U.S. Flights Data Analysis 🛫

Project Overview

This repository presents an in-depth analysis of airline and airport operations for US flights in 2015, based on data sourced from Kaggle. The project encompasses a full lifecycle of data handling from extraction through visualization, focusing on 5,000,000+ commercial airline flights records.

Process Details :

1. Data Extraction 🔄:

   • Utilized a Python script to automatically extract data, ensuring the ability to refresh data for up-to-date analysis. The script manages extensive datasets involving flight operations. 🐍

2. Data Transformation and Cleaning ✨:

   • Applied rigorous cleaning processes to enhance data quality by addressing missing values and duplicates.
   • Transformed data for analysis suitability, adjusting timestamps, and categorizing reasons for cancellations.

3. Data Loading 📥:

   • Efficiently loaded the prepared data into an analytics database, facilitating comprehensive analysis.

4. Data Modeling 📊:

   • Created a star schema to facilitate effective querying and data aggregation necessary for the analysis.

5. Data Analysis 🔍:

   • Analyzed 5.82 million rows across 40 fields to determine flight volume variations, departure delay percentages and durations, causes of cancellations, and airline reliability.

6. Reporting and Visualization 📈:

   • Developed intuitive dashboards and visual representations, using bar charts, line graphs, and pie charts to clearly illustrate trends and outliers in flight operations.

Analysis :

1. Flight Volume Variations: Analysis of how overall flight volume varies by month and day of the week.
2. Departure Delays: Examination of what percentage of flights experienced a departure delay in 2015, including the average delay time in minutes.
3. Seasonal Delay Patterns: Insights into how the percentage of delayed flights varies throughout the year, with a specific focus on flights leaving from Boston (BOS).
4. Flight Cancellations: Metrics on how many flights were cancelled in 2015, including the percentage due to weather versus airline/carrier issues.
5. Airline Reliability: Evaluation of which airlines are the most and least reliable in terms of on-time departures.

Key Insights 🌟

• Airline Dashboard: Offers a comparative analysis of airline operations, highlighting cancellations and delays.
• Airport Dashboard: Showcases performance metrics by airport, with a focus on operational challenges.
• Delay Time Dashboard: Provides a detailed view of delay metrics to identify operational inefficiencies across airlines.

📊 Visualization :

1. Report 1: Overview containing all the KPIs about the project, including general statistics, key metrics, and high-level insights.
2. Report 2: Airline Report showcasing metrics such as the top 5 airlines with the most flights, average delay times by airline, and other relevant airline-specific KPIs.
3. Report 3: Airport Report featuring data such as the top 5 airports by flight volume, flight origin and destination patterns, and other key airport-related metrics.
4. Report 4: Delay Time Report visualizing average flight delays, delay trends over time, and delays by different factors such as airline and airport.

📈 Reports :

Reports were created to effectively communicate the insights and findings from the data analysis.

Report 1

Report 2

Report 3

Report 4

📧 Contact

For more informations, please contact:

• Email: [[email protected]]
• LinkedIn: [https://www.linkedin.com/in/raghad-el-ghobashy/]