Chisomalor/Sub-Saharan-Crop-Yield-Analysis

Multi-decadal analysis of crop production and agricultural biometrics in Nigeria using R # 🌍 Sub-Saharan Crop Yield Analysis ## About This Project As a Plant Science graduate from Nigeria teaching myself computational agriculture, I wanted to explore real crop yield data from Sub-Saharan Africa. This project combines my traditional plant science background with the Python and R skills I have been building independently. ## What I Explored - Comparing maize and rice yield trends in Nigeria - Analyzing how crop yields have changed over time - Exploring the relationship between different crops - Applying basic statistical analysis to real data ## Tools Used - R | ggplot2 | Posit Cloud ## What I Learned This project pushed me beyond my comfort zone. Coming from a traditional agriculture background, working with real statistical data taught me how computational tools can reveal patterns that field observation alone cannot show. ## Why This Matters Sub-Saharan Africa faces real food security challenges. Understanding crop yield patterns using data is increasingly important for agricultural researchers in this region. ## Author **Chisom Alor** | Plant Science & Biotechnology Graduate University of Nigeria, Nsukka GitHub