aduayomide706-commits/agricultural-data-analysis

Agricultural crop yield and farmer records analysis for Ondo State, Nigeria — built with Microsoft Excel (PivotTables, XLOOKUP, Charts). # agricultural-data-analysis Author: Adu Ayomide John Tools Used: Microsoft Excel (PivotTables, XLOOKUP, Conditional Formatting, Charts) Data Scope: 30 smallholder farmers across 8 LGAs in Ondo State, Nigeria — 2023 Farming Season Overview This project involves the collection, cleaning, and analysis of agricultural field data to identify crop yield trends, assess soil and rainfall influences on farm productivity, and generate insights to support evidence-based agricultural planning. What's Inside Raw Data Sheet — Farmer records including farm size, crop type, soil condition, rainfall, fertiliser usage, yield per hectare, and estimated revenue Pivot Summary Sheet — Aggregated performance tables by crop type and LGA Charts & Trends Sheet — Visual analysis of crop yield comparisons and rainfall-yield relationships Report Summary Sheet — Executive summary with key findings and recommendations Key Findings Loamy soils and 1,200–1,600mm rainfall correlated with the highest yields Combined NPK + Organic fertiliser use outperformed single-input approaches Cocoa and Palm Oil generated the highest average farm revenue Skills Demonstrated Data Collection · Data Cleaning · PivotTable Analysis · XLOOKUP · Data Visualisation · Report Writing