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Dataset Sample Bundle Maker

Select representative valid and invalid rows; package schemas and import examples.

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Samples the first matching rows under your explicit type rules. This is not statistically representative sampling and does not remove private information.

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Using Dataset Sample Bundle Maker

Select representative valid and invalid rows; package schemas and import examples.

  1. Use Try example to explore dataset sample bundle maker, or enter your own dataset csv / json.
  2. Set column types as json, rows per valid / invalid group. Read the field notes for supported values.
  3. Choose Create sample bundle and inspect the result, including any review flags or unsupported cases.
  4. Use the relevant download buttons to keep your result. CSV and report JSON preserve the available findings; original files are not changed.

Example

Dataset CSV / JSON: id,email
1,mira@example.com
2,alex@example.com
oops,missing-id
3,
Column types as JSON: {"id":"integer","email":"string"}
Rows per valid / invalid group: 2

Questions & answers

What does Dataset Sample Bundle Maker do?

Select representative valid and invalid rows; package schemas and import examples.

What input does this tool support?

Dataset CSV / JSON. Column types as JSON: Supported types: string, number, integer, boolean. Every listed column is required.. Rows per valid / invalid group

What should I check before using the result?

Samples the first matching rows under your explicit type rules. This is not statistically representative sampling and does not remove private information.

Can I keep or share the result?

Yes. Use the result-specific downloads, CSV where available and report JSON. Downloads can contain your supplied information, so review the content before sharing. Processing runs in this browser; public pages also include the site’s approved advertising and optional analytics.

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