The purpose of this analysis is to provede the ride sharing data from the 'Rural, Urban, and Suburban' areas. I'll be merging the data from the Ride_data and City_data to help with my analysis. I'll then create a summary DataFrame of the ride-sharing data by city type. Lastly after the conclusion of my dataframe I'll create a multiple-line graph that shows the total weekly fares for each city type. The final results are in my PyBer_Challenge
Judging from the total_rides picture below we can anazlyze and tell the differences in so of the ride sharing data. IF we start off from the columns from left to right we'll first see the Total Rides column. We can see that the least amount of rides are in Rural areas and the most amount of rides are in Urban areas. In the urban areas it almost triple the amount of ride from the suburban areas. For that reason the Urban areas need more drivers. There's clearly a higher demand for rides and drivers in Urban areas. Also the fare is the lowest in the Urban areas and the highest in the Rural areas. Which leads to the average fare per drive is higher in the Rural area because the Fare for the ride is higher. This tells me the demand for more rides are in Urban areas because more people live in those areas and possibly have shorter distances to go than Rural and Suburban areas. With the Rural and Suburban areas most people already depenend on their own means of transportation so RideSharing is less likely an option. When people from those Rural and Suburban areas do ride share the fare is higher because there's possibly a longer distance to drive and less drivers in those areas.
After reviewing the Total_Fare_by_City_Type picture below this gives me a fair monthly assessment. What i can analyze from this picture is all Citty have a spike between the months of Feburary and March. This can be because the change and weather if i were to take a guess. Once the new month of march hits all of the city's take a hit also. Manily the Suburban city. Seems like the Suburban and Rural areas remain constant and really not many changes between the months of March and April. The Urban city's has ongoing increasing and decreasing spickes throughout the months of March and April.
- Based on the results, provide three business recommendations to the CEO for addressing any disparities among the city types.
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The first business decision I'd recommend getting a survey to from all of the ride sharers to see if they enjoyed their ride or not. A simple yes or no survery every ride sharer can answer after their ride.
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I'd compare the survery's between the 3 cities. This can tell you if the amount of that are doing the ride share actually enjoys the share. This can also help you get a forecast of how many drivers are making or breaking the ride share.
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Lastly depending on the comparisons on the survey which ever city had the highest rating I'd incread the ride fare on the months the rideshare had the lowest production. Judging from this analysis that would be between Feb and March. I'll only increase the cities that are doing well because that tells me that the customer really likes the ride share and will help the company in a business aspect in the low performing months.