Custom Categorized Data Visualization -- 2
Budget: $10 – $30 USD
I have a numeric data set that must be reordered in a very specific, category-based sequence rather than standard ascending or descending sorting. After the data is in that custom order, I need a handful of clear, publication-ready graphs to illustrate the results and trends that emerge from the new arrangement.
The category logic is already defined; your task is to apply it accurately, verify the new ordering, and then generate concise visualizations—think bar charts, line plots, or any chart type that best conveys the story hidden in the numbers. I typically work with Excel and Python (pandas, matplotlib or seaborn), but I’m open to whichever tool lets you complete the work cleanly and reproducibly.
Deliverables
• Sorted data file in its original format (plus CSV if conversion is needed)
• 3–5 high-resolution charts, each supplied as PNG and the native editable format (e.g., .xlsx or .ipynb)
• Brief note explaining the steps taken so I can replicate or extend the process later
Accuracy in applying the custom category order is the key success metric; the visual output should naturally reflect that revised structure.
The category logic is already defined; your task is to apply it accurately, verify the new ordering, and then generate concise visualizations—think bar charts, line plots, or any chart type that best conveys the story hidden in the numbers. I typically work with Excel and Python (pandas, matplotlib or seaborn), but I’m open to whichever tool lets you complete the work cleanly and reproducibly.
Deliverables
• Sorted data file in its original format (plus CSV if conversion is needed)
• 3–5 high-resolution charts, each supplied as PNG and the native editable format (e.g., .xlsx or .ipynb)
• Brief note explaining the steps taken so I can replicate or extend the process later
Accuracy in applying the custom category order is the key success metric; the visual output should naturally reflect that revised structure.