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flight-data-analysis

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Databricks and PySpark project for airline delay analysis, visualization, machine learning prediction, and MongoDB NoSQL storage using U.S. flight data from 2016 to 2018, including more than 18.5 million flight records in the dataset.

  • Updated Apr 11, 2026
  • HTML

This project focuses on scraping flight details from Google Flights, processing the data, and performing cleaning and visualization for future use in analytics or predictive modeling.

  • Updated Jan 21, 2025
  • Jupyter Notebook

This project is a Python-based web scraping script designed to extract flight details from the Yatra travel website. The extracted data includes flight pricing, origin, destination, departure and arrival times, and duration. The data is then saved into a CSV file for further analysis.

  • Updated Jan 17, 2025
  • Jupyter Notebook

Excel analysis of 9,999 US domestic flights (2015) — covers departure/arrival delays by airline (AA, AS, DL, NK, WN etc.), cancellation rates, weather vs. air-system vs. airline delay breakdown, average air time per carrier, and departure hour patterns. Built with pivot tables and an interactive dashboard.

  • Updated Apr 6, 2026

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