data-transform

Transform, clean, and reshape data locally using pandas and numpy; works with any LLM provider.

• Clean and preprocess raw data
• Normalize and scale numeric features
• Reshape data between wide and long formats
• Filter and subset datasets
• Merge multiple datasets

• Uses pandas, numpy, and sklearn locally
• Compatible with any LLM provider
• Supports missing value handling
• Includes outlier detection and removal
• Offers multiple scaling methods (Z-score, min-max, robust)
• Supports filtering, merging, and feature engineering
• Works offline without cloud dependency
• Handles data type conversion and transformation

1. 1.Import pandas, numpy, and sklearn libraries
2. 2.Clean data: remove duplicates, fill missing values, remove outliers
3. 3.Normalize data using Z-score, min-max, or robust scaling
4. 4.Reshape data with melt/pivot operations
5. 5.Filter and subset data by condition or value
6. 6.Merge datasets via join or concatenate