**Multi-Criteria Project Analysis Code**

Welcome to the Multi-Criteria Project Analysis Code! This code is designed to help you analyze and optimize projects based on various criteria. It can be a valuable tool for project managers, decision-makers, and analysts who need to make informed decisions regarding project selection.

**Instructions for Using the Code:**

**1. Requirements:**
   - This code is written in Python, so you'll need a Python interpreter installed on your system. You can download Python from [python.org](https://www.python.org/downloads/).

**2. Installation:**
   - Download the code files from [GitHub Repository URL].
   - Extract the code to a directory of your choice.

**3. Data Preparation:**
   - Prepare your project data in CSV format. You will need two CSV files:
     - `project_criteria.csv`: This file should contain information about project criteria, including project names, costs, and criteria values.
     - `project_sets.csv`: This file should define sets of projects, indicating which projects belong to each set using 'X' or any other delimiter.

**4. Running the Code:**
   - Open a terminal or command prompt.
   - Navigate to the directory where you extracted the code.
   - Run the code using the following command:

     ```
     python project_analysis.py
     ```

**5. Analyzing Projects:**
   - The code will read your project data and perform multi-criteria analysis.
   - It will display project costs, criteria, and the best set of projects based on the defined criteria weights.

**6. Customization:**
   - You can customize the code by adjusting the criteria weights in the code to match your specific project evaluation needs.

**7. Output:**
   - The code will provide you with the best set of projects and their total score based on the given criteria.

**8. Enjoy Your Informed Decision-Making:**
   - Use the insights from this code to make informed decisions about project selection, optimization, and resource allocation.

**9. Support and Contributions:**
   - If you encounter issues or want to contribute to the code, please visit our [GitHub repository URL] and follow the instructions.

Happy project analysis and optimization!