data-analysis

You can run SQL queries on Excel and CSV files by loading them into an in-process SQL engine. This allows you to inspect schemas, filter data, and perform cross-file joins directly on uploaded spreadsheets without writing code.

Yes, you can use SQL to join data across multiple sheets in an Excel workbook. The analysis engine handles multi-sheet workbooks efficiently, allowing you to perform cross-file joins and inspect schemas across the entire uploaded dataset.

You can export SQL query results to JSON or Markdown from a CSV file by running your analysis and selecting an output format. The system supports exporting statistical summaries and query results to CSV, JSON, or Markdown formats for reporting.

The best way to generate statistical summaries for spreadsheet columns is by loading the file into an in-process SQL engine. This approach quickly calculates key statistics for both numeric and string columns, making data exploration accessible.

Yes, DuckDB supports inspecting the schema and data types of uploaded CSV files. When you load your data into the in-process SQL engine, you can immediately query the structure, columns, and data types before running complex analysis.

An in-process SQL engine simplifies data analysis because it runs directly in your environment without requiring a separate database server. This makes analyzing Excel and CSV files more accessible and efficient for quick, ad-hoc reporting.