Project Contributions by:
- Jose Figueroa - figuej3@rpi.edu * Matthew Garber - garbem4@rpi.edu * Andrew Gaudet - gaudea@rpi.edu * Eileen Yao - yaoe@rpi.edu
Requirements:
- Postgres
- Python v 3.4+
- Anaconda
- Or just the pandas, psycopg2, matplotlib, numpy libraries
- Progress library
pip install progress
Setup.py creates the user 'health' and the database 'health' where the program will create relations and execute query. If you have the default postgres superuser you can simply run:
python Setup.py
If you have a different superuser, credentials or database, run the following:
python Setup.py -u username -p password -d database
Load_data.py now completely parses 500_cities.csv and healthy_aging.csv into health database. To run via command line you have to methods:
- If both the CSV files and schema.SQL file are in the same directory, simply run:
python load_data.py - If either the CSV or SQL file are not in the same directory, run:
python load_data.py -c /path/to/csv -s /path/to/schema
load_data.py is verbose and will alert you when each insert is complete.
To run queries on the database run: python application.py