Adding Rows and Columns to DataFrames – University of Illinois Lecture

This is a hands-on lesson from the University of Illinois' "Data Science Discovery" lecture series, focusing on one of the most fundamental and commonly used operations in data analysis—adding rows and columns to DataFrames. The video is moderate in length, with clear pacing, making it suitable for learners who are just getting started with Python data processing. The key highlight is that the instructor does not stop at simply calling functions. Instead, using real data scenarios, they demonstrate how to flexibly apply the Pandas library to expand existing tables with new dimensions, while also addressing easy-to-miss details such as index alignment and data consistency. Whether you need to combine multiple records or generate new fields by calculating from existing columns, this lesson will help you build a more solid mindset for working with DataFrames. Before watching, it is recommended that you have a basic understanding of Pandas' core data structures and have a Jupyter Notebook ready to follow along hands-on. When you encounter code examples, pausing, typing them out yourself, and observing the output will be more effective than just listening. If you are preparing for a data science course assignment or project, this lesson can help you avoid a lot of unnecessary detours.