Load Excel and CSV files into DuckDB for SQL queries and statistics.
npx skills add https://github.com/easyspace-ai/minote --skill data-analysis-easyspace-ai
Please help me install this Agent Skill. Skill: data-analysis Source: https://github.com/easyspace-ai/minote/tree/main/skills/public/data-analysis Command: npx skills add https://github.com/easyspace-ai/minote --skill data-analysis-easyspace-ai
Data scientists and teams waste time analyzing scattered Excel/CSV files; this Skill provides a DuckDB-based workflow to inspect schemas, run SQL queries, compute statistics, and export results in multiple formats.
Upload your Excel or CSV data to /mnt/user-data/uploads and start by inspecting the schema, then run queries to summarize and export results.
High-intent search queries and answers about installing and using this skill.
To query Excel and CSV files with SQL, load your uploaded data into DuckDB for in-process analytics, inspect the schema, and execute arbitrary SQL statements across multiple files.
Yes, you can analyze multi-sheet Excel workbooks by loading them into DuckDB, where each sheet automatically becomes a separate table available for cross-sheet SQL querying and statistical summaries.
Get statistical summaries from CSV data by loading the file into DuckDB to compute means, percentiles, null counts, and top values, then export the analysis results to CSV, JSON, or Markdown formats.
Yes, this approach handles large Excel and CSV files efficiently by parsing binary Excel streams with OpenPyXL and caching loaded data in DuckDB for fast subsequent repeat analyses.
The best way to inspect the schema of uploaded CSV and Excel files is loading them into DuckDB to automatically reveal columns, data types, sheet names, and row counts before running queries.
Yes, you need DuckDB and OpenPyxl installed, as OpenPyxl parses binary Excel streams and DuckDB executes the in-process SQL queries required for cross-file data exploration and export.
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