🚦 Traffic Data Analysis (R)

An analytical project developed in RStudio to explore, visualize, and understand traffic patterns and congestion trends.

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🧠 Project Overview

This project investigates traffic volume and flow patterns using statistical methods and data visualization in R. It applies data cleaning, exploratory data analysis (EDA), and correlation analysis to extract meaningful insights from real-world traffic datasets.

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⚙️ Tools & Libraries

• RStudio
• tidyverse
• ggplot2
• dplyr
• lubridate

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🧾 Dataset

The dataset includes attributes such as:

• Date, Time
• Vehicle_Count
• Weather_Condition
• Speed, Road_Type
• Region / Location

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📊 Methodology

1. Data Cleaning and Preprocessing
2. Exploratory Data Analysis (EDA)
3. Visualization of traffic trends and congestion
4. Correlation and pattern discovery

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📈 Key Insights

• Peak congestion observed during morning and evening hours
• Weather conditions and weekdays significantly impact vehicle count
• Positive correlation between traffic volume and time of day

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📂 Files Included

File	Description
traffic_analysis.R	Main R script
traffic_data.csv	Dataset used for analysis
Traffic_Report.docx	Full project report with outputs
Traffic_Insights.pdf	Summary report containing visual findings

📘 All outputs, graphs, and results are included in the report files.

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👨‍💻 Author

Hemant Kumar M
📍 Newcastle upon Tyne, UK
📧 hihemantkumar786@gmail.com
🔗 GitHub: github.com/Hemant-Kumar786