JSON to Excel - Online Tool

The tool scans field names across all objects, uses their union as the header, and leaves blank cells for missing fields. A single object is treated as one row; strip the ad-hoc debug fields before generating for a cleaner header.

One level of nesting usually becomes columns directly; deeper structures tend to turn into cell text, so flatten or project them first when needed. Arrays are best split into rows or sub-tables. Agree as a team on what false, null, and empty string each stand for to avoid ambiguity.

It can. Excel treats long numbers as Number, dropping leading zeros or switching to scientific notation, and Unix timestamps may be read as date serials. Write identifiers as strings in the source JSON, format them as text after opening, and spot-check the extremes. Before sharing, verify three things: the row count, a few long IDs, and a filter on blanks to make sure no column was swallowed by type coercion.

It fits sample reconciliation and one-off analysis, not production sync pipelines; tens of thousands of rows may be fine, but anything larger should go through CSV or a backend export — a lagging tab does not mean the conversion failed. Choose xlsx for desktop filtering and simple formulas; choose CSV for scripts, diff, and Git. Both run locally.