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Text to Table Input Types

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Use this page to understand what Text to Table can convert and how to prepare common input formats.

Text with clear separators such as commas, tabs, semicolons, or pipes works well with local parsing.

First Name,Last Name,Department,E-Mail
Alice,Johnson,HR,[email protected]
Bob,Smith,IT,[email protected]
Clara,Lee,FIN,[email protected]
David,Kim,MKT,[email protected]

If one value contains commas, wrap that value in double quotes so it stays in one cell.

First Name,Last Name,Department,E-Mail

Text copied from emails, notes, or AI output can still be converted even when it does not have clear separators.

Alice Johnson (HR) [email protected] Bob Smith (IT), [email protected], Clara Lee (FIN), [email protected], David Kim (MKT), [email protected]

Markdown table syntax is supported.

| Customer | Order | Milk |
|-------------|------------|--------|
| Alice | Latte | Oat |
| Bob | Americano | None |
| Charlie | Cappuccino | Almond |

Markdown tables are a good fit when your source already has clear row and column structure but is still stored as text.

Text to Table can also handle Markdown content that mixes tables with headings, lists, or paragraphs.

Examples:

  • documentation snippets with a heading followed by a table
  • notes copied from an AI tool
  • project updates written in Markdown

If your selection mixes several Markdown blocks and you want more control over the result, use Open in Table Editor.

Text to Table uses the first parsed row as headers. It does not infer headers automatically.

If you want specific column names, include them in the first row of the text you convert.

If you start Text to Table with no selected text, you can also import:

  • .csv
  • .tsv
  • .txt
  • .xlsx

Those files open through Table Editor first so you can review the result before you click Apply.