Does this skill require me to specify which columns to analyze?

No, the skill is designed to be fully automatic. It scans the entire CSV, identifies relevant data types, and generates comprehensive results without asking for user input.

What types of visualizations does it generate?

It creates context-specific plots such as time-series trends (if dates are present), correlation heatmaps (for numeric data), and distribution charts (for categorical data).

Can I use this for large datasets?

Yes, it leverages the high-performance Python pandas library to handle standard CSV datasets efficiently within the Claude Code environment.

Why does it skip asking me what I want to do with the data?

The core design philosophy of this skill is 'immediate action.' It assumes that if you provide a CSV, you want a full analysis right away, saving you time and reducing unnecessary conversation turns.

CSV Data Summarizer

Name: CSV Data Summarizer
Author: Weiwei-Mao

byWeiwei-Mao

数据科学与机器学习

Analyzes CSV files automatically to generate comprehensive statistical summaries and context-aware visualizations using Python and pandas.

关于

This skill transforms Claude into a proactive data analyst that immediately processes CSV files without requiring manual direction or repetitive back-and-forth prompting. Upon detecting a tabular dataset, it intelligently identifies data types—such as sales, customer, or financial data—and automatically executes relevant statistical analyses, identifies missing values, and generates tailored visualizations like time-series plots and correlation heatmaps. It is specifically designed for users who need instant insights and professional-grade data overviews without having to specify analysis parameters or navigate complex configuration options.

主要功能

Proactive analysis without user intervention or follow-up questions
Automatic data type detection for dates, categories, and numeric values
Comprehensive statistical summaries and missing data reporting
Intelligent industry-specific adaptation for sales, finance, and survey data
0 GitHub stars
Context-aware visualizations including time-series, histograms, and heatmaps

使用场景

Getting an instant high-level overview of newly uploaded sales or transaction datasets
Automating the initial exploratory data analysis (EDA) phase for data science projects
Quickly identifying data quality issues and missing values in large tabular files

关于

主要功能

Proactive analysis without user intervention or follow-up questions
Automatic data type detection for dates, categories, and numeric values
Comprehensive statistical summaries and missing data reporting
Intelligent industry-specific adaptation for sales, finance, and survey data
0 GitHub stars
Context-aware visualizations including time-series, histograms, and heatmaps

使用场景

Getting an instant high-level overview of newly uploaded sales or transaction datasets
Automating the initial exploratory data analysis (EDA) phase for data science projects
Quickly identifying data quality issues and missing values in large tabular files