Data Visualization Functionality Explained
Supported Chart Types
THESIS Agent's data visualization capabilities are quite comprehensive, and the types of charts that can be generated include:
- Base Chart:Bar charts (bar), line charts (line), pie charts (pie)
- Advanced Charts:Scatter, heatmap.
- Portfolio Charts:Supports visual comparison of multiple data series
- Interactive charts:Dynamic visualizations that can be scaled and filtered
Operation Guide
- Prepare the data file:Data should be saved in CSV format, containing column names and values
- Configuration Script:Edit the scripts/visualize_data.py file to set:
- data_file: data file path
- chart_type: desired chart type
- style_config: optional visual style parameter
- Run the script:Execute python scripts/visualize_data.py in the terminal
- View Results:The output file is saved in the output/charts directory
Recommendations for advanced use
- Large dataset processing: pre-sampling or aggregation can be considered for large amounts of data
- Style customization: adjust colors, labels and other visual elements by modifying configuration files
- Multi-chart combination: you can set up to generate an overall report with multiple sub-charts
- Export options: supports multiple formats for easy embedding into papers or presentations
This answer comes from the articleTHESIS Agent: An Intelligent Tool to Assist in Writing Academic PapersThe
May not be reproduced without permission:AI productivity tools " What chart types are supported by THESIS Agent's data visualization feature? How does it work?
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