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CMPT 732 Project: Weather Analysis for British Columbia

Introduction

In response to the growing need for comprehensive weather analysis in British Columbia, our project aims to leverage advanced data analytics and visualization techniques to provide a detailed understanding of key environmental factors. Focused on weather, temperature, air pollution, and wildfire data, our project culminates in the development of a web application designed to offer accessible insights to the residents and authorities of British Columbia.

Contributors

  • Chengkun He
  • Binming Li
  • Dexin Yang

Repository Structure

.
└── cmpt-732-final-project
    ├── assets/                                <- picture assets of web app
    │   ├── 128x128/...
    │   ├── 64x64/...
    │   ├── Logo.png
    │   ├── arrow-down-sign-to-navigate.png
    │   └── dashExtensions_default.js
    ├── config/                                <- main config
    │   └── config.yaml
    ├── src/                                   <- backend utils & scripts for automation
    │   ├── data_fetch.py
    │   ├── data_provider.py
    │   ├── import_data_c.py
    │   ├── import_data_hf.py
    │   ├── initialize.py
    │   ├── load_data_hf.py
    │   ├── wildfire_data_scraping.py
    │   ├── wildfire_initialize.py
    │   └── wildfire_spark_load.py
    ├── data/                                  <- sample data for illustration
    │   ├── prot_current_fire_polys/...
    │   ├── prot_current_fire_polys.zip
    │   ├── forecast_weather.csv
    │   └── history_weather.csv
    ├── pages/                                 <- pages displayed in app
    │   ├── weather_map.py
    │   ├── weather_chart.py
    │   ├── wildfire_graphs.py
    │   ├── wildfire_list.py
    │   └── wildfire_map.py
    ├── app.py                                 <- main app
    ├── requirements.txt                       <- requirements to be installed
    ├── README.md                              <- deployment & launch instruction
    ├── RUNNING.md                             <- introduction to the project
    └── .gitignore

Demo

Tools/Technologies

  • Data Fetch Automation: Python Schedule, tmux
  • ETL operations: Apache Spark, Pandas
  • Backend Database: Amazon Keyspace (Cassandra)
  • Visualization: Plotly, Leaflet, Mapbox
  • Deployment: Amazon EC2
  • Frontend: Dash by Plotly

Data source

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