sources, and wrangling. It delves into various data types, such as CSV files, PDFs, and SQL dumps, and the challenges of dealing with missing and inconsistent data. The instructor discusses the importance of data wrangling, which involves extracting, standardizing, and cleaning raw data to prepare it for analysis. Tools like Requests, Scrapy, and Beautiful Soup are highlighted for data manipulation. The lecture emphasizes the significance of understanding data problems, such as missing values and incorrect data, and provides insights into the process of diagnosing and transforming data effectively.