📊 Internet Usage Analysis

This project analyzes internet usage data from an ISP log file (isp.csv) to uncover session behavior, peak usage times, daily/hourly trends, anomalies, and more. It includes data preprocessing, insightful analytics, and visualizations.

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📁 Dataset

Input File: isp.csv

Each row in the dataset contains:

• MAC Id: Device identifier
• Login Time: Session start time
• Session Time: Duration of the session (HH:MM:SS)
• Download: Data downloaded in MB
• Upload: Data uploaded in MB

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🧪 Objectives

• Load and clean the dataset
• Engineer useful time-based features
• Analyze total download/upload, sessions, and durations
• Identify top usage days and active hours
• Compare weekday vs weekend usage
• Detect anomalies (long sessions, rapid relogins, high data usage)
• Visualize trends and insights
• Generate a summary report

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📊 Key Insights Extracted

• 📦 Total Download: ~935 GB
• 🚀 Total Upload: ~68 GB
• 📈 Total Sessions: 1163
• 🕒 Average Session Duration: ~29.27 minutes
• 💡 Peak Download Day: 2025-06-17 (~102.78 GB)
• 🔼 Upload/Download Ratio: ~0.07
• ⏱ Longest Session: 61.48 minutes
• ⚡ Shortest Session: 0 minutes (rapid relogin)

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📊 Visualizations

• 📅 Line plot: Daily download/upload trends
• 📊 Bar chart: Top 5 usage days
• 🧊 Heatmap: Hourly login distribution by weekday
• 📉 Histogram: Session time distribution
• 🥧 Pie chart: Upload vs Download share
• 📈 Cumulative usage plot: Over time
• 📆 Daily session duration: Trend over the month

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🧰 Tools Used

• pandas – data processing
• matplotlib / seaborn – data visualization
• numpy – numerical computations
• jupyter notebook – analysis interface

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📦 How to Use

1. Clone the repository

   git clone https://github.com/your-username/internet-usage-analysis.git
   cd internet-usage-analysis