This repository contains an exploratory data analysis (EDA) project using Python, Pandas, Matplotlib, and Seaborn. It evaluates farm-level performance across seasonal cultivation cycles (Kharif, Rabi, and Zaid) using a dataset of 4,000 farm records with 28 attributes.
From the README
SeasonalAgriculturePerformanceAnalysis An exploratory data analysis (EDA) project evaluating farm-level performance across seasonal cultivation cycles (Kharif, Rabi, and Zaid) using Python, Pandas, Matplotlib, and Seaborn. --- 📌 Project Overview Agricultural productivity and farm economics are strongly influenced by seasonal climate patterns, resource availability, and management choices. This project analyzes a structured dataset of 4,000 farm records across 28 distinct attributes to evaluate how environmental metrics, irrigation practices, and input investments translate into physical crop yields and net financial margins across seasons. --- 📊 Dataset Summary • Total Records: 4,000...
Skills
- Jupyter Notebook
