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Data Visualisation dashboard served with fastAPI (Python backend framework) running in Microsoft Azure VM , Domain Name registered with Namecheap.com with Data Processing done in ipynb file and data stored in collections of MongoDB Atlas cloud database

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sanjay-06/zerodown

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Question 3 : US housing market dynamics


The project is done with following technologies

Cloud Platform - Microsoft Azure
server - FastAPI
Frontend - HTML + Chart.js + Bootstrap
Domain   - Namecheap.com
Database - MongoDB Atlas

Project links


Domain Registered with Namecheap.com pointing to Microsoft Azure VM public ip

http://sanjay-zerodown-task.me/

Server Access

http://20.185.234.212:8000/

Folder Structure

US housing market dynamic
|__notebook
|   |_marketdynamics.ipynb(data processing notebook file)
|
|__webapplication
    |_html(static pages for frontend)
    |_routes(route files for fastapi)
    |_main.py(driver code for server)

Screenshots of Interface

First page for metrics like median_sale_price & Quarterly values for different values

first

Price page for metrics like & Quarterly values for different values

Second

comparison for each metric in case of county & metro

third

Video demo

--> click here for Interface demo

The sequence diagram for interface



sequence


Package Usage

Quick start


clone the repository

git clone https://github.com/sanjay-06/zerodown

cd zerodown

Install required Modules

     pip install -r requirements.txt

Navigate to the Project folder (Question 3)

cd "US housing market dynamics"/webapplication

Start the server

  python main.py

View in browser

http://localhost:8000/


Question 2 : Natural Hazards

Shapefile loading done with creating pandas dataframe


Package Usage


Data loading done with hurricane.ipynb notebook

Folder Structure

Natural Hazards
|__hurricane.ipynb

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Data Visualisation dashboard served with fastAPI (Python backend framework) running in Microsoft Azure VM , Domain Name registered with Namecheap.com with Data Processing done in ipynb file and data stored in collections of MongoDB Atlas cloud database

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