A Python stacked-percentage bar-chart workflow that converts percentage strings, computes a remainder category and exports a chart image.
Tasks
Convert percentage strings to numeric values and build a structured pandas DataFrame.
Sum the known category shares and calculate the remainder as 100 minus that total.
Build stacked Matplotlib bars with cumulative bottom values and readable labels/legend.
Export the figure as a 300-dpi PNG and close it after display.
Inputs
Aligned period/group labels and known category percentages as strings or numeric values.
Category names, chart labels and a destination image path.
A compatible Python plotting environment and available fonts for the selected label language.
Outputs
A DataFrame with numeric shares, current_total, cat_remainder and final_check.
A stacked percentage chart, with the source example saving stacked_ratio_analysis.png at 300 dpi.
Limitations and checks
The sample data are placeholders to replace, not findings from a real dataset.
Computing final_check after setting remainder to 100 minus the known total is arithmetic consistency, not independent input validation. Reject or investigate negative remainder, invalid values and missing/misaligned data.
The example converter does not handle every locale/format or malformed string; add validation appropriate to the actual input.
The default plot dimensions/colors/legend position are examples, not automatic readability guarantees.
Do values use the same 0–100 percentage scale and align with labels?
Are malformed/missing/non-finite or negative values handled before plotting?
Is the known total at most 100 within an explicit tolerance, with a meaningful remainder?
Do cumulative bottoms and legend labels match the actual categories?
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