✈️ Flight Delays Analysis (R Programming Project)

📌 Project Overview

This project analyzes flight delays using R programming.
The dataset includes flight information such as scheduled time, departure time, carrier, weather, and delay status.
The goal was to visualize the impact of different factors on delays using histograms, scatter plots, box plots, bar charts, and pie charts.

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🛠️ Tools & Packages

• R Programming
• ggplot2
• dplyr
• readxl
• tidyverse
• lubridate

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📂 Repository Contents

• datasets/Flight_Delays.xlsx → Dataset
• FlightDelays.R → R Script with analysis code
• images/ → All chart images
• Flight_Delay_Project_Summary.pdf → Project Report
• My_Learning_Experience.pdf → Learning Note
• README.md → Documentation

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📊 Visualizations (in analysis order)

1) Scheduled Time Distribution

2) Flights per Carrier

3) Flight Distribution by Destination

4) Flight Distribution by Origin

5) Flights Distribution by Weather Condition

6) Flights Distribution by Day of the Week

7) Scheduled vs Departure Time (Scatter Plot)

8) Delay Distribution by Day of the Month (Box Plot)

9) Flight Delays by Departure Period

10) Flight Delays by Carrier

11) Flight Delays by Day of the Week

12) Flight Delays by Weather

13) Flight Delays by Scheduled Time

14) Delayed vs On-Time Flights (Pie Chart)

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🔑 Key Insights

• 19.45% of flights were delayed, 80.55% were on-time.
• Delays were more frequent in late evening flights.
• Certain airlines had higher delay rates than others.
• Weather caused only 1.5% of delays, but when bad weather occurred, delays were almost certain.

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🧑‍💻 Learning Experience

Working on this project gave me a valuable opportunity to apply R programming concepts to a real dataset.
I learned data cleaning, time conversion, categorical representation, and visualization using ggplot2 and dplyr.
This project strengthened my ability to explore and present insights clearly.

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▶️ How to Run

1. Download this repository.
2. Install required R packages:

   install.packages(c("ggplot2","dplyr","readxl","lubridate","tidyverse"))

3. Run the script: source("FlightDelays.R")