Identifying Cities with Unusual Ride Demand

Requirements Clarification & Assessment

Before diving into the solution, it's crucial to clarify the requirements and assess the available data and constraints:

1. Objective:

   • Identify cities with unusual ride demand, either significantly higher or lower than the average.

2. Data Availability:

   • Access to ride-sharing data from Lyft, including metrics like ride requests, ride completions, user base, and city demographics.
   • Historical data to compare current trends against past performance.

3. Factors Influencing Demand:

   • Population density, public transportation availability, city structure, seasonal events, and socio-economic factors.

4. Time Frame:

   • Define the period for which the demand comparison is relevant (e.g., last month, last quarter).

5. Statistical Significance:

   • Determine the threshold for statistical significance to identify a city as having unusual demand.

6. Performance Metrics:

   • Define specific metrics to be used in the analysis, such as rides per capita, app downloads per capita, and ride frequency.