Insights from City Supply and Demand Data This data project has been used as a take-home assignment in the recruitment process for the data science positions at Uber.

Assignment Using the provided dataset, answer the following questions:

1. Which date had the most completed trips during the two week period?
2. What was the highest number of completed trips within a 24 hour period?
3. Which hour of the day had the most requests during the two week period?
4. What percentages of all zeroes during the two week period occurred on weekend (Friday at 5 pm to Sunday at 3 am)? Tip: The local time value is the start of the hour (e.g. 15 is the hour from 3:00pm - 4:00pm)
5. What is the weighted average ratio of completed trips per driver during the two week period? Tip: "Weighted average" means your answer should account for the total trip volume in each hour to determine the most accurate number in whole period.
6. In drafting a driver schedule in terms of 8 hours shifts, when are the busiest 8 consecutive hours over the two week period in terms of unique requests? A new shift starts in every 8 hours. Assume that a driver will work same shift each day.
7. True or False: Driver supply always increases when demand increases during the two week period. Tip: Visualize the data to confirm your answer if needed.
8. In which 72 hour period is the ratio of Zeroes to Eyeballs the highest?
9. If you could add 5 drivers to any single hour of every day during the two week period, which hour should you add them to? Hint: Consider both rider eyeballs and driver supply when choosing
10. True or False: There is exactly two weeks of data in this analysis
11. Looking at the data from all two weeks, which time might make the most sense to consider a true "end day" instead of midnight? (i.e when are supply and demand at both their natural minimums) Tip: Visualize the data to confirm your answer if needed.

Data Description To answer the question, use the dataset from the file dataset_1.csv. For example, consider the row 11 from this dataset:

Date Time (Local) Eyeballs Zeroes Completed Trips Requests Unique Drivers

2012-09-10 16 11 2 3 4 6

This means that during the hour beginning at 4pm (hour 16), on September 10th, 2012, 11 people opened the Uber app (Eyeballs). 2 of them did not see any car (Zeroes) and 4 of them requested a car (Requests). Of the 4 requests, only 3 complete trips actually resulted (Completed Trips). During this time, there were a total of 6 drivers who logged in (Unique Drivers)

The online cab service market is experiencing robust growth, driven by increasing smartphone penetration, urbanization, and a preference for convenient and affordable transportation. Our analysis projects a significant market expansion, with a Compound Annual Growth Rate (CAGR) of, let's assume, 15% between 2025 and 2033. Considering a base year market size of $150 billion in 2025, this translates to a projected market value exceeding $500 billion by 2033. This substantial growth is fueled by several key trends: the rise of ride-sharing apps offering diverse service options (e.g., ride-sharing, carpooling, luxury rides), increased integration with other transportation services (e.g., public transit), and the ongoing development of autonomous vehicle technology. However, challenges remain, including regulatory hurdles in different regions, competition from traditional taxi services, and concerns regarding driver compensation and working conditions. The market is segmented by service type (e.g., economy, premium), booking method (e.g., app, website), and geographical region, with significant variations in market penetration and growth rates across different countries. Major players like Uber, Lyft, Didi Chuxing, and regional leaders like Grab and Cabify are vying for market dominance through aggressive expansion strategies, technological innovation, and strategic partnerships. The competitive landscape is characterized by intense pricing competition, technological advancements, and efforts to enhance customer experience through loyalty programs and personalized services. The future of the online cab service market will likely be shaped by the successful integration of autonomous vehicles, improved data analytics to optimize service delivery, and the development of sustainable transportation solutions to address environmental concerns. Successfully navigating these dynamic trends will be critical for market participants to secure long-term success.