AI Research Data Processor 📊

An intelligent Python application with a Graphical User Interface (GUI) to process and standardize unstructured text data generated by AI into a structured Excel format. This project was developed as a tool to streamline academic research by automating the process of data entry.

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✨ Key Features

• GUI for Easy Use: A modern, user-friendly graphical interface built with PySide6 for intuitive data processing.
• Flexible Data Parsing: Reads data from a simple text file (.txt) with a user-defined delimiter (%).
• Intelligent Delimiter Handling:
  • Maxsplit Logic: Processes rows with inconsistent column counts by intelligently placing all remaining content into the last column.
  • User Control: Provides a checkbox to toggle this feature on or off.
• Duplicate Header Management: Automatically detects and skips repeated header rows in the data, preventing redundant entries.
• Error & Warning Reporting: Provides a comprehensive report of any issues (like missing files, inconsistent column counts, or extra delimiters) in a pop-up window after processing.
• Multilingual Interface: Supports multiple languages, including English, Persian, and others, through a simple dropdown menu.
• Excel Output: Converts the processed data into a clean, ready-to-use Excel file (.xlsx) using the pandas library.

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🖼️ User Interface

Here is a screenshot of the graphical interface in action:

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🛠️ Technologies Used

• Python 3.13.5: The core programming language for the project.
• PySide6: A professional, cross-platform framework for creating the GUI.
• pandas: An essential library for data manipulation and creating DataFrames.
• openpyxl: A library used by pandas to read and write Excel files (.xlsx).
• os & sys: Standard Python modules for interacting with the operating system and file paths.

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⚙️ Installation

To run this project, you need to have Python installed. It is highly recommended to use a virtual environment.

1. Clone the repository: You can clone the repository using the following command:

   git clone https://github.com/ahmadreza-hajtalebi/ai-text-to-excel-tool.git

   Alternatively, you can download the project files directly from the repository's main page.

2. Install the required libraries: The project uses a requirements.txt file to list all dependencies. Install them with a single command:

   pip install -r requirements.txt

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🚀 How to Use

1. Prepare your input file:

   • Create a text file (e.g., input_data.txt) in the data/ folder.
   • The first line must be the column headers, separated by a % delimiter.
   • Subsequent lines should contain your data, also separated by a %.
   • Example format:

     Poem_Title%Verse_ID%Material_Mentioned%Material_Property
     The Raven%7%Oak%Durability%Toughness
     The Charge of the Light Brigade%22%Steel%__
     

2. Get structured data from AI:

   • To get data from an AI that is compatible with this script, use the prompt template provided in the prompts/ folder.
   • The template helps you define the research subject, columns, and required output format.
   • You can find the template file here: ai_prompt_template.txt

3. Run the GUI:

   • Navigate to the gui/ directory.
   • Execute the main application script:

     python main_app.py

4. Process your data:

   • Use the "Browse" buttons to select your input and output file paths.
   • Enter the exact number of columns (e.g., 4).
   • (Optional) Check the box to ignore extra delimiters.
   • Click the "Process Data" button.

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📂 Project Structure

ai-text-to-excel-tool/
├── core/
│   └── data_processor.py        # Core logic for data parsing and Excel output
├── gui/
│   ├── main_app.py              # Main GUI application script
│   └── translations.py          # Dictionary for multilingual support
├── data/
│   ├── input_data.txt           # Example input file
│   └── e.g. example image.png   # Screenshot of the GUI
├── prompts/                     # Directory for AI prompt templates
│   └── ai_prompt_template.txt   # Template for getting structured AI output
├── .gitignore
├── requirements.txt             # Project dependencies
└── README.md                    # Project documentation

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🗺️ Future Roadmap

• Add supplementary tools for advanced Excel management (e.g., automatic column sizing, data sorting, and filtering).
• Add More Languages: Expand the translation dictionary to include more languages.
• Interactive Error Display: Display errors and warnings directly in a text widget on the GUI instead of a pop-up message box.
• Merge Existing Excel Data: Add an option to merge new data into an existing Excel file instead of creating a new one.
• Dark/Light Theme: Implement a dark mode or other visual themes.

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👨‍💻 About the Author

Ahmadreza Haj Talebi - Aerospace Engineering student with a passion for programming and space.

• GitHub Profile
• LinkedIn Profile
• Vortiqon Science (YouTube Channel)

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