✈️ Flight Delay Dashboard — Dash & Plotly

An interactive analytics dashboard for exploring U.S. flight delay causes between 2010–2020.
Built with Dash + Plotly, the project demonstrates dashboard engineering, data visualization, and storytelling with data.
Designed to be interview-ready, with emphasis on clarity, reproducibility, and professional presentation.

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📂 Project Structure

├── python_flight_delay_vscode.py # Main Dash application ├── dashboard_layout.png # Dashboard overview screenshot ├── carrier_delays.png # Carrier delay plot ├── weather_delays.png # Weather delay plot ├── nas_security.png # NAS & Security delay plot ├── late_delays.png # Late aircraft delay plot ├── README.md # Project documentation

markdown Copy code

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⚙️ Skills & Tech

• Languages: Python
• Libraries: Pandas, Plotly, Dash
• Visualization: Interactive line charts, dark theme, hover tooltips
• Dashboarding: Dash callbacks, responsive multi-plot layout
• Environment: VS Code, auto browser launch

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📝 Project Overview

This project builds an interactive dashboard that helps analyze causes of flight delays.

Workflow highlights:

1. Data Loading — U.S. flight delay dataset (2010–2020)
2. Computation — Aggregating monthly averages for each delay type
3. Dashboard UI — Year selector + five interactive plots
4. Interactivity — Real-time updates when a year is selected

Delay categories analyzed:

• Carrier
• Weather
• NAS (National Airspace System)
• Security
• Late Aircraft

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📊 Dataset

• Source: U.S. Department of Transportation – Bureau of Transportation Statistics
• Records: ~500,000 flight records
• Features:
  • Year, Month, Reporting_Airline
  • CarrierDelay, WeatherDelay, NASDelay, SecurityDelay, LateAircraftDelay

5. **Results **

   📊 Results

📊 Results

The dashboard provides interactive insights into different causes of flight delays.
Below are example visualizations generated from the app:

🛫 Carrier Delays

🌦️ Weather Delays

🛰️ NAS & Security Delays

✈️ Late Aircraft Delays

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📌 Full Dashboard Layout

▶️ How to Run

1. Clone this repository:

   git clone https://github.com/Shamir-Havas/Flight_Delay-Dash-Plotly.git
   cd Flight_Delay-Dash-Plotly

Install dependencies:

bash Copy code pip install pandas dash plotly Run the application:

bash Copy code python python_flight_delay_vscode.py Open in browser:

http://127.0.0.1:8050/
📊 Results & Dashboard 🔹 Carrier Delay Trends

🔹 Weather Delay Trends

🔹 NAS & Security Delays

🔹 Late Aircraft Delay Trends

🔍 Insights

Carrier delays rise in summer due to higher passenger volumes.

Weather delays peak in winter, especially for northern hubs.

NAS delays consistently impact all airlines.

Security delays are rare but disruptive when they occur.

Late aircraft delays are a major contributor across all years.

🚀 Future Improvements

Deploy live dashboard (Heroku / Render)

Enhance UI with advanced filtering (airport, airline)

Integrate ML models to predict delays

Add economic impact analysis of delays

📦 Requirements

pandas==2.0.3
plotly==5.17.0
dash==2.15.0