Dataset Analysis EDA 📊

Dataset Analysis EDA is a Python-based tool designed for comprehensive exploratory data analysis (EDA) and machine learning model evaluation. This intelligent system processes various dataset formats, performs data preprocessing, conducts statistical analysis, and generates insightful visualizations.

🌟 Key Features

• 📄 Multi-format Data Processing: Handle various file formats including CSV and Excel.
• 🧹 Automated Data Preprocessing: Includes grammar correction, handling of missing values, and feature encoding.
• 📊 Comprehensive EDA: Generates statistical summaries, correlation analyses, and various visualizations.
• 🤖 Machine Learning Model Evaluation: Implements Random Forest classification with cross-validation.
• 📈 Feature Importance Analysis: Provides insights into the most influential features in the dataset.
• 📉 Advanced Visualizations: Includes histograms, heatmaps, confusion matrices, and feature importance plots.
• 🛠️ Robust Error Handling: Comprehensive error management to ensure smooth operation with various datasets.

📦 Project Structure

├── AUTHORS.md
├── DatasetAnalysis.py
├── FUNDING.yml
├── INFO.md
├── LICENSE.md
├── PRIVACY.md
├── PlanilhaModelagem.csv
├── PlanilhaModelagem.xlsx
├── README.md
├── images
│   ├── screenshot-01.png
│   ├── screenshot-02.png
│   ├── screenshot-03.png
│   ├── screenshot-04.png
│   ├── screenshot-05.png
│   ├── screenshot-06.png
│   ├── screenshot-07.png
│   ├── screenshot-08.png
│   ├── screenshot-09.png
│   ├── screenshot-10.png
│   ├── screenshot-11.png
│   ├── screenshot-12.png
│   ├── screenshot-13.png
│   └── screenshot-14.png
└── requirements.txt

🏃‍♂️ How to Use

1. Clone the Repository:

   git clone https://github.com/Takk8IS/DatasetAnalysisEDA.git
   cd DatasetAnalysisEDA

2. Install Dependencies:

   pip install -r requirements.txt

3. Run the Analysis:

   python DatasetAnalysis.py PlanilhaModelagem.xlsx

4. Review the Results:

   • The script will generate various plots and print analysis results in the console.
   • Review the generated visualizations for insights about your dataset.

Contributing

We welcome contributions from the community! If you'd like to contribute, please:

1. Fork the repository.
2. Create your feature branch (git checkout -b feature/AmazingFeature).
3. Commit your changes (git commit -m 'Add some AmazingFeature').
4. Push to the branch (git push origin feature/AmazingFeature).
5. Open a Pull Request.

Donations

If this project has been helpful, consider making a donation:

USDT (TRC-20): TGpiWetnYK2VQpxNGPR27D9vfM6Mei5vNA

Your support helps us continue to develop innovative data analysis tools.

License

This project is licensed under the CC-BY-4.0 License. See the LICENSE file for more details.

About Takk™ Innovate Studio

Leading the Digital Revolution as the Pioneering 100% Artificial Intelligence Team.

• Author: David C Cavalcante
• LinkedIn: linkedin.com/in/hellodav
• X: @Takk8IS
• Medium: takk8is.medium.com
• Website: takk.ag