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 # WineSalesForecast
 Time Series Wine Sales Forecasting: Analyzing and predicting sales trends for different types of wines in the 20th century using Sparkling and Rose wine datasets.
+
+# Wine Sales Forecasting
+
+## Project Overview
+This project centers around the time series analysis and forecasting of wine sales in the 20th century. Using Python for data analysis and predictive modeling, the sales data for different types of wines (Sparkling and Rose) is examined. The project also includes a business report presented in PowerPoint format.
+
+## Repository Contents
+- `data/`: Folder containing the Sparkling.csv and Rose.csv datasets.
+- `python_analysis/`: Python scripts and notebooks for data exploration, analysis, and forecasting.
+- `business_report/`: PowerPoint presentation summarizing findings and forecasting insights.
+
+## Project Workflow
+1. Data collection and preprocessing.
+2. Python analysis to understand sales trends and patterns.
+3. Time series forecasting using predictive modeling techniques.
+4. Creation of a comprehensive business report , encompassing insights and future projections.
+
+## How to Use
+- Clone this repository to your local machine.
+- Access the `data/` directory to explore the Sparkling and Rose wine datasets.
+- Review Python analysis and forecasting in `python_analysis/`.
+- Refer to the PowerPoint business report in `business_report/` for a concise presentation of the project's findings.
+
+## Acknowledgments
+- The Sparkling and Rose wine datasets serve as the basis for analysis and forecasting.
+- Python is employed for data manipulation, analysis, and modeling.
+- The business report provides a synthesized overview of insights and projections.
+
+## Contact Information
+For inquiries or feedback, feel free to reach out to me at zizou.yogesh@yahoo.com