⚡ ML Preprocessing CLI

A beginner-friendly Command-Line Interface (CLI) tool to automate essential data preprocessing tasks in machine learning workflows — from missing value handling to encoding and feature scaling.

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🎯 Features

• 📊 Dataset summary and null value statistics
• 🧹 Missing value handling (drop or impute)
• 🧠 Categorical encoding (Label Encoding, One-Hot Encoding)
• 📏 Feature scaling (Standard or Min-Max)
• 📥 Export cleaned dataset to CSV
• 🧪 Interactive terminal menu — no notebook required!

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🧰 Installation

Make sure you have Python 3.10+ installed.

git clone https://github.com/mohakamitpatel/ML_Preprocessing_CLI.git
cd ML_Preprocessing_CLI
pip install -r requirements.txt

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🗂️ Project Structure

📂 ML_Preprocessing_CLI
├── data/ → Sample datasets (optional)
├── data_input.py → Reads the dataset
├── data_description.py → Summarizes the dataset
├── imputation.py → Missing value imputation
├── categorical.py → Encoding categorical features
├── feature_scaling.py → Feature scaling logic
├── download.py → Saves the cleaned dataset
├── main.py → CLI entry-point
└── requirements.txt → Required Python libraries

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💻 How to Use

Run the CLI from the terminal:

python main.py

You will be guided through a step-by-step menu to:

1. Upload dataset
2. Handle missing values
3. Encode categorical variables
4. Scale features
5. Download processed file

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🔍 Example Usage

$ python main.py
📁 Please enter the path to your CSV file: data/sample.csv

✅ Dataset Loaded!
Choose an option:
[1] Describe Data
[2] Handle Missing Values
[3] Encode Categorical Features
[4] Scale Features
[5] Export Cleaned Data

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📦 Dependencies

• pandas
• numpy
• scikit-learn
• tabulate
• termcolor

Install via:

pip install -r requirements.txt

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🎥 Demo Preview

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💡 Future Ideas

• Add support for command-line arguments
• Integrate GUI using Tkinter or Streamlit
• Auto EDA with visualizations
• Upload directly from URL or cloud storage

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🤝 Contributing

Pull requests are welcome!
If you have suggestions or find bugs, feel free to fork and improve.

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✌️ Peace out. Built with code, not caffeine — Mohak