The objective of the project was to predict whether customers would accept a coupon based on various driving scenarios through data analysis and visualization techniques. In the project, Python served as the programming language, with Seaborn and Matplotlib utilized for data visualization, Pandas for data manipulation and analysis, and NumPy for numerical computations, enhancing the ability to analyze and present data insights effectively. A Jupyter Notebook was created and used to capture all steps and analysis.

Project Notebook

Foreseeable next steps for additional investigation could be to compare age groups and their probability to accept coupons, or compare age groups and time of rides to find out the likelihood of accepting coupons.