Which programming languages and libraries does this skill support?

The skill primarily focuses on Python using Matplotlib, Seaborn, and Plotly, but it also provides full support for R using the ggplot2 library.

How does this differ from standard AI chart generation?

This skill focuses on 'storytelling,' meaning it applies narrative structures, removes unnecessary design clutter, and uses color theory to highlight insights rather than just decorating data.

Are the visualizations accessible?

Yes, the skill is programmed to use color-accessible palettes like Viridis or ColorBrewer and emphasizes high-contrast, clear typography for better readability.

Can I use this for business presentations?

Absolutely. It is specifically designed to cater to different audiences, including the ability to generate executive summaries that translate technical charts into business value.

Can this skill help with data cleaning?

Yes, it includes a Data Preparation Strategy to handle missing values, type conversions, and general data cleaning before any visualization begins.

Data Storytelling Analyst

Name: Data Storytelling Analyst
Author: organvm-iv-taxis

byorganvm-iv-taxis

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データサイエンスとML

Transforms raw datasets into impactful visual narratives using advanced data visualization techniques and narrative design principles.

The Data Storytelling Analyst skill empowers Claude to act as a specialized information designer, bridging the gap between raw data and actionable insights. It moves beyond generic chart generation by identifying patterns and outliers through Exploratory Data Analysis (EDA) and structuring those findings into a logical narrative flow (Context, Conflict, Resolution). By applying core design principles—such as whitespace optimization, accessible color palettes, and the elimination of 'chart junk'—this skill ensures that data visualizations are both aesthetically professional and highly communicative for technical and executive audiences.

主な機能

01Narrative structuring for logical storytelling flow

02Automated Exploratory Data Analysis (EDA) to detect trends and patterns

032 GitHub stars

04Design optimization including accessible color palettes and direct annotations

05Expert visualization using Python (Matplotlib, Seaborn, Plotly) or R (ggplot2)

06Insight generation to interpret complex charts for stakeholders

ユースケース

01Generating executive-ready performance reports from raw business data

02Visualizing complex scientific distributions for research presentations

03Creating clear, annotated data narratives for technical documentation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add organvm-iv-taxis/a-i--skills data-storytelling-analyst

For use in Claude.ai and ChatGPT

Download Skill