owendi17/Climate-Resilience-and-Agricultural-Technology-Adoption-Among-Smallholder-Farmers-in-Kenya

# 🌱 Climate Resilience and Agricultural Technology Adoption ### Smallholder Farmers in Kenya – Analysis & Decision-Support Tool > **Developed as part of an application for the Global R&D Data Analyst role at One Acre Fund** --- ## Project Overview This project investigates the factors influencing adoption of modern agricultural practices among smallholder farmers in Kenya, and evaluates how climate risks, financial inclusion, and farmer characteristics affect agricultural resilience. The work is structured to meet the analytical standards required for agricultural development programmes — combining causal inference framing, mixed-effects modelling, machine learning, and an interactive deployment tool. --- ## Interactive Dashboard (Tableau) Explore the visual story of this analysis on Tableau Public: 🔗 **View the Tableau Dashboard** The dashboard covers: - Adoption rates by region, education, and financing access - Climate hazard prevalence and vulnerability mapping - Farmer demographic profiles --- ## Project Structure ``` ├── Agri_Strengthened.ipynb # Main analysis notebook ├── app.py # Streamlit deployment app ├── Agri.csv # Raw survey data (not included in repo) ├── cleaned_agriculture_data.csv# Output of cleaning pipeline └── README.md # This file ``` --- ## Research Questions 1. Does access to financing increase adoption of modern farming practices? 2. Which farmer groups are most vulnerable to climate-related losses? 3. What factors predict adoption of improved agricultural practices? 4. How can data-driven recommendations improve agricultural resilience? --- ## Notebook Summary (`Agri_Strengthened.ipynb`) | Section | Description | |---|---| | 1. Imports | All libraries with reproducibility seed set | | 2. Load Data | Shape audit, missingness report | | 3. Data Cleaning | Mode/median imputation, regex extraction for numeric fields | | 4. Feature Engineering | Adoption score ( …