Flight Tracker

Introduction to Data Science

Team 3: Fantastic Four
Group Member:

  • Sim Jia Hong (U2005316)
  • Pua Zhi Xian (U2005293)
  • Cher Jia Wen (U2005415)
  • Tan Jia Chyi (17205011)

Lecturer: Dr Salimah Mokhtar

Introduction



This shiny app is implemented to track airfare based on price range, duration and departure time. This shiny app tracks airfare based on price range, duration, and departure time.

Direct link to
GitHub
ShinyApp
Dataset

Problem Statement

- How do users compare domestic airfares offered by Indian airlines to find the best deal?

Solution

- An app is developed that allows consumers to check and compare domestic airfares from multiple Indian airlines to find the best deal.

Stakeholder

- Citizens who travel within India.

Summary of Experience using the App

- Challenge faced: scraping real-time data from the website
- Solution: use online flight price tracker dataset
- Summary: gained useful knowledge in developing shiny apps

Data Science Process

1. Asking Question

What problems do consumers encounter when looking for flights?

2. Finding Dataset

The dataset is from Kaggle and includes features like airline, departure
and arrival time, source city, destination city, duration and price.

3. Cleaning Data

To fix incomplete and duplicated data.

4. Analyzing Data

To analyze the data using EDA.

5. Presenting Data

To present the data in data storytelling for visualization.

Drop-down menus select the departure city, destination, cabin class, and departure time. Users can simply select the desired price range and click “Sort” to get the results.

Data visualization included in the summary tab:

Key Takeaway

By using the flight price tracker, we are able to:

  1. Track the airfare in India and choose the most suitable one
  2. View the data visualization on the price difference in cabin classes