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time-series-and-categorical-analysis

Clean percentage fields and analyze time-series or categorical Excel data into trends, tiers, and forecasts.

2|Updated May 19, 2026
Search Tags:#data visualization#time series#excel#forecasting#categorical analysis#percentage cleaning#tiered modeling
One-click install
npx skills add https://github.com/aiyinluya/SenseNova-Skills-Studio --skill time-series-and-categorical-analysis-aiyinluya
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: time-series-and-categorical-analysis
Source: https://github.com/aiyinluya/SenseNova-Skills-Studio/tree/main/skills/sn-da-excel-workflow/capability/excel-data-analysis/time-series-analysis
Command: npx skills add https://github.com/aiyinluya/SenseNova-Skills-Studio --skill time-series-and-categorical-analysis-aiyinluya

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps you turn messy time-series or categorical Excel data into cleaned percentage metrics, quantified trends, tier-based modeling, and a single high-resolution visual report.

Core Features & Use Cases

  • Percentage cleaning: Converts percent strings into numeric values while handling empty and malformed entries.
  • Trend and change detection: Computes point-to-point differences and labels direction (up/down/stable).
  • Tiered modeling & forecasting: Groups categorical entities into high/mid/low tiers and applies tier-specific growth rates to generate predictions.
  • High-resolution visualization report: Produces a combined figure (stacked area, current vs forecast bars, growth-rate distribution, and growth-amount breakdown).
  • Use case: Monitor KPI performance over time (e.g., channel share and growth) and produce an exec-ready forecast snapshot for business decision-making.

Quick Start

Use the skill to analyze the attached spreadsheet 'data.xlsx' and generate a high-resolution 'trend_analysis_report.png' based on your time column and indicator share columns.

Frequently Asked Questions about time-series-and-categorical-analysis

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

FAQPage Schema
How do I forecast time-series data from an Excel spreadsheet with percentage strings?▼

To forecast time-series data in Excel, the Skill cleans percentage strings into numeric values, computes point-to-point differences, and applies tier-specific growth rates to generate predictions for your dataset.

What is the best way to visualize categorical data trends and growth tiers for KPI monitoring?▼

Visualizing categorical data trends is done by generating a high-resolution combined figure using matplotlib and seaborn, featuring stacked areas, current versus forecast bars, and growth-rate distributions for KPI monitoring.

How do I clean malformed percentage fields in Excel data before computing diffs?▼

Cleaning malformed percentage fields is handled automatically by converting percent strings into numeric values while resolving empty entries, ensuring accurate computation of point-to-point differences for trend analysis.

Can I use pandas and seaborn for tiered modeling and categorical analysis on Excel workbooks?▼

Yes, you can use pandas and seaborn for tiered modeling by loading your Excel workbook via pandas, grouping categorical entities into high, mid, and low tiers, and exporting visualizations with seaborn.

Does time-series forecasting with tiered growth modeling work for categorical performance grading?▼

Time-series forecasting with tiered growth modeling works for categorical performance grading by applying tier-specific growth rates to grouped entities, producing quantified predictions for decision-support scenarios.

Why does my Excel trend analysis report fail when grouping categorical entities into tiers?▼

Excel trend analysis may fail if the workbook lacks proper time or group dimensions, as the Skill requires these structural elements to compute tier thresholds and apply tier-specific growth rates for forecasting.

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