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A powerful and user-friendly CSV editor built with Streamlit, allowing users to upload, view, and dynamically edit CSV files directly in the browser.

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CSV Editor

A powerful and user-friendly CSV editor built with Streamlit, allowing users to upload, view, and dynamically edit CSV files directly in the browser. This tool is designed for quick data manipulation without the need for complex spreadsheets or additional software.

Features

  • Upload CSV Files: Easily upload any CSV file for instant editing.
  • Dynamic Editing: Make real-time changes to your data, including adding, deleting, and updating rows and columns.
  • Save Changes: Save the modified CSV file locally with the click of a button.
  • Simple and Intuitive: User-friendly interface built with Streamlit to simplify data manipulation tasks.

Installation

  1. Clone the repository:

    git clone https://github.com/varshith-Git/csv_editor.git
    cd csv_editor
    
  2. Install the required dependencies:

    pip install streamlit pandas
    

Usage

  1. Run the application:

    streamlit run app.py
    
  2. Open the link provided by Streamlit in your browser.

  3. Upload your CSV file and start editing. Once you're done, you can download the edited file directly.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes. Ensure your code follows the project's coding standards and is well-documented.

License

This project is licensed under the Apache License. See the LICENSE file for more information.

Author

Gudur Varshith
Data Engineer with expertise in data modeling, ingestion, and migration. Passionate about building innovative data solutions.

Acknowledgements

Thanks to the Streamlit community and contributors for providing the tools to make this project possible.

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A powerful and user-friendly CSV editor built with Streamlit, allowing users to upload, view, and dynamically edit CSV files directly in the browser.

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