The purpose of this project was to create a summary DataFrame of the ride-sharing data by city type. Using that DataFrame, create a multiple-line graph that shows the total weekly fares for each city type. The graph then allows Pyber to address any disparities in the ride-sharing data among the city types.
The data shows that the average ride per driver is significantly less than the average fare in urban cities. Conversely in rural areas the average fare per driver is much higher than the average fare per ride. In suburban areas the average fare per ride and per driver are much closer.
It is clear from the data that there are more drivers in urban areas than there is a demand for; and there appears to be a much greater need for drivers in rural areas. The suburban fare data would indicate a more optimal ratio. Pyber should use this data and other data points not collected here like length/distance of each ride to determine how to increase its driver count in rural areas while decreasing it in urban.