Airlines Data Analysis Dashboard
Indian Domestic Flight Analytics | 300,000+ Records
Overview
Pandas-backed analytics on 300,153 records with Plotly dashboards: pricing, routes, seasonality, and hub performance across four HTML pages.
Problem
Airlines lack interactive tools to analyze pricing patterns, route profitability, and booking behaviors across 300,000+ flight records.
Solution
The dashboard loads 300,153 records into Pandas. Four HTML pages embed Plotly visualizations. Main Dashboard shows average price by airline, price distribution by class, price versus days left scatter, route heatmap, and stop count impact. Price Analysis page examines dynamic pricing by airline, route, and days left. Time Trends page analyzes seasonality and booking window. Route and Airline page presents hub performance and stop penalties.
Technologies
- Python 3.10
- Pandas 2.0
- NumPy 1.24
- Plotly 5.17
- Altair 5.1
- HTML5
- CSS3
- JavaScript
Results
Booking 21+ days before departure saves 35% versus last-minute. Hyderabad–Chennai route lowest average price. Two-or-more stops cost 2.3x non-stop flights. Zero missing values.