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Data Analytics · Python
Real Estate Analytics
Automated Property Market Intelligence Dashboard
Automated
Pipeline
Python
Stack
Streamlit
Dashboard
PostgreSQL
Storage
◈ The Problem
Real estate analysts in Pakistan spend hours manually collecting and cross-referencing property data from Zameen.com and Graana.com, making market trend analysis slow, inconsistent, and labour-intensive.
◉ The Solution
An automated data pipeline that scrapes live property listings from Zameen and Graana, stores them in PostgreSQL, and surfaces rich interactive analytics through a Streamlit dashboard.
✓Automated Zameen & Graana scraping
✓Structured PostgreSQL storage
✓Interactive Streamlit dashboard
✓Price trend visualisations
✓Location-based heat maps
✓Property type breakdowns
✓Scheduled daily data refresh
✓Export to Excel / CSV
◆ My Role
Designed and built the complete end-to-end data pipeline from scraping to visualisation, including database schema design and dashboard development.
▸Built Python scraping pipeline
▸Designed PostgreSQL schema
▸Built Streamlit analytics dashboard
▸Created Plotly visualisations
▸Set up scheduled scraping jobs
▸Wrote data cleaning & normalisation
Tech Stack
Scraping
- Python
- BeautifulSoup
- Scrapy
- Selenium
Storage
- PostgreSQL
- SQLAlchemy
- Pandas
Visualisation
- Streamlit
- Plotly
- Matplotlib
Key Features
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