Sales Analysis Project 📊

This project focuses on Sales Data Analysis using Python in a Jupyter Notebook.
It provides insights into sales trends, revenue generation, and product performance.

📂 Project Structure

• sales_ana.ipynb → Notebook containing all analysis steps.
• sales_ana_corrected.ipynb → Cleaned version of the notebook without execution errors.
• Sales_Analysis.pdf → Original project report/summary in PDF format.

🚀 Features

• Data Cleaning & Preprocessing
• Exploratory Data Analysis (EDA)
• Sales Trends Visualization
• Product & Revenue Insights
• Interactive plots (if using libraries like Plotly/Seaborn/Matplotlib)

🛠️ Technologies Used

• Python 🐍
• Google Colab
• Pandas, NumPy → Data handling
• Matplotlib, Seaborn → Visualization

▶️ How to Run

1. Clone this repository:

   git clone https://github.com/your-username/sales-analysis.git
   cd sales-analysis

2. Open the notebook in Jupyter or Google Colab:

   jupyter notebook sales_ana_corrected.ipynb

3. Run each cell step by step to perform the analysis.

📊 Example Insights

• Monthly sales performance
• Best-selling products
• Peak sales time periods
• Revenue contribution by category

📌 Future Improvements

• Automating data pipeline
• Adding predictive analysis (forecasting sales using ML models)
• Creating a dashboard with PowerBI

👨‍💻 Author

Developed during Vocational Training by Rishabh Chaudhari.
Feel free to fork, contribute, and suggest improvements! 🚀

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