plot

Plot

Generate a data visualization by producing and executing a Python script (Matplotlib/Seaborn) based on the prompt, surrounding context, and a referenced data file.

Input

• File path: the file being processed.
• Surrounding text: the paragraph or block where the <@plot: ...> tag appears.
• Prompt: description of the desired visualization, including chart type, styling, and any specific formatting instructions.

Workflow

1. Read the surrounding text and prompt.
2. Identify the data file from the prompt's context references ( ``). Read the data file to understand its structure (columns, types, number of rows).
3. Identify the output path from the prompt's context references. If none is specified, save the plot in the same directory as the source file with a name derived from the prompt (e.g., plot_completion_time.png).
4. Generate a self-contained Python script that:
   • Reads the data file (using pandas for CSV/TSV/Excel, or appropriate libraries for other formats).
   • Produces the requested visualization using matplotlib and/or seaborn.
   • Applies any styling or formatting instructions from the prompt.
   • Saves the figure to the output path with dpi=300 and bbox_inches='tight'.
5. Execute the script in a single Bash command:

   python -c "
   <generated script here>
   "
   

6. Verify the output file was created.
7. Replace the <@plot: ...> tag with a format-appropriate image reference:
   • Markdown (.md): ![description](output_path.png)
   • LaTeX (.tex): \includegraphics{output_path.png}
   • other format, try to determine by yourself.

Context References

The prompt may contain context references wrapped in double backticks ( ``). These point to external resources.

• As data source: The reference points to the data file to visualize. E.g., <@plot: bar chart using ``data/results.csv``> -- read data/results.csv as the input data.
• As output path: The reference specifies where to save the generated plot. E.g., <@plot: line chart, save to ``figures/trend.png``> -- save the plot to figures/trend.png.
• Resolve references relative to the source file's directory unless an absolute path is given.
• Remove the delimiters from the output.
• If the input tag does not contain any context reference, ask user the elaborate.

Rules

• Always read the data file first to understand its structure before generating the script. Do not assume column names or data types.
• Generate a complete, self-contained Python script. Do not rely on variables or state from previous executions.
• Run the script in a single Bash invocation. Do not split into separate calls.
• Use python (not python3) for execution.
• Default to clean, publication-ready styling: white background, legible font sizes, clear axis labels.
• If the prompt does not specify a chart type, infer the most appropriate one from the data structure and surrounding context.
• If the data file cannot be found or read, warn the user and skip.
• If execution fails, report the error and include the generated script so the user can debug.
• Sanitize the output filename: lowercase, underscores, no spaces or special characters (unless an explicit output path is given via context reference).
• The <@plot: ...> tag and all delimiters must be removed in the output.