The Data Normalization Tool helps users standardize datasets by transforming values into a consistent scale. It ensures fair comparisons across variables and improves the performance of machine learning models, statistical analysis, and financial calculations.

Key Features

✅ Supports Multiple Normalization Methods – Choose from Min-Max Scaling, Z-Score Standardization, Log Transformation, and Decimal Scaling.
✅ Batch Processing – Normalize large datasets quickly and efficiently.
✅ Graphical Visualization – Compare data distributions before and after normalization.
✅ Customizable Scaling Ranges – Adjust scaling parameters based on dataset needs.
✅ PDF Report Generation – Export normalized data, transformation methods, and visualization charts.

Use Cases

📌 Machine Learning & AI – Improve model accuracy by standardizing input features.
📌 Financial Data Analysis – Normalize stock prices, economic indicators, and financial ratios.
📌 Scientific & Medical Research – Ensure consistent scaling in experiments and clinical data.
📌 Business & Marketing Analytics – Standardize customer metrics for better segmentation and insights.

How It Works

1️⃣ Upload or Enter Data – Input numeric values manually or upload a CSV file.
2️⃣ Select Normalization Method – Choose from Min-Max Scaling, Z-Score, Log Transformation, or Decimal Scaling.
3️⃣ Run Normalization – The tool applies the selected transformation to adjust data values.
4️⃣ Compare Results – View before-and-after distributions using histograms and summary statistics.
5️⃣ Download PDF Report – Export the transformed dataset, methodology, and visual insights.

This tool makes data normalization easy and efficient, ensuring accurate and meaningful analysis for various applications. 🚀