This project focuses on analyzing the Flights Booking Dataset containing real-world flight details between major cities in India.
The dataset was scraped datewise from a popular travel website and structured as a CSV file for analysis.
The dataset includes the following key features:
- 🏙️ Source & Destination City
- 🕓 Departure & Arrival Time
- ⏱️ Flight Duration
- 💸 Ticket Price
✈️ Airline Name
Each record represents a scheduled flight along with its corresponding details such as timing, price, and airline.
The goal of this analysis is to:
- Explore pricing trends among different airlines and routes
- Identify peak travel times and flight duration patterns
- Understand how factors like duration or departure time affect flight prices
- Provide insights useful for the Airlines and Travel industries
This analysis can help airline professionals, travel agents, and data analysts make better, data-driven decisions on pricing and scheduling.
- Analyse_Flights_Data.ipynb — Full exploratory data analysis using Pandas and visualization libraries.
