Analyze CSV and JSON files to generate statistical summaries and data quality audits.
npx skills add https://github.com/hasna/skills --skill analyze-data
Please help me install this Agent Skill. Skill: Analyze Data Source: https://github.com/hasna/skills/tree/main/skills/skill-analyze-data Command: npx skills add https://github.com/hasna/skills --skill analyze-data
This Skill automates the process of understanding your data, providing immediate statistical summaries, quality checks, and trend detection without requiring manual data science expertise.
Analyze the attached CSV file named 'customer_data.csv' to get a quick health check.
High-intent search queries and answers about installing and using this skill.
To generate a statistical summary from a CSV file, you can use automated data analysis to instantly extract key metrics like mean, median, standard deviation, and custom percentiles for numeric columns without manual data science expertise.
Data quality auditing on JSON files automatically identifies missing values, duplicates, and data type inconsistencies. This process checks your dataset's health to ensure structural integrity before you run deeper statistical profiling or correlation analysis.
Yes, you can detect outliers and correlations in large datasets. The analysis supports large file sampling and generates correlation matrices to discover relationships between variables and spot trends without processing the entire file at once.
Yes, data analysis supports exporting reports to HTML and Markdown. It processes CSV and JSON inputs to generate comprehensive statistical summaries and data quality audits, outputting the final results in multiple formats including Markdown, JSON, and HTML.
The best way to find trends in customer sales data is to run automated trend detection on your CSV file. This identifies correlations between product purchases and highlights statistical anomalies like missing contact information instantly.
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