This Analysis is about showing the total weekly fares by using a multiple-line graph in three city types suburban, urban and rural , On the other hand Analyzing total rides for each city type ,total drivers and average fare per ride , we did also compared the average ride fare to the total number of rides
This data is including a set of information in Total Rides ,Total Drivers , Total Fares Average Fare per Ride and Average Fare per Driver
the multiple-line chart is able to show total fare by the city over Jan to May 5 months we can see an increase during the month of April and ,The number of rides seems not stable at the end of February and fluctuates during the month of March
The end of Feb is the peek there is a relationship between city population and the total number of rides and total drivers , we can notice the average fare per ride and per driver seems to increase in urban areas and suburban areas ,another fact in rural areas fewer drivers lead to a higher average fare per ride
it is related to the accessibility for (the internet connection ) and the public transportation in some areas
First of all , We can see an increase during the month of April in suburban cities, and the total fare decreases for other types of cities Furthermore the average fare per ride shows an increase from more populated cites to less populated cities. This type of information helps the company addressing the reasons behind these data and fixing it , by limiting or increasing the number of drivers during a certain time . and we can notice the less number of rides is the reason behind less drivers and making average fare per ride more expensive This data set is so important for the company in making more profit and managing rush hours in hiring new drivers and also addressing the problem of why in rural areas total rides are minimum .?