Data Tune 🚀

Data Tune is a powerful ML Ops tool that provides an intuitive interface for data preparation and cleaning of tabular data files such as CSV, XLS, and XLSX. It streamlines the data preparation process, ensuring clean and well-structured data for model training.

Features

• ✨ Null Value Replacement: Easily replace missing values with custom data.
• 🔄 Duplicate Row Removal: Identify and remove duplicate rows from your dataset.
• 🗑️ Missing Value Elimination: Quickly eliminate rows with missing data.
• 🔡 Text Conversion to Lowercase: Transform text data to lowercase, enhancing consistency.
• ❌ Column Deletion: Select and remove specific columns from your dataset.
• 🔀 Column Sorting: Sort columns in ascending or descending order to enhance data organization.
• 📝 Column Capitalization: Capitalize the first letters of text data in chosen columns.

Getting Started

Installation

1. Clone the repository:

   git clone https://github.com/anxkhn/data-tune.git
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Run the Streamlit app:

   streamlit run app.py
   

Usage

1. Upload your data file (CSV, XLS, XLSX) using the provided file uploader.

2. Select the sheet to work with (if applicable).

3. Choose from a variety of data cleaning operations to tune your data.

4. Download the cleaned data in the same format as your input file or in CSV format.

License

This project is licensed under the MIT License.

Acknowledgments

• We'd like to thank the Streamlit community for making it easy to create this user-friendly ML Ops tool.

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Data Tune is proudly brought to you by Anas Khan.