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data-analysis

Compute SaaS metrics and generate Streamlit dashboards from ingested data.

28|3|Updated Dec 10, 2025
Search Tags:#pandas#data-analysis#plotly#streamlit#polars#saas-metrics
One-click install
npx skills add https://github.com/ScientiaCapital/skills --skill data-analysis-scientiacapital
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/ScientiaCapital/skills/tree/main/active/data-analysis-skill
Command: npx skills add https://github.com/ScientiaCapital/skills --skill data-analysis-scientiacapital

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Executive teams often struggle to synthesize scattered data into actionable insights; this Skill automates executive-grade data analysis for dashboards and investor reports.

Core Features & Use Cases

  • Ingests data from CSV, Excel, JSON, Parquet, PDF, and more; cleans and standardizes data types and dates.
  • Calculates SaaS metrics (MRR, ARR, LTV, CAC, churn) and builds a cohort retention matrix.
  • Generates McKinsey-style visualizations and interactive dashboards in Streamlit for investor-ready storytelling.

Quick Start

Load your data, run SaaS metrics, and render executive visuals in a Streamlit dashboard.

Frequently Asked Questions about data-analysis

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

FAQPage Schema
How do I calculate SaaS metrics like MRR, ARR, and churn from raw data?▼

To calculate SaaS metrics like MRR, ARR, LTV, CAC, and churn, this Skill ingests and cleans your raw data, then computes the metrics and builds a cohort retention matrix for dashboard visualization.

Can I build a Streamlit dashboard for investor presentations using Python and Plotly?▼

Yes, you can build a Streamlit dashboard for investor presentations by generating McKinsey-style visualizations with Plotly and Altair, creating interactive executive-grade reports from your ingested data.

What file formats can I use for automated data ingestion and cleaning in pandas?▼

For automated data ingestion and cleaning, the Skill supports multiple file formats including CSV, Excel, JSON, Parquet, and PDF, standardizing data types and dates during the processing stage.

Do I need Python 3.11 and polars to run cohort analysis and generate executive visuals?▼

Yes, you need Python 3.11+ along with pandas and polars for data processing, plus Plotly or Altair for visuals, to run cohort analysis and render executive dashboards.

What is the best way to create a cohort retention matrix for SaaS analytics?▼

The best way to create a cohort retention matrix for SaaS analytics is to use this Skill to standardize your dates, compute retention metrics automatically, and render the matrix in an interactive Streamlit dashboard.

pandas vs polars for executive data analysis: which does this approach use?▼

This approach uses both pandas and polars together for data processing, leveraging both frameworks to clean data and compute SaaS metrics before rendering McKinsey-style visualizations.

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