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Pyber Charts

This is a visualization project where I use matplotlib library to explore the market opportunity for an imaginary ride-sharing company "Pyber". The analysis is based on company's dataset that contains information about every active driver and historic rides, including details like city, driver count, individual fares, and city type.

Findings

  1. The following chart shows that despite most revenue being generated in urban areas, rural and suburban areas, too, have significant demand for ride-sharing services that should not be ignored.

TotalFaresChart

  1. The next two charts show a disproportionate ratio between rural rides and number of drivers operating there. This suggests that by hiring more rural drivers the company can not only increase the demand but also lower the fares since rural drivers will cost less than drivers operating in urban and suburban areas.

TotalRidesChart TotalDriversChart

  1. Clearly, rural and suburban rides are an opportunity emerging companies like Pyber should tap into. The figure below demostrates that rural and suburban areas are largely underserved having the least number drivers and yet the highest ride-sharing fares.

BubblePlot_RideSharingData

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Visualizations using matplotlib library

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