oluwabusola-may/nigeria-professional-financial-analysis

Data analytics project analyzing financial wellness among young Nigerian professionals which includesurvey design, Python data cleaning and EDA, SQL, and a Power BI dashboard. Built a 0–100 Financial Wellness Score across budgeting, saving, emergency funds, investing, and literacy for 308 respondents. README (5).md # The State of Personal Finance Among Young Nigerian Professionals (2026) A data analytics deep-dive into savings behaviour, emergency-fund coverage, investing habits, budgeting, and financial literacy among young Nigerian professionals — from survey design through to an executive Power BI dashboard. **[View the Linkedin write up (linkedin.com)]**  |  **View the dashboard (PDF/screenshots) →** --- ## 📊 Overview Financial fragility is common among young professionals, but it's rarely quantified in a way banks, fintechs, and consulting firms can act on. This project builds a **Financial Wellness Score (0–100)** from real survey data, then uses it to answer: - How financially healthy are young Nigerian professionals, really? - Where does that health break down first — budgeting, saving, emergency funds, investing, or literacy? - Does income, employment type, region, or age explain the differences? **Sample:** 308 respondents (real survey responses collected via Google Forms, supplemented with synthetic data validated to sit within 3–5 percentage points of real-data distributions on key variables). ## 🔑 Key Findings - **74.4%** of respondents fall into the *Vulnerable* or *At Risk* wellness bands — financial fragility is the norm, not the exception, in this sample. - **Emergency fund coverage is the weakest link**: the lowest-scoring component for 48% of respondents, and only 58.1% have any fund at all. - **57.8% don't invest**, and "I don't earn enough" is the most common reason given — not distrust or lack of awareness. - **Income and employment type both independently predict wellness score** (ANOVA p ## 🛠️ Tech Stack | Stage | Tools | |---|---| | Data collection | Google Forms | | Automated scoring & respondent emails | Google Apps Script | | Data cleaning & analysis | Python (pandas) | | SQL querying | SQLite | | Exploratory Data Analysis | Python (MatPlotlib) | | Visualization | Power BI | | …