Metadata-Version: 2.4
Name: ibrahim-dataprep
Version: 0.1.3
Summary: Autonomous Data Science Assistant for Instant Data Preparation.
Home-page: https://github.com/ibrahimmcx/dataprep
Author: ibrahimmcx
Author-email: ibrahimmcx@github.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: typer
Requires-Dist: rich
Requires-Dist: python-dateutil
Requires-Dist: openpyxl
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# DataPrep AI 🤖

**Autonomous Data Science Assistant for Instant Data Preparation.**

DataPrep AI is a CLI tool designed to transform raw, messy datasets into clean, ML-ready data with a single command. It automatically handles missing values, encodes categories, normalizes features, and detects anomalies.

## 🚀 Key Features

- **Autonomous Cleaning**: Smart handling of missing values (mean/median/mode) and duplicate removal.
- **Intelligent Encoding**: Automated One-Hot and Label encoding based on feature cardinality.
- **Goal-Oriented Prep**: Optimization for `prediction`, `classification`, or `analysis`.
- **Date Parsing**: Automatically detects and transforms date-like strings to datetime objects.
- **Modern CLI**: Beautiful, colorized logs and progress indicators.

## 📦 Installation

```bash
pip install ibrahim-dataprep
```

## 🛠 Usage

### Auto Clean
Analyze and clean a dataset with one command:
```bash
dataprep auto your_data.csv
```

### Goal-Specific Preparation
Prepare data specifically for machine learning:
```bash
dataprep auto your_data.csv --goal prediction
```

### Custom Fixes (Experimental)
Interact with your data using natural language:
```bash
dataprep fix "fix the missing values in this file" your_data.csv
```

## 📄 License
MIT License. See [LICENSE](LICENSE) for details.
