Metadata-Version: 2.1
Name: SyntheticDataAlchemy
Version: 0.1.0
Summary: A package for generating synthetic data
Home-page: https://github.com/phillip1029/DataAlchemy
Author: Phillip Peng
Author-email: ppeng08@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: category-encoders

# SyntheticDataAlchemy

SyntheticDataAlchemy is a Python package for generating synthetic data that preserves the statistical properties and relationships of the original dataset.

## Installation

You can install SyntheticDataAlchemy using pip:

```
pip install SyntheticDataAlchemy
```

## Usage

Here's a simple example of how to use SyntheticDataAlchemy:

```python
import pandas as pd
from SyntheticDataAlchemy import generate_synthetic_data

# Load your original data
original_df = pd.read_csv('your_data.csv')

# Generate synthetic data
synthetic_df = generate_synthetic_data(original_df, n_samples=1000)

# Save the synthetic data
synthetic_df.to_csv('synthetic_data.csv', index=False)
```

## Features

- Generates synthetic data for both numerical and categorical features
- Preserves statistical properties of the original data
- Maintains relationships between features
- Handles missing data

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License.
