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Web application that uses Flask and SQLAlchemy to extract data from a SQLite database and uses the Plotly and ZingChart JavaScript libraries to visualize the data in an interactive dashboard

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mileslucey/airbnb_dashboard

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Airbnb Dashboard

Background Information

Team Members

  • Shannon Chang
  • Madeleine Merken
  • Miles Lucey

Data Source

  • MySQL database created in a past project. Follow this link to see how we originally assembled the database
  • The database is adapted to only include four Seattle neighborhoods (Queen Anne, Central Area, Downtown, and Beacon Hill) and then converted into a SQLite database
  • The data is taken at a single point in time and includes 1,114 listings in total:
    • 245 Queen Anne listings
    • 318 Cemtral Area listings
    • 449 Downtown listings
    • 102 Beacon Hill listings

Tools Used

  • Back end database: SQLite
  • Front end: HML, CSS, JavaScript
  • Connecting front end and back end: Python (SQLAlchemy and Flask)
  • Charts: JavaScript libraries (Plotly and ZingChart)
  • Deploying application: Heroku

Final Product

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Web application that uses Flask and SQLAlchemy to extract data from a SQLite database and uses the Plotly and ZingChart JavaScript libraries to visualize the data in an interactive dashboard

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