Seeds of fortune – unraveling the correlation between weather patterns and John Deere’s stock performance
In this section, you’ll learn how to use weather data and John Deere’s stock data to create a “weather score” to understand how crop growth conditions affect stock performance. The process consists of five stages: preparing the data, extracting information with Python, and importing it into Power BI.
We’ll showcase future possibilities by integrating OpenAI with Power BI to generate insights, such as correlating weather intensity with stock price fluctuations or creating heatmaps to capture weather patterns and corresponding stock price changes.
Power BI visualization
Important note
Please note that this guide is based on the assumption that you’ve stored your weather and John Deere stock data in a CSV file, and that the weather data has already been transformed into a “weather score.”
Our journey...
