🔍 Unveiling West Bengal's Surface Lift Irrigation Insights through Data Science! 📊💧

Excited to share my latest project where I explored the 6th Minor Irrigation Census data focused on Surface Lift Irrigation Schemes in West Bengal!

🌾 Project Goals: Analyzed the financial aspects: Construction, Machinery, and Maintenance Costs across schemes

Visualized cost distribution to understand resource allocation

Explored potential correlations that could help in better planning and investment strategies

🔧 Tools Used: Python | Pandas | NumPy | Matplotlib | Seaborn

✨ Key Highlights: ✅ Cleaned and pre-processed real-world government data

✅ Performed detailed Exploratory Data Analysis (EDA)

✅ Visualized average cost contributions through pie charts

✅ Identified missing values and handled them effectively for better model reliability

🧠 Learning Outcomes: Working with real, complex datasets enhanced my skills in data cleaning, EDA, visualization, and understanding resource utilization patterns.

It also deepened my appreciation of how data can inform smarter public infrastructure planning.

🌍 Why It Matters: Surface lift irrigation is critical for sustainable agriculture in water-scarce regions — data can unlock better efficiency, equity, and impact on rural livelihoods.

here are my objective on this topic *to determine scheme_construction_cost,scheme_machinery_cost,scheme_maintainence_cost *to find the construction_subsidy,machinery_subsidy *to analize water_distribution_method_name *to depict the trends on lifting_device_enrgy_source_name,horse_power_of_lifting_device,pump_operating_days_rabi_season *to analize culturable_command_area,ipc_kharif_season,ipc_rabi_season,ipc_perennial_season