Tables

Documentation Index

Fetch the complete documentation index at: https://docs.databar.ai/llms.txt

Use this file to discover all available pages before exploring further.

Tables are the core data structure in Databar. Each table is a collection of rows and columns where you store, enrich, and transform your data. Tables support large datasets with infinite scroll, cell-level enrichment tracking, and flexible column types.

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Creating tables

You can create a new table in several ways:

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Columns

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Adding and managing columns

• Click the + button at the end of the column header row to add a new column.
• Right-click any column header to rename, delete, or reorder columns.
• Columns created by enrichments are automatically named based on the data field they contain.

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Column types

Databar supports several column types:

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Column grouping

When an enrichment returns multiple fields, those columns are grouped together under a collapsible header. This keeps your table readable even when dozens of data points are attached to each row.

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Rows

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Adding rows

• Single row — click Add row at the bottom of the table.
• Bulk add — paste multiple values or use an importer to add hundreds or thousands of rows at once.
• Programmatic — use the API to insert rows from scripts or automations.

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Editing cells

Click any cell to edit its value directly. For JSON columns, use the expanded editor for easier navigation of nested structures.

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Row detail view

Click the expand icon on any row to open the sidebar detail view. This shows all column values for that row in a vertical layout, making it easier to inspect complex or wide tables.

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Infinite scroll

Tables load rows progressively as you scroll. There is no pagination — just keep scrolling to see more data, even for tables with tens of thousands of rows.

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Cell-level enrichment statuses

Each cell that was populated by an enrichment displays a status indicator showing what happened during processing:

• Success — data was returned and written to the cell.
• No data — the provider was reached but returned no matching result for that input.
• Error — something went wrong (hover over the triangle icon to see details).
• Pending — the enrichment is still running for this row.

This granularity lets you identify exactly which rows need attention without inspecting logs.

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Filtering and sorting

• Sort — click any column header to sort ascending or descending.
• Filter — use the filter bar above the table to show only rows matching specific conditions (e.g., “Status equals Error” or “Email is not empty”).

Filters and sorts can be combined and are applied client-side for instant feedback.

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Data formatting

Databar automatically handles common formatting needs:

• UNIX timestamps are converted to human-readable dates.
• Booleans display as checkmarks or crosses.
• Image URLs render inline previews.
• Long text is truncated in the cell with full content visible in the detail view.

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Working with JSON columns

Many API providers return nested JSON objects. Databar provides a JSON expander that lets you flatten specific fields from a JSON column into their own top-level columns. This makes it easy to extract exactly the data you need without manual parsing.

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Next steps