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Using SQLAlchemy to do basic climate analysis and data exploration. Specifically using SQLAlchemy ORM queries, Pandas, and Matplotlib.

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SQLalchemy & Flask: API Creation and Climate Analysis

Project description:

Using SQLAlchemy to do basic climate analysis and data exploration. Specifically using SQLAlchemy ORM queries, Pandas, and Matplotlib.

Based on the above analysis, I have created a Flask API and based it on the ORM queries developed in the section above. The API includes the following routes:

  • '/' Route
  • '/home' Route
  • '/api/v1.0/precipitation/' Route
  • '/api/v1.0/stations' Route
  • '/api/v1.0/tobs' Route
  • Dynamic routes (user based input):
    • '/api/v1.0/start' Route -> This will provide the minimum, maximum, and average temperature from the specified startdate onwards.
    • '/api/v1.0/start/end' -> This will provide the minimum, maximum, and average temperature from the specified startdate to the specified end date.

Analysis Images

line_chart

histogram

Folder structure

.
├── SurfsUp
│   ├── Images    
│   |   ├── Fig_1.png
│   |   ├── Fig_2.png               
│   ├── Resources
│   ├── hawaii_measurements.csv   
│   ├── hawaii_stations.csv 
│   ├── hawaii.sqlite      
│   ├── app.py
│   ├── climate_starter.ipynb
|___.gitignore               
|___README.md

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Using SQLAlchemy to do basic climate analysis and data exploration. Specifically using SQLAlchemy ORM queries, Pandas, and Matplotlib.

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