This project involves analyzing airline data to uncover insights on flight delays, airline performance, and travel patterns. The goal is to provide meaningful visualizations and statistics that can aid in better understanding the aviation industry trends.
The dataset used for this analysis is sourced from Kaggle, and includes information such as:
- Airline names
- Airline age
- Fleet size
- Aircraft utlisation
- Load factor
- Python
- Pandas – Data manipulation
- NumPy – Numerical analysis
- Matplotlib & Seaborn – Visualizations
- Jupyter Notebook – Interactive coding
- Identified top airlines according to their fleet size.
- Analyzed fleet distribution stats.
- Visualized average fleet age by region.
- Explored trends and patterns.
- Boxplotted outliers in fleet size.
- Bar charts showing nulls.
- Clone the repo:
git clone https://github.com/pui1ya/airlines-data-analysis.git