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aiyinluya
aiyinluyaCOMMUNITY
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stacked-chart-visualization

Converts percentage strings to numeric shares and plots validated stacked bar charts as PNGs.

2|Updated May 19, 2026
Search Tags:#data visualization#pandas#data cleaning#matplotlib#seaborn#stacked bar chart#percentage conversion
One-click install
npx skills add https://github.com/aiyinluya/SenseNova-Skills-Studio --skill stacked-chart-visualization-aiyinluya
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stacked-chart-visualization
Source: https://github.com/aiyinluya/SenseNova-Skills-Studio/tree/main/skills/sn-da-excel-workflow/capability/excel-data-visualization/stacked-chart-visualization
Command: npx skills add https://github.com/aiyinluya/SenseNova-Skills-Studio --skill stacked-chart-visualization-aiyinluya

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you transform categorical percentage data (including percentage strings) into a validated stacked bar chart, optionally inferring a remaining category so all parts sum to 100%.

Core Features & Use Cases

  • Percentage string conversion: Converts values like "23.21%" into numeric floats for computation.
  • Structured DataFrame building: Packs cleaned ratios into a tabular format suitable for vectorized calculations and plotting.
  • Remainder dimension completion: Computes an implied “other/remainder” category from the 100% constraint and performs a completeness check.
  • Stacked bar visualization: Uses layered bars with proper bottom offsets and styling to clearly show composition changes across groups/time.
  • Chart export: Saves a high-resolution PNG for sharing or reporting.

Quick Start

Use the stacked-chart-visualization skill to generate a stacked bar chart from your percentage-by-category dataset like time-series category shares that include percent strings (e.g., "24.53%") and automatically infer the remaining “other” portion.

Frequently Asked Questions about stacked-chart-visualization

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

FAQPage Schema
How do I convert percentage strings like "24.53%" into a stacked bar chart with pandas?▼

To build a stacked bar chart, this Skill converts percentage strings into numeric floats, structures them into a pandas DataFrame, and uses matplotlib with correct bottom offsets to plot the composition changes across groups or time.

How do I automatically infer the remaining category when stacked percentages don't sum to 100%?▼

When stacked percentages do not sum to 100%, this Skill computes an implied remainder category from the 100% constraint, performs a completeness check, and adds the missing portion to your dataset before plotting.

What's the best way to visualize multi-dimensional composition changes for a business presentation?▼

The best way to visualize composition changes is a validated stacked bar chart, which this Skill generates by layering bars with proper bottom offsets and exporting a high-resolution PNG suitable for reporting and dashboards.

Can I use seaborn to plot stacked categorical share data from an Excel-like report?▼

Yes, this Skill supports Excel-like reporting scenarios by cleaning percentage-string categorical share data, structuring it for vectorized calculations, and generating layered stacked bar visualizations using matplotlib and seaborn.

How do I export a high-resolution stacked chart image for marketing analytics dashboards?▼

You can export a high-resolution PNG of your stacked chart by passing cleaned and structured percentage data to this Skill, which builds the layered visualization and saves the image for sharing in marketing analytics dashboards.

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