Flight Price EDA and Prediction ✈

Note: Use google colab in order to view the code and interactive plotly graphs.

Dataset 📔

Kaggle link: Flight Price Data

Objectives 🏆

In this project, these questions will be answered:

• Does price vary with Airlines?
• How is the price affected when tickets are bought in just 1 or 2 days before departure?
• Does ticket price change based on the departure time and arrival time?
• How the price changes with change in Source and Destination?
• How does the ticket price vary between Economy and Business class?
• Which features have the most impact on predicting flight price?
• Which model is the best for predicting flight price?

Project's Table of Contents ✍️

Click to expand!

1. Problem statement
2. Import Libraries and Data
3. Handling Missing Values
4. Data Analysis and Visualization
5. Outlier Detection
6. Check for Rare Categories
7. Categorical Variables Encoding
8. Dataset Splitting
9. Modeling and Parameter Optimization
10. Feature Importance
11. Results

Project Overview 💼

Sample Visualization:

Model Evaluation: