Prompt Engineering for Data: Basic Data Manipulation Using Generative AI

“With DataFrames in pandas you can filter aggregate join pivot and manipulate data efficiently. These operations enable data analysts and scientists to work with datasets for various data-driven tasks. Prompt engineering tools are adept at generating code to make these tasks simple.

You will start this course by exploring the configurations you can apply to read in your data. You ll present your problem statement to ChatGPT and explore the use of arguments to configure various aspects of the file reading such as defining column names and specifying which columns to include in the DataFrame. Additionally you will learn how to read data from different sources including JSON Excel and the Clipboard and write files out to these different formats.

Next you ll delve into common DataFrame operations examine statistics on your data rename columns iterate over and sort your data. As you encounter issues you will turn to prompt engineering to help debug them.

Finally you ll explore how you can enhance your data using computed columns. You ll harness the power of two essential functions apply and map to transform your records. You will also focus on utilizing generative AI for code generation and you will employ the chAIn-of-thought prompting method to guide the chatbot in generating code effectively.”