By Team Hypomnema · Data
Reshape long records into wide data, or turn wide columns into rows.
Use the guide alongside the working tool.
Open Pivot & Unpivot Data →Explicit working sample
region,product,amount
North,Notebook,24.5
North,Pen,15
South,Notebook,49
South,Pen,9Reshape long records into wide data, or turn wide columns into rows. Pivot requires unique index + category combinations; aggregate duplicates first with Group & Aggregate. Unpivot preserves chosen identifier columns and emits a variable/value pair. Empty values can be retained or skipped. Output stays within the published cell and column limits.
Prepare the input
Reshape long records into wide data, or turn wide columns into rows.
CSV, TSV and arrays of scalar JSON objects are supported. Identifiers stay text. Empty cells are missing by default; add special missing tokens only if their meaning is certain. Use the sample to inspect the exact workflow.
Review the method
Pivot requires unique index + category combinations; aggregate duplicates first with Group & Aggregate. Unpivot preserves chosen identifier columns and emits a variable/value pair. Empty values can be retained or skipped. Output stays within the published cell and column limits.
Keep the useful output
Review the summary and result records. Transformation tools retain separate change, rejected-record or diagnostics datasets where relevant. Choose the dataset before exporting; a report and a cleaned dataset serve different purposes.
CSV exports protect formula-like text. JSON keeps data portable without making an Excel workbook. Reports and editable backups may contain private source values; download only what you intend to share. No automatic account storage or server processing is used.
Ready to apply this workflow?
Try Pivot & Unpivot Data →Explore a related workflow
- Group & Aggregate Data: methods and data limits
Summarize records by multiple keys with explicit aggregate measures.
- Data Filter Builder: methods and data limits
Keep or exclude records using typed, exportable filter conditions.
- Column Split & Extract: methods and data limits
Extract structured pieces from a column while keeping the original values.
- Data Value Mapper: methods and data limits
Replace codes and labels using a checked reference dictionary.
Keep your original files and review the result. Found unclear instructions? Contact Team Hypomnema.