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data-analysis

MITUpdated on Nov 11, 202685,246GitHub starsIncludes scripts

A skill shipped with ByteDance's DeerFlow agent for analysing uploaded spreadsheets and CSV files. A bundled Python script loads the files into DuckDB, an in-process SQL engine, turning each Excel sheet into a table.

InstallRepository Checked on Nov 12, 2026

What the skill teaches

A skill shipped with ByteDance's DeerFlow agent for analysing uploaded spreadsheets and CSV files. A bundled Python script loads the files into DuckDB, an in-process SQL engine, turning each Excel sheet into a table. The agent first inspects the structure, with sheet and column names, types, row counts and sample rows, then answers questions by writing SQL queries, asks for per-column statistics, and can save query results as CSV, JSON or Markdown. It covers joins across files, aggregation and filtering. The script needs the duckdb and openpyxl Python packages, and the paths in the instructions follow DeerFlow's sandbox layout.

Capabilities

  • Inspect sheets, columns and types of Excel or CSV files
  • Query uploaded data with SQL through DuckDB
  • Produce per-column summary statistics
  • Export query results as CSV, JSON or Markdown

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