Data Mining project: scraping, cleaning, analyzing, and visualizing Python job listings in Egypt.
# 🧠 Python Job Market in Egypt – End-to-End Data Mining Project
> **An end-to-end data pipeline**: Scraping → Cleaning → Database → Analysis → Visualization → Machine Learning.
> This project analyzes the **Python job market in Egypt** using data scraped from Wuzzuf and Tanqeeb.
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## 📌 Overview
The Egyptian tech job market is booming, but data on it is scattered. This project solves that by building a complete data mining pipeline:
1. **Web Scraping**: Extracted live job postings from `Wuzzuf` and `Tanqeeb`.
2. **Data Cleaning**: Standardized cities, handled missing values, removed duplicates, and dropped irrelevant columns.
3. **Database Storage**: Stored the cleaned data in an SQLite database (`jobs.db`) for efficient querying.
4. **Analytics (SQL)**: Ran complex queries to uncover trends like top job titles, top hiring companies, and skill demands.
5. **Visualization**: Built insightful charts (bar charts, pie charts, heatmaps) using Matplotlib & Seaborn.
The dataset gained traction on **Kaggle with 22 upvotes** and inspired 2–3 community members to build their own analysis notebooks on top of it!
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## 📊 Key Insights at a Glance
- **Most In-Demand Role**: `Senior Data Engineer` (16 listings).
- **Top Hiring Company**: `Joveo Ai` (32 job postings).
- **Job Location**: **Cairo** dominates with **81.1%** of all listings.
- **Top Job Category**: **AI / ML** (104 listings), followed by Development and Software Eng.
- **Employment Type**: **Full-Time** positions make up the vast majority (325 jobs).
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## 📂 Project Structure
```bash
Python-Job-Market-in-Egypt/
│
├── data/ # Sample datasets (Full data available on Kaggle)
│ ├── sample_before_cleaning.csv
│ └── sample_after_cleaning.xls
│
├── notebooks/ # Jupyter Notebooks
│ └── v.ipynb # Main visualization & analysis notebook
│
├── scripts/ # Python scripts
│ ├── tanqeeb.py # Scraper for Tanqeeb. …