Vinod Chugani works with Pandas:
In the realm of data analysis, SQL stands as a mighty tool, renowned for its robust capabilities in managing and querying databases. However, Python’s pandas library brings SQL-like functionalities to the fingertips of analysts and data scientists, enabling sophisticated data manipulation and analysis without the need for a traditional SQL database. This exploration delves into applying SQL-like functions within Python to dissect and understand data, using the Ames Housing dataset as your canvas. The Ames Housing dataset, a comprehensive compilation of residential property sales in Ames, Iowa, from 2006 to 2010, serves as an ideal dataset for this exploration, offering a rich variety of features to analyze and derive insights from.
Click through for examples of how to use the query() function in conjunction with other Pandas functionality to answer questions of the data.