AbhayRautela213/Exploring-the-Factors-behind-COVID-19-Surge-Predictive-Modeling-and-Analysis. ? reverse-engineered prompt

Build me a clean Jupyter notebook that analyzes what factors are linked to COVID 19 case surges in the Delhi NCR region, using the Excel dataset in the repo. I want it to load the data, do basic cleaning, explore the relationships between weather, air quality, demographic, medical history, and lifestyle factors, then train a prediction model for case counts.

Please use a LightGBM based approach like the project description says, and show the results with clear metrics such as MAE, MSE, and R squared. Add simple visualizations so it is easy to see which factors matter most, and make the notebook readable for someone reviewing it for a research paper. If anything about the dataset needs clarification, inspect the files and infer the column meanings as best you can, and look up current docs online if you need to. At the end, include a short summary of the key findings, especially the impact of temperature.