The purpose of the new analysis is to summarize and understand the demand for ride-sharing in urban, suburban, and rural cities, as well as how ride-sharing usage affects the price of fares.

The above bubble chart displays the relationship between the different types of cities being analyzed: Urban, suburban, and rural. The x-axis measures the total number of rides per city and the y-axis measures the average price for fare in each city type. The circle size indicates driver count per city type.

The above pie chart displays the percentage of total rides by city type. Urban cities have the highest percentage of total rides with 68.4% of total ride-shares happening in the urban cities. Suburban cities follow with 26.3% and rural cities take the smallest percentage with 5.3% of total rides.

The above pie chart displays the percentage of total drivers by city type. Similarly to the chart displaying the percentage of total rides, urban cities take the lead with 80.9% of total drivers. This means that 16.5% of the total count of drivers drive in suburban cities and thus are responsible for 26.3% of the total count of rides. The same goes for rural drivers, 2.6% of the total amount of drivers drive in rural cities and thus are responsible for 5.3% of total rides.

The above multiple-line chart shows the total fare by city type with the x-axis measuring the total weekly fares across the months of January to April of 2019. The y-axis measures the price of fares in $USD. The pie chart shows the percentage of total fares by city types. The pie chart supplements the information we can see from the multiple-line chart; urban cities had 62.7% of the total fares and this is seen with the top-most yellow line showing that urban cities made the most money from fares. Rural cities, by contrast, would barely break $500 total fares between January and April.

Using the above analysis of the data for this ride-sharing service, the company can set measures in place to reward the frequent usage of PyBer in Urban areas as well as incentivizing its use in Rural areas. Possible incentives for rural users might be a rewards system where the consumer accumulates points over time. This can apply to drivers as well, implementing a ranking system based on reviews given by riders. While the demand indeed influences fare prices, incentivizing users by giving them rewards for using the service can increase ride-sharing usage. Ride-sharing relies heavily on drivers, so it is important to make sure that the drivers feel taken care of by offering perks for receiving good reviews from riders.