Hawaii Climate Analysis

Hawaii climate is being analyzed in this project. I addition, climate API is generated using flask server, which will serve as input for front-end programming. This analysis was carried out in these steps:

Backend Engineering

Step 1 - Data Engineering "data_engineering.ipynb"

• Data from csv files was cleaned and prepared for the analysis. Cleaned csv files were resaved in "Cleaned_CSV" folder.

Step 2 - Database Engineering "database_engineering.ipynb"

• Using SQLAlchemy (declarative_base) to model table schemas and create a sqlite database for the two tables.
• Sqlite database was saved in folder "Resources_cleaned"

Step 3 - Create FLASK API "app.py", by reflecting db into ORM classes and then creating queries. The routes created were:

• /api/v1.0/precipitation
• /api/v1.0/stations
• /api/v1.0/tobs
• /api/v1.0/ (start date as '%Y-%m-%d')
• /api/v1.0//(start/end date as '%Y-%m-%d')

Climate Analysis

• Precipitation Analysis

• Station Analysis

• Temperature Analysis