Refactor stratification logic to ensure proper selection of indices by adding break statements for clarity and control flow.

had to designate a maliable target

printing some lens

more strat testing

the while loop broke things, doing a range instead

Testing some new logic around stratification

Implement vectorized calculations for salary, median, and ownership in app.py to enhance performance and memory efficiency. Refactor reassess_edge and stratification_function to minimize DataFrame copies and improve memory management. Update filtering logic to use boolean masks for better efficiency.

Refactor similarity score calculations in stratification_function to use quantiles instead of min/max thresholds, improving accuracy in target similarity score generation.

Add stratification sample range slider to app.py and update stratification_function to accept threshold parameters for improved player selection control.

Add stratification functionality and enhance portfolio handling in app.py