Project-13-Python-For-Data-Analysis-Airlines

End-to-end EDA on 300,153 Indian airline flight bookings | Analyzing price patterns across airlines, routes, departure times, booking windows & travel classes using Python, Pandas & Seaborn

✈️ Data Analysis Project — Airlines Flights Dataset (India)

An end-to-end Data Analysis project on 300,153 flight booking records across 6 Indian cities, completed as part of the Python for Data Analysis course.

📌 Objective

Analyze flight pricing patterns across airlines, departure/arrival times, routes, last-minute booking behavior, and Economy vs Business class comparisons.

📂 Dataset

• Source: AirlinesFlightsData.csv
• Records: 300,153 flight bookings
• Airlines: SpiceJet, AirAsia, Vistara, GO_FIRST, Indigo, Air_India
• Cities: Delhi, Mumbai, Bangalore, Kolkata, Hyderabad, Chennai
• Features: airline, flight, source_city, departure_time, stops, arrival_time, destination_city, class, duration, days_left, price

🛠️ Tools & Libraries

Library	Purpose
Pandas	Data cleaning, filtering, groupby
Matplotlib	Bar charts, line charts
Seaborn	Boxplots, heatmaps, scatter plots

❓ Analytical Questions

Q1 — Airlines & Their Frequencies

Q2 — Bar Graphs: Departure Time & Arrival Time

Q3 — Bar Graphs: Source City & Destination City

Q4 — Does Price Vary with Airlines?

Q5 — Does Price Change Based on Departure & Arrival Time?

Q6 — How Does Price Change with Source & Destination?

Q7 — How is Price Affected for Last-Minute Bookings (1–2 Days)?

Q8 — Price Difference Between Economy & Business Class

Q9 — Average Price: Vistara | Delhi → Hyderabad | Business Class

📊 Analysis Structure

1. Imports & Setup
2. Load Dataset
3. First Look (head / tail)
4. Data Structure & Info
5. Data Quality Check
6. Unique Values per Column
7. Analytical Questions (Q1 → Q9)
8. Additional Visualizations
   • Price Distribution
   • Price vs Stops
   • Price vs Duration
   • Correlation Heatmap
9. Key Insights

💡 Key Insights

• Business class costs 5–6x more than Economy on average
• Last-minute bookings (1–2 days before) are significantly more expensive
• Vistara is the most premium airline; SpiceJet & AirAsia are budget-friendly
• Evening and Late Night departures tend to be cheaper
• Non-stop flights can be priced higher than one-stop — convenience premium
• Delhi and Mumbai dominate as source cities

🚀 How to Run

git clone https://github.com/ammarelsayed-2a/Project-13-Python-For-Data-Analysis-Airlines.git
cd Project-13-Python-For-Data-Analysis-Airlines
jupyter notebook "Project 13 Airlines.ipynb"

👤 Author

Ammar Elsayed — Python for Data Analysis | 2026 LinkedIn