data-automation-kit 2.0.1

A comprehensive Python package for automated data loading, cleaning, visualization, and quality checks with AI integration

Data Automation Kit v2.0 🚀

One line to rule them all: quick_analyze() — Your complete data analysis in one function!

🎯 What's New in v2.0

• 🚀 One-Command Analysis: quick_analyze() does everything
• 🎨 Professional Visualizations: Beautiful, publication-ready charts
• 🤖 Enhanced AI Integration: Smarter insights with Groq
• 📊 Smart Data Detection: Auto-identifies data types and patterns
• 🛠️ Robust Architecture: Clean, maintainable code structure

⚡ Quick Start

Installation

```bash pip install data-automation-kit ```

Usage (30 seconds)

```python from data_automation_kit import quick_analyze quick_analyze() ```

🎨 What You Get

Feature	Description	Output
Smart Data Loading 📥	CSV, Excel, JSON, SQL, or sample data	Clean DataFrame
Auto Quality Checks 🔍	Data quality scoring	Quality report
Intelligent Cleaning 🧹	Handle missing values, duplicates	Cleaned data
Beautiful Visualizations 📊	Automatic charts	PNG files
AI-Powered Insights 🤖	Analysis & recommendations	Text report

📚 Complete Examples

One-Line Magic

```python from data_automation_kit import quick_analyze quick_analyze() ```

Step-by-Step Control

```python from data_automation_kit import DataLoader, AutoVisualizer

loader = DataLoader() data = loader.load_csv("your_data.csv")

visualizer = AutoVisualizer(data) visualizer.create_comprehensive_dashboard() ```

Interactive Session

```python from data_automation_kit import InteractiveAnalyzer InteractiveAnalyzer().start_interactive_session() ```

🎯 Key Features

Smart Data Loading

• CSV, Excel, JSON, SQL
• Built-in sample datasets
• Smart file type detection
• Graceful error handling

Professional Visualizations

• Correlation heatmaps
• Histograms, box plots, density plots
• Categorical charts
• Business dashboards

AI-Powered Intelligence

• Dataset insights
• Cleaning recommendations
• Suggested charts
• Business recommendations

🛠️ Installation

From PyPI

```bash pip install data-automation-kit ```

From Source

```bash git clone https://github.com/yourusername/data-automation-kit cd data-automation-kit pip install -e . ```

📖 Documentation

Basic Usage

```python from data_automation_kit import DataLoader, AutoVisualizer

loader = DataLoader() data = loader.load_csv("data.csv")

data = loader.create_sample_data("sales")

viz = AutoVisualizer(data) plots = viz.create_comprehensive_dashboard()

print(f"Created {len(plots)} visualizations!") ```

AI Integration

```python from data_automation_kit import GroqAnalyzer report = GroqAnalyzer().generate_data_report(data) print(report) ```

🎨 Visualization Gallery

``` data_visualizations/ ├── 01_correlation_heatmap.png ├── 02_distribution_age.png ├── 03_categorical_department.png ├── 04_missing_values.png ├── 05_data_types.png └── ...and more! ```

🔧 Requirements

• Python 3.7+
• pandas, numpy, matplotlib, seaborn
• sqlalchemy
• groq
• scikit-learn, scipy

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md.

📄 License

MIT License — see LICENSE.

🆘 Support

📧 Email: [e-mail]
🐛 GitHub Issues
💬 Discussions

⭐ If you find this useful, please star the repo! Built with ❤️ for the data community.