Raw weather-CCI evidence is weak
Pearson, Spearman, lag and seasonal t-tests do not support a direct linear CCI story.
Retail is more predictable
Random Forest reaches strong retail performance once weather and macro controls are combined.
Macro context dominates
Inflation and unemployment carry major signal; weather contributes but is not the sole driver.
Claims remain associative
The project does not claim causality; it builds a transparent predictive and statistical analysis.
Future Work
Time-series validation
Use rolling-origin or blocked time splits instead of shuffled K-Fold.
Sub-national data
Add city or regional retail proxies to reduce country aggregation bias.
Causal design
Use event-study or instrumental-variable logic before making causal claims.
Thank you for exploring the project
Weather may not move confidence in a simple straight line, but the full pipeline shows how data science can separate weak direct evidence from stronger predictive structure.
View on GitHub