We used the flights data from May 1st 2017 to perform database construction and queries. The final python scripts are in PS3.py.
We succeeded to get the average departure-delayed time of all airports for each state on that day, and the average departure-delayed time for each airport in Florida, using raw SQL.
SELECT State, ROUND(AVG(Dep_Delay_New),2) FROM Flights JOIN Airports ON Origin = Code GROUP BY State;
SELECT Code,ROUND(AVG(Dep_Delay_New),2) FROM Airports JOIN Flights ON Code = Origin GROUP BY Code HAVING State = 'FL';
You will receive points for:
| Rubric item | Points | Your score |
|---|---|---|
| Group plan submitted | 5 points | 5 |
| Defined elements above: * Database: * Tables are normalized * Tables have reasonable structure * Tables have primary and foreign keys defined * SQLAlchemy * Add data to database * Query database * Select, where, join |
20 points | 20 |
| Having at least one commit from each member of the team | 2 points | 2 |
| Using meaningful commit messages | 2 points | 2 |
| Using branches to work collaboratively | 4 points | 4 |
| Using comments in code | 1 points | 1 |
| Logical flow to code | 3 points | 3 |
| Readability of code | 3 points | 3 |
Total points:
40/40
Good job. Would have been better to add the queries to your python script, but OK.