Analyse and graph data using the Matplotlib library.
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1- Urban Cities have considerably more rides
Rural 125
Suburban 625
Urban 1625
2- Similarely as ilustrated on data frame 2 and 3 Urban Cities have more total drivers and total amount of fares
- Having more rides as it is the case in Urban Cities it makes sense to have more drivers and fares.
3- As seen on data frame 4 and 5, the average price per city and per driver is lower in Urban cities and highest in rural areas
- With less rides it makes sense tha the prices will be higher in rural areas.
4- The summary of the above data is represented in tables in point 6 and 7
5- The graph on the second deliverable depicts the fare prices from January to April and the prices throughout this period
Rural areas have consistantly higher prices
Rural areas have almost twice the price of Suburban areas and the Suburban areas have almost twice the price of Urban Cities
Rural areas exebit a more dynamic trend especially starting from the end of February to April while Suburban and Urban cities are more stable
- Based on the results, the three business recommendations to the CEO for addressing any disparities among the city types are as below:
1- Must focus more on the rural area as the market share is low while the margins are very high.
2- A similar strategy to the above could be pursued with the Suburban areas.
3- Regarding urban cities, despite the lower margins the turnover and dynamism is high. It is the most important part of the business. I would suggest to maintain current track especially in April and end of February in which prices are higher. A shift could be considered towards rural and suburban areas if solid success is achieved.