Web Server Log Analysis Python| Analyzing Calgary HTTP Web Logs
Welcome to this complete walkthrough of a real-world data analysis project using Python! 🔍📊
In this video, we analyze the Calgary HTTP dataset, which simulates approximately one year’s worth of HTTP requests to the University of Calgary’s Computer Science web server (1995). The project walks you through *data loading, cleaning, exploration, and 10 analytical queries* including 404 errors, bandwidth tracking, top requests, and more.
✅ Topics Covered:
Introduction
What is the Calgary HTTP Dataset?
Importing Required Libraries
Data Cleaning & Preprocessing
Log File Structure Explained
Q1: Total Log Records
Q2: Unique Hosts
Q3: Date-wise Unique Filename Counts
Q4: Number of 404 Errors
Q5: Top 15 Filenames with 404 Responses
Q6: Top File Extensions (404)
Q7: Bandwidth per Day (July 1995)
Q8: Hourly Traffic Distribution
Q9: Most Requested Files
Q10: HTTP Status Code Distribution
Summary & Final Thoughts
📁 Tools Used:
Python
Pandas
Matplotlib / Seaborn
Regular Expressions
Jupyter Notebook
💡 Ideal for:
Students working on Python log analysis projects
Data Science learners
Web server log analysts
Anyone curious about how to work with real-world HTTP server logs
📎 GitHub Repository / Notebook:
👉 [Add your GitHub repo or notebook link here]
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