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The script allows users to visualize data in a dynamic and interactive way.\n\n## Requirements\n\n- Python 3.x\n- Plotly library (`pip install plotly`)\n\n## Usage\n\n1. Install the necessary Python packages:\n\n   ```bash\n   pip install plotly\n   ```\n\n2. Modify the script by updating the `categories` and `values` lists with your own data:\n\n    ```python\n    categories = ['Category A', 'Category B', 'Category C', 'Category D']\n    values = [23, 45, 56, 78]\n    ```\n\n3. Run the Python script:\n\n    ```bash\n    python interactive_bar_graph.py\n    ```\n\n4. The script will generate an interactive bar graph using Plotly. The graph will be displayed in your default web browser.\n\n## Customization\n\n- Modify the `categories` and `values` lists to represent your own dataset.\n- Adjust colors, titles, axes labels, and other graph properties by modifying the parameters in the script's `update_layout` and `go.Figure` sections.\n\n## Example\n\nHere's a snippet of how to create the bar graph:\n\n```python\nimport plotly.graph_objects as go\n\n# Sample data\ncategories = ['Category A', 'Category B', 'Category C', 'Category D']\nvalues = [23, 45, 56, 78]\n\n# Create a bar graph\nfig = go.Figure(data=[go.Bar(\n    x=categories,\n    y=values,\n    marker_color='skyblue'  # Change color as needed\n)])\n\n# Update graph layout for better visualization\nfig.update_layout(\n    title='Interactive Bar Graph',\n    xaxis=dict(title='Categories'),\n    yaxis=dict(title='Values'),\n    hovermode='closest'\n)\n\n# Show the interactive graph\nfig.show()\n```\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmusatahawar%2Finteractive-bar-chart","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmusatahawar%2Finteractive-bar-chart","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmusatahawar%2Finteractive-bar-chart/lists"}