A data science portfolio project analyzing Rwanda education indicators to explore trends, progress, gaps, and policy-relevant insights using Python and public development data.
# Rwanda Education Indicators Analysis
## Project Overview
This project is a data science portfolio project analyzing Rwanda education indicators to explore trends, progress, gaps, and policy-relevant insights using Python and public development-style data.
The project focuses on education access, completion, equity, and quality indicators. It demonstrates how data analytics can support education monitoring, policy analysis, program planning, and evidence-based decision-making.
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## Problem Statement
Education systems generate important indicator data over time, but this data must be cleaned, organized, analyzed, and visualized before it can support decision-making.
This project addresses the need for a structured analytics workflow that can:
- Organize education indicator data
- Track trends across years
- Compare primary and secondary education indicators
- Analyze access, completion, equity, and quality patterns
- Identify areas of progress and areas needing continued support
- Communicate findings through charts, reports, and dashboard planning
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## Objectives
The main objectives of this project are to:
- Build a clean and organized education indicators dataset
- Use Python to clean, analyze, and summarize education data
- Explore trends in enrollment, completion, gender parity, and pupil-teacher ratio
- Create visualization scripts for education indicator analysis
- Develop a dashboard plan for education monitoring
- Present findings in a clear portfolio-ready format
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## Repository Structure
- `data/rwanda_education_indicators.csv`
- `scripts/01_data_cleaning_and_eda.py`
- `scripts/02_visualizations.py`
- `reports/project_summary.md`
- `visuals/dashboard_plan.md`
- `notebooks/notebook_plan.md`
- `README.md`
- `requirements.txt`
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## Dataset
The dataset is a sample Rwanda education indicators dataset covering 2015 to 2023. It includes indicators related to access, completion, equity, and education quality.
**Dataset file:** `data/rwan …