cmd-plotting

To generate a colour-magnitude diagram from a photometric catalog, use Python with matplotlib to plot observational data and save the results as a publication-ready PNG file. The Skill processes input data and enforces consistent axis labeling.

Yes, you can use parquet files to create astronomy data visualizations by passing input.parquet directly to the plotting script. The script processes the parquet data to generate colour-magnitude diagrams as output PNG files.

The best way to plot large photometric samples in a colour-magnitude diagram is using hexbin density representations. This approach visualizes dense observational data effectively and produces publication-ready outputs via matplotlib.

Yes, matplotlib supports reproducible plotting choices for observational astronomy data by enforcing consistent axis labeling and explicit units. This ensures your colour-magnitude diagrams maintain consistent plotting conventions across teaching materials.

Yes, you need Python to produce publication-ready CMD plots because the Skill requires Python and matplotlib to process photometric catalogs. Running the plotting script generates consistent colour-magnitude diagram outputs.