📊 Financial Dataset Analysis with Python and Power BI

A comprehensive data analysis project using Python to clean, explore, visualize, and model a real-world financial dataset.

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📌 Project Description (English)

This project analyzes a financial dataset containing department-level monthly budgets, spending, and revenues. The goal is to:

• Clean and preprocess raw financial data
• Analyze spending and profits across departments
• Create insightful visualizations using Seaborn and Matplotlib
• Build a predictive model to estimate monthly profit/loss
• Provide business insights to support strategic decisions

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📌 وصف المشروع (عربي)

يهدف هذا المشروع إلى تحليل بيانات مالية حقيقية تتضمن الميزانية الشهرية والمصروفات والإيرادات لكل قسم داخل الشركة، ويشمل:

• تنظيف ومعالجة البيانات الخام
• تحليل الإنفاق والربح حسب الأقسام
• إنشاء رسوم بيانية توضيحية باستخدام Seaborn وMatplotlib
• بناء نموذج تنبؤي لتقدير الربح/الخسارة
• تقديم رؤى لدعم اتخاذ القرار

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🧪 Tools & Libraries / الأدوات والمكتبات

• Python (Pandas, NumPy, Seaborn, Matplotlib)
• Power BI (for advanced dashboard visualization)
• Machine Learning (Linear Regression)

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📈 Key Visuals

Profit Trends	Total Spending

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🚀 How to Use

1. Clone this repo
2. Install required libraries:
3. Open analysis_financial_dataset.ipynb and run step-by-step

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📊 Result Highlights

• Marketing department had the highest total spending
• HR achieved the highest total profit
• July was the month with the biggest loss across departments

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🧠 Author

Mohammed T. — Python Developer | Data Analyst | Power BI Specialist
🔗 Upwork Profile
📫 Reach me for freelance data analytics and automation projects!