In this project, we will deeply investigate Corn and Wheat crop production stats from the past to discover current trends. Afterward, we plan to create smart models to predict future outputs for both plants according to identified patterns and harvest periods. The purpose is to give helpful info for better planning, wiser resource use, dealing with changing conditions, meeting market needs, and staying updated on farming technology in agriculture. Through careful studies neat graphs, and clever algorithms, we aim to shine a light on hidden factors behind successful Corn and Wheat harvests worldwide, helping bring positive change and success in world farming.
- Python
- Jupyter Notebook
- Pandas
- Numpy
- scikit-learn
- seaborn
- matplotlib
In this project, we use four datasets for yield Analysis.
- Corn_price_history.csv
- Wheat_price_history.csv
- Client_cash.csv
- new_dump.csv
I Uploaded the dataset in repos you can download it easily
The goals of the project likely involve performing an exhaustive analysis of historical price trends for Corn and Wheat commodities, coupled with investigating cash management dynamics and other relevant factors present in the Client_cash.csv and new_dump.csv files. Specific objectives may comprise:
- Thorough exploration of pricing volatilities, cyclical patterns, and macroeconomic drivers influencing historical Corn and Wheat prices.
- Examine Corn_price_history.csv
- Evaluate Wheat_price_history.csv
- Investigation of cash flow management practices, funding sources, expense allocations, and investment behaviors demonstrated by participants outlined in the Client_cash.csv.
- Dissect Client_cash.csv
- Delving into supplementary variables captured within the new_dump.csv, recognizing their contribution to comprehensively understanding Corn and Wheat yield cycles and economic viabilities.
- Explore new_dump.csv
- Construction of data-informed predictive models accounting for observed trends and causal phenomena to estimate probable future price trajectories, taking into consideration anticipated fluctuations in supplies, demand, geopolitical forces, meteorological events, and technological breakthroughs.
- Create predictive models integrating discovered insights
- Synthesis of actionable recommendations and prescriptive actions intended for stakeholders operating within the agricultural sector, assisting them in navigating uncertain futures, hedging risks, maximizing returns, and reinforcing sustainability commitments.
- Formulate practical advice and applicable solutions
- By pursuing these goals, the project seeks to augment decision-making capacities and enhance operational efficiencies for investors, traders, producers, insurers, policymakers, and scholars having vested interests in the Corn and Wheat commodity ecosystem..