1- Create appropriate SQL expressions to determine the most frequent trips between any two stations by the day of the week. 2- Create appropriate SQL expressions to determine usage patterns by gender and age for any given station.
3- Create appropriate SQL expressions to identify any dormant or vacant bike stations.
4- Reconstruct the tables and recreate the SQL expressions above to include zip codes, hence allowing for aggregation by area. Identify the area with the highest usage of the program. Note that zip 2 codes are not included in the data provided but may be related to the StationId by its Latitude and Longitude. This could be part of your research and may require some coding!