Maximizing Revenue For Drivers.
This Jupyter Notebook explores statistical techniques to maximize revenue by analyzing key factors influencing business performance. It includes data preprocessing, exploratory data analysis (EDA), and statistical modeling to uncover insights that drive revenue growth. Using Python libraries like Pandas, NumPy, Matplotlib, Seaborn, and SciPy, the notebook provides a structured approach to identifying trends, optimizing strategies, and making data-driven decisions. Whether you're looking to enhance pricing strategies, understand customer behavior, or improve operational efficiency, this project offers valuable insights to boost revenue. Contributions and improvements are welcome!
For the Dataset, you can refer to Kaggle or Data.gov.
URL: https://data.cityofnewyork.us/api/views/4b4i-vvec/rows.csv?accessType=DOWNLOAD