Metadata-Version: 2.4
Name: etl-helper-kit
Version: 0.1.0
Summary: A Python package for data cleaning, preprocessing, visualization, and machine learning.
Author: Surthi Lakshmi
License: MIT
Keywords: python,data-science,machine-learning,data-cleaning,preprocessing,visualization
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: scikit-learn
Dynamic: license-file
Dynamic: requires-python

# DataKit

DataKit is a beginner-friendly Python package for data cleaning, preprocessing, visualization, machine learning, and evaluation.

## Features

- Data Cleaning
- Data Preprocessing
- Machine Learning Models
- Model Evaluation Metrics
- Data Visualization
- Utility Functions
- Built-in Datasets

## Installation

```bash
pip install datakit
```

Or install locally:

```bash
git clone https://github.com/yourusername/datakit.git

cd datakit

pip install .
```

## Example

```python
from datakit.datasets import DatasetLoader
from datakit.cleaning import DataCleaner

df = DatasetLoader.iris()

cleaner = DataCleaner(df)

cleaner.remove_duplicates()

print(cleaner.summary())
```

## Modules

- cleaning
- preprocessing
- modeling
- metrics
- visualization
- utils
- datasets

## Running Tests

```bash
pytest
```

## Requirements

- Python 3.9+
- pandas
- numpy
- matplotlib
- seaborn
- scikit-learn

## License

MIT License
