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JSON Statistics

Summarize JSON size, structure, keys, and value types.

JSON input

Paste strict JSON for live local analysis. Your JSON is never modified.






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What this tool does

Analyze a valid JSON value without changing it. The dashboard counts values, objects, arrays, keys, nesting, strings, numbers, and repeated key names locally.

How metrics work

Every JSON value counts as one node, including the root object or array; object key names are not nodes. The root value has depth 0, and each contained value adds one depth level. Total keys counts every object property, while unique keys counts distinct property names across the document. Array elements are counted in their original order. String length uses Unicode code points, and numeric aggregates use JavaScript number semantics.

Privacy

Your JSON stays in this browser. Nothing is uploaded, logged, or automatically saved, and the analysis never modifies your JSON.

Frequently asked questions

What counts as a JSON node?

Each JSON value counts once; property names do not count as value nodes.

How is maximum depth calculated?

The root is depth 0, and every nested value is one level deeper.

Are array elements counted?

Yes. Every array item is a node and contributes to the total element count.

What are unique keys?

They are distinct object-property names, even when the same name appears in many objects.

Does the tool modify my JSON?

No. It reads a parsed value only and never reorders or rewrites the input.

Can primitive JSON values be analyzed?

Yes. Strings, numbers, booleans, and null are valid root values.

How are number averages calculated?

They use JavaScript floating-point number arithmetic for finite values.

Practical guide

When to use it

Use it to quickly understand the size and shape of unfamiliar JSON before deciding whether to view, transform, or query it.

Three steps

  1. Paste valid JSON into the editor.
  2. Read the counts for objects, arrays, values, keys, and depth.
  3. Use the result to spot unusually deep nesting or unexpectedly large collections.

Example and a common mistake

A response with 1,000 array entries and depth 8 may need a tree view rather than manual scanning.

Statistics describe the data that is present; they do not assess data quality or enforce a schema.

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