HopefulJim7/Analysis-of-Food-Prices-in-Kenya-Analysis

# 🍽️ Kenyan Food Prices Pipeline A simple data pipeline that loads WFP Kenyan food market prices into PostgreSQL for analysis, automated with Apache Airflow. --- ## Project Structure ``` Project_1/ food_prices.ipynb ├── 01_setup.sql # Database + staging table ├── 02_load_csv.py # Load CSV into PostgreSQL ├── 03_queries.sql # 6 SQL queries ├──food_prices_dag.py # Airflow ├── food_prices1_dag.py # Airflow DAG └── README.md ``` --- ## Quick Start ```bash # 1. Create database psql -U postgres -c "CREATE DATABASE food_prices_db;" # 2. Install packages pip install pandas sqlalchemy psycopg2-binary # 3. Load data python 02_load_csv.py # 4. Run Airflow airflow standalone ``` --- ## Data Issues Observed 1. **Commodity name inconsistencies** — Same commodity recorded under multiple names e.g. `Maize`, `Maize (white)`, `Maize (white, dry)` making aggregations unreliable. 2. **Extreme price outliers** — Suspicious spikes like Beans (dry) jumping 5,060% in one month suggesting data entry errors where KG and 90KG units were mixed up. 3. **Missing GPS coordinates** — 53 rows have NULL latitude and longitude preventing spatial analysis for those markets. --- ## Dataset **Source:** World Food Programme (WFP) **Coverage:** Kenya 2006–2026 **Size:** 18,379 rows --- ## 🏅 License MIT License — free to use, modify and distribute.