Web Traffic Data Analysis
Mehmood Ahmad
Web Traffic Data Analysis
Project summary
This repository contains an exploratory data analysis of a web traffic dataset using Python (Pandas, NumPy) and visualization libraries (Matplotlib, Seaborn).
The analysis explores traffic sources, user behavior, and trends to answer key questions about traffic sources, session duration, bounce rates, page views, and Conversion Rate.
What’s included
A Jupyter notebook with the EDA steps: data upload, inspection , cleaning, and visualization.
Plots that summarize traffic sources, session duration, bounce rates, page views, and Conversion Rate.
Findings and recommendations based on the observed patterns.
Key findings
Top traffic sources: organic search and paid traffic.
Peak conversion rate by traffic source.
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Posted Nov 26, 2025
Conducted EDA on web traffic data using Python and visualization libraries.
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