An Analytical Perspective of 2D Dependencies of Crop Factor with Data Mining

As we know that agricultural sector holds a crucial position in upholding global food security and economic equilibrium. The precision of forecasts related to crop yield and pricing is of paramount importance to both farmers and policymakers. This research employs data mining techniques to delve into the intricate interplay between crop yield and market prices, furnishing a valuable analytical perspective. The study is based on the opinion of the expert of agriculture fields and potential farmers with the assembly of an all-encompassing dataset, market prices, along with the response question/variables. Although there are lot of parameters such as weather patterns, soil quality, agricultural practices, and economic indicators which affects said relation. To gain a comprehensive understanding of the dataset, we conduct exploratory data analysis (EDA) to unveil underlying patterns, correlations, and dependencies. We probe into the multifaceted factors that wield influence over crop yield and pricing. The analysis delivers valuable insights into the determinants of crop yield and market prices. This study contributes to the broader comprehension of the agricultural ecosystem, underscoring the pivotal role of data mining in providing actionable insights for the promotion of sustainable agriculture and the formulation of informed economic policies.