Metadata-Version: 2.4
Name: auto_lm
Version: 0.1.0
Summary: Advanced Automated EDA Library for comprehensive data analysis
Home-page: https://github.com/yourusername/auto_lm
Author: Louati Mahdi
Author-email: your_email@example.com
Project-URL: Bug Reports, https://github.com/yourusername/auto_lm/issues
Project-URL: Source, https://github.com/yourusername/auto_lm
Keywords: eda exploratory-data-analysis data-science statistics machine-learning
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=1.3.0
Requires-Dist: numpy>=1.21.0
Requires-Dist: scipy>=1.7.0
Requires-Dist: tabulate>=0.8.9
Requires-Dist: statsmodels>=0.12.0
Requires-Dist: seaborn>=0.11.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license-file
Dynamic: project-url
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# auto_lm - Advanced Automated EDA Library

[![PyPI version](https://badge.fury.io/py/auto_lm.svg)](https://badge.fury.io/py/auto_lm)
[![Python 3.7+](https://img.shields.io/badge/python-3.7+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

**auto_lm** is a powerful Python library for automated Exploratory Data Analysis (EDA) that provides comprehensive statistical analysis with just a few lines of code.

## 🚀 Features

- **Comprehensive Analysis**: Univariate, Multivariate, Correlation, and Causation analysis
- **Statistical Tests**: Normality tests, ANOVA, Chi-square, and more
- **Automated Insights**: Detect outliers, multicollinearity, and data quality issues
- **Beautiful Output**: Results displayed in customized, easy-to-read tables
- **Google Colab Ready**: Works seamlessly in Google Colab environments
- **Target Analysis**: Special analysis for supervised learning scenarios

## 📦 Installation

```bash
pip install auto_lm
