/pyber-analysis

Primary LanguageJupyter Notebook

pyber-analysis

Overview

This project analyzes trends in PyBer's rideshare services in urban, suburban, and rural city types in order to help Pyber to improve their services' accessibility and affordability in underserved neighborhoods.

Results

Average Fare per Ride & Fare per Driver -- [Link to chart]

There is a noticeable discrepancy between the three city types in regards to average fares per ride and fares per driver. In rural areas the average fare per ride is also roughly 10 dollars USD more expensive. Rural drivers on average are also earning more than three times that of urban drivers. There are also significantly fewer drivers serving rural cities and suburban cities compared to the urban cities. Urban cities are also the only city type where the average fare per driver is less than the average fare per ride. This means that most urban drivers are not receiving as many customers as their suburban and rural counterparts, because the market is oversaturated with too many drivers in urban centers.

If PyBer wishes to increase their accessibility and affordability to their customers in rural and suburban cities, it may be worth recruiting more drivers for these areas, and suggesting to some of their urban drivers to consider working in a rural or suburban environment instead. For urban drivers, it may be more lucrative for them to transfer to a rural or suburban area

Total Fare by City Type -- [Link to chart]

The chart linked above shows the total fares earned each week across a 4-month period from January 2019 through April 2019. Unsurprisingly, urban cities cumulatively earn the most, followed by suburban and then rural cities. For each city type, there does not appear to be too great of a change in the total fares collected each week during this time period, though urban cities may have increased slightly. A longer time period would be needed to judge if there are any significant trends over time.

What this chart makes clear is that urban cities conduct the most business by far, and that rural cities conduct the least. This means that if PyBer were to recruit more drivers to serve rural and suburban cities, care should be taken not to recruit too many, or the drivers may not be able to earn enough, and may decide to find other work instead.

Summary

There is a statement summarizing three business recommendations to the CEO for addressing any disparities among the city types.

Based on the results of the analysis, there are a few measures that PyBer could consider taking to address the disparities between the city types. First, because urban cities are oversaturated with too many drivers, and urban drivers' wages are low, it may be worth convincing some urban drivers to transfer to serving a rural or suburban city instead. Second, PyBer could also open up opportunities to recruit new drivers in suburban and rural areas. Having more drivers in these areas would both decrease the cost and provide more access to the service for passengers. Lastly, if PyBer is interested in preventing the suburban and rural cities from becoming as oversaturated in drivers as the urban cities, it would be best to try to limit how many new drivers are recruited in rural and suburban areas.