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MichaelYang-lyx
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stacked-chart-visualization

Convert percentage strings into numeric values and render stacked bar charts.

110|3|Updated Feb 26, 2026
Search Tags:#visualization#pandas#excel#data-analysis#percentages#chart#stacked-chart
One-click install
npx skills add https://github.com/MichaelYang-lyx/AIDABench --skill stacked-chart-visualization-michaelyang-lyx
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stacked-chart-visualization
Source: https://github.com/MichaelYang-lyx/AIDABench/tree/main/skills/sn-da-excel-workflow/capability/excel-data-visualization/stacked-chart-visualization
Command: npx skills add https://github.com/MichaelYang-lyx/AIDABench --skill stacked-chart-visualization-michaelyang-lyx

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps you transform percentage strings into numeric values, unify multi-category data with missing dimensions, and generate stacked bar charts to visualize how compositions change over time or categories.

Core Features & Use Cases

  • Percentage normalization: convert percentage strings to numeric values for accurate calculations.
  • Structured data assembly: build a DataFrame with time or category dimensions and category proportions.
  • Missing-dimension inference: compute the remaining category percentage to ensure a complete 100% view and validate data integrity.
  • Visualization: render stacked bar charts with layered categories to reveal trends.

Quick Start

Run the provided example to generate a stacked chart from sample percentage data.

Frequently Asked Questions about stacked-chart-visualization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a stacked bar chart from percentage strings in pandas?▼

This skill converts percentage strings to numeric values, assembles a structured pandas DataFrame with time or category dimensions, and renders a stacked bar chart to visualize composition changes.

How do I visualize data when one category percentage is missing?▼

To visualize data with a missing category percentage, this skill computes the remaining dimension to ensure a 100% total, validates data integrity, and includes the inferred segment in the stacked bar chart.

Can I use matplotlib or seaborn to plot multi-category percentages from Excel data?▼

Yes, this skill uses pandas to structure Excel data and leverages matplotlib or seaborn plotting libraries to render stacked bar charts for multi-category percentage visualizations.

What is the best way to normalize percentage strings for data analysis?▼

The best way to normalize percentage strings for data analysis is to transform them into numeric values, which ensures accurate calculations and structural data assembly before visualization.

Does this stacked chart visualization validate that category proportions total 100 percent?▼

Yes, this skill validates data integrity by recomputing the remaining category percentage to ensure a complete 100% total before rendering the stacked bar chart.

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