Analyze Excel and CSV files with SQL queries and export results.
npx skills add https://github.com/MagicCube/agentara --skill data-analysis-magiccube
Please help me install this Agent Skill. Skill: data-analysis Source: https://github.com/MagicCube/agentara/tree/main/user-home/.claude/skills/data-analysis Command: npx skills add https://github.com/MagicCube/agentara --skill data-analysis-magiccube
This Skill automates the process of analyzing data from Excel (.xlsx/.xls) and CSV files, allowing users to gain insights without manual data manipulation or complex software.
Use the data-analysis skill to inspect the structure of the uploaded file 'sales_data.xlsx'.
High-intent search queries and answers about installing and using this skill.
You can analyze Excel and CSV data using SQL by leveraging an in-process SQL engine like DuckDB. This allows you to execute arbitrary SQL queries directly against your files for complex analysis, filtering, and aggregation without manual database setup.
Yes, you can perform cross-file joins and analyze multi-sheet Excel workbooks. The SQL engine handles the underlying integration, allowing you to query across multiple files and worksheets seamlessly to combine datasets for analysis.
You can generate statistical summaries for spreadsheet columns by running automated analysis functions. This provides key statistics including mean, median, minimum, maximum, and null counts to help you understand data distribution and quality quickly.
The best way to export SQL query results from CSV analysis is to use built-in export functions. You can save your processed query results directly to CSV, JSON, or Markdown formats for reporting and downstream data consumption.
Yes, analyzing large Excel files with an in-process SQL engine includes automatic caching for performance. This optimizes repeated queries against the same dataset, reducing load times and accelerating complex analytical workflows.
You can inspect the schema of an uploaded Excel file by using dedicated data inspection commands. This reveals the underlying structure, column names, and data types, enabling you to construct accurate SQL queries for your analysis.
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