Hi there, I’m Bhushan Yashwant Patil 👋

👨‍💻 About Me:

I am a passionate Data Analyst with experience in Python, SQL, and data visualization. I love turning raw data into actionable insights and building interactive dashboards that help teams make informed decisions.

• 🔭 Currently working on Data Science & Analytics projects using Python, Pandas, and Machine Learning.
• 🌱 Continuously learning Advanced Analytics, Machine Learning, and Big Data Tools.

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🛠 Skills:

• Technical Skills: Statistcs and Mathmatics.
• Data Analysis & Visualization: Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly), Excel, Power BI, Tableau.
• Databases & SQL: MySQL, PostgreSQL, SQLite.
• Machine Learning: Scikit-Learn, Regression, Classification, Clustering.
• Other Tools: Jupyter Notebook, Google Colab.

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📊 Projects

1. Retail Sales Analytics Dashboard

• This project showcases a complete data analysis pipeline — from raw CSV files to interactive dashboards — using Python, MySQL, and Tableau Public.
• The dataset represents a multi-store retail company dealing in bikes and accessories, containing information about customers, products, orders, stores, and staff.

Problem Statement:

• A retail company wants to identify key factors driving its sales performance across multiple stores and product categories.
• The challenge is to consolidate scattered CSV data into a single relational system and derive actionable insights.
• This project delivers a data-driven dashboard that supports business decisions on revenue growth and customer engagement.

Project Details: https://github.com/BhushanYP/Retail-Sales-Analytics-Dashboard

2. Hospital Readmission Analysis

• Hospital readmissions are a significant concern in healthcare, as they can indicate complications, poor post-discharge care, or ineffective treatment.
• The goal of this project is to analyze hospital patient data and predict readmission risk, providing actionable insights to improve patient outcomes and reduce hospital costs.

Problem Statement:

• Hospitals face high costs and penalties when patients are readmitted within 30 days of discharge.
• These readmissions often indicate poor care coordination, unplanned complications, or lack of follow-up.

Project Details: https://github.com/BhushanYP/Hospital_Readmissions

3. Grid Stability Prediction using Machine Learning

• This project focuses on predicting power grid stability based on sensor-like simulation data of producers and consumers in an electrical grid.
• The goal is to anticipate unstable states before they occur — enabling early maintenance and preventing power failures.

Problem Statement:

• In modern energy grids, maintaining stability between producers (power plants) and consumers (loads) is critical.
• Even small fluctuations in parameters like reaction time, nominal power, or price elasticity can cause instability.
• This project applies machine learning to predict whether the grid is in a stable or unstable state.
• Enabling proactive rerouting or maintenance before customer impact.

Project Details: https://github.com/BhushanYP/Grids_Stability_ML_Model

4. Pokémon Team Builder

• This project is an Pokémon Team Builder that helps players create the most balanced and powerful teams using data-driven insights.
• It uses machine learning to predict Pokémon battle power and recommend team members that complement each other’s types — ensuring full team coverage and strategic advantage.

Problem Statement:

• Building a balanced Pokémon team manually often leads to poor type coverage and weak defense against certain opponents.
• Players struggle to predict true battle potential of Pokémon based on raw stats and types.
• There’s no easy system that combines type synergy, power prediction, and visual analysis to recommend the most effective team.

Project Details: https://github.com/BhushanYP/Pokemon-Team-Builder

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📫 Contact Me:

• LinkedIn: https://www.linkedin.com/in/bhushan-patil-381601293/
• Email: patilbhushan1086@gmail.com

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