Optimized Large-Scale Dataset with making selections for data | python

This project demonstrates the development of an optimized, interactive command-line analytics application designed to process large-scale, multi-city transport datasets. Built entirely in Python, the solution focuses on programmatic efficiency, scalable data manipulation, and programming practices. Engineering & Analytical Technicalities: use pandas to read data from excel CSV files and put them in data frames suitable to get info from them, clean them if needed and extract results and KPIs from the data, with the help of Numpy library