In this project my role is acting as Chief Data Strategist for a rideshare company. In this role, I explore and analyze the rideshare data to contribute data-backed guidance on new opportunities for market differentiation.
The provided data includes information about every active driver and historic ride, including details like city, driver count, individual fares, and city type.
I. Create a Bubble Plot that showcases the relationship between four key variables:
- Average Fare ($) Per City
- Total Number of Rides Per City
- Total Number of Drivers Per City
- City Type (Urban, Suburban, Rural)
See RideSharePlot.png
II. Create three pie charts showing:
- % of Total Fares by City Type - TotalFares_CityType.png
- % of Total Rides by City Type - TotalRides_CityType.png
- % of Total Drivers by City Type - TotalDrivers_CityType.png
For this project I implemented:
- Pandas Library with the Jupyter Notebook to explore, merge, and analyze data
- Import Matplotlib library to visualize project objectives
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