Unveiling livestock trade trends: A beginner's guide to generative AI-powered visualization

Abstract

This tutorial, rooted in the context of livestock research, is designed to assist novice or non-programmers in visualizing trends in livestock exports between the US and Japan using Python and generative AI systems such as Microsoft's Copilot and Google's Gemini. The analysis of these trends plays a pivotal role in optimizing livestock production. The tutorial offers a thorough guide on preparing data using reliable federal datasets, generating Python code, and tackling potential issues such as overlapping data points. It effectively simplifies complex tasks into manageable steps and includes Python code in the appendices for easy reference. By enabling researchers to extract insights and make predictions from livestock data, this tutorial addresses a significant void in the existing literature. This innovative approach has the potential to transform the way researchers engage with and interpret livestock data, thereby making a substantial contribution to the field.