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nafeesafirdous/README.md

Hi, I'm Nafeesa

I clean, analyse and visualise data using Python and SQL, turning raw datasets into findings someone can actually act on.

My toolkit is Python and pandas for cleaning and analysis, SQL/MySQL for querying, Excel for quick checks, and Git for version control. I'm currently building up my Power BI skills to take these projects further into dashboards.

Projects

Gloucestershire Crime Analysis · Python, pandas, Matplotlib, Seaborn Cleaned and combined 117,553 street crime records from 24 monthly files into one dataset, then worked through what the numbers could and couldn't actually support.

Retail Sales SQL Analysis · MySQL 14 SQL queries, including a window function for branch-level rankings, turning 1,000 transactions into business findings and recommendations.

Travelling Salesman Visualiser · Python, Streamlit An interactive app comparing brute-force and nearest-neighbour route optimisation, trading a small amount of accuracy for a big jump in speed.

Get in touch

nafeesafirdous9555@gmail.com · LinkedIn

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  1. gloucestershire-crime-analysis gloucestershire-crime-analysis Public

    Exploratory data analysis of 117,553 street crime records published by Gloucestershire Constabulary for the years 2024–2025. Built with Python, pandas, Matplotlib and Seaborn.

    Jupyter Notebook

  2. Supermarket-Sales-Performance-Analysis-SQL Supermarket-Sales-Performance-Analysis-SQL Public

    SQL analysis of supermarket sales data to uncover revenue drivers, branch performance, customer behaviour, and sales trends.

  3. travelling-salesman-visualiser travelling-salesman-visualiser Public

    A Streamlit app that solves and animates the Travelling Salesman Problem using Brute Force and Nearest Neighbour algorithms, with support for random points and real-world geocoded locations.

    Python