mznaturl1/sqlalchemy-challenge

sqlalchemy-challenge

SQLAlchemy Challenge:

Using Python and SQLAlchemy to preform a basic climate analysis and data exploration for a climate database for Honolulu, Hawaii containing precipitation and temperature observations. climate database that contains precipitation and temperature observations across 9 stations. Once the analysis is complete, design a Flask API based on SQLAlchemy ORM queries.

Technologies Used

• Python
• SQLAlchemy ORM queries
• Pandas
• Matplotlib

Part 1: Analyze and Explore the Climate Data

1. Complete climate analysis data exploration
2. Connect to the SQLite database using SQLAlchemy
3. Reflect the tables into classes, saving references to classes name station and measurement
4. Link Python to the database by creating a SQLAlchemy session.
5. Perform an analysis on precipitation and then an analysis on station

Part 2: Design The Climate App

Designed a Flask API based on the queries that were developed

1. Home (Welcome) Page, lists available routes
2. Precipitation amounts by date
3. Detailed list of weather stations
4. Recorded temperatres for the last 12 months
5. Min, Average, and Max temps based on start date
6. Min, Average, and Max temps based on start and end dates