edwin20-hub/Kenya-County-Development-Indicators-Analysis

Analysis of Kenya County Development Indicators # Kenya County Development Indicators Analysis ## Project Overview An analysis of poverty and economic output (Gross County Product) across Kenya's 47 counties, aiming to identify which counties are outliers relative to their region and surface patterns that could inform development prioritization. **Status**: 🚧 In Progress **Role**: Independent analysis (personal project) **Tools**: SQL, Python (Pandas, Matplotlib), Tableau ## Dataset - **Sources**: - World Bank — Kenya Poverty 2015-2016 (county-level poverty rates) - Kenya National Bureau of Statistics — Gross County Product (GCP) - **Granularity**: County level (47 counties) - **Variables**: county, region, poverty_rate, gross_county_product, population *(planned — will be finalized as data collection continues)* ## Planned Analyses 1. **SQL**: Join poverty and GCP datasets by county; rank counties by poverty rate within their region; calculate GCP per capita. 2. **Python**: Clean and merge the two source datasets; visualize the relationship between poverty rate and GCP per capita (scatter plot); identify statistical outliers. 3. **Tableau**: Build an interactive map/dashboard of Kenya showing poverty rate and GCP by county, with filtering by region. ## Key Questions To Answer - Which counties have high GCP but also high poverty rates (a mismatch worth investigating)? - How does poverty rate vary within a single region (e.g. across former-province groupings)? - Is there a visible relationship between economic output and poverty at the county level? ## Repository Structure ``` ├── data/ # Raw and cleaned datasets ├── sql/ │ └── queries.sql # Join, ranking, and per-capita queries ├── analysis.ipynb # Python cleaning, merging, and visualization ├── dashboard/ # Tableau workbook └── README.md ``` ## How to Use *(Will be updated as each component is completed)* 1. Data cleaning and merge: `analysis.ipynb` 2. SQL queries: `sql/queries.sql` 3. Interactive dashboard: `dashbo …