Data Table Editor

Data Table Editor

Advanced spreadsheet-like table editor. Sort, filter, search data. Basic formulas support. Import/export CSV, JSON. Free online data grid editor

A spreadsheet in your browser tab for ad-hoc data work — sort, filter, search, basic formulas, import/export CSV/JSON — without launching Excel or Google Sheets. The interesting features for developers are: paste TSV from a database client and instantly query it; export to multiple formats (CSV, JSON, SQL INSERT statements, Markdown table); and do all of it without uploading data to a cloud service. For confidential data exports, this avoids the Google Sheets / Excel Online trap.

What you can do with it

  • Paste from spreadsheet — TSV (tab-separated) from any spreadsheet imports cleanly. Paste from CSV file works similarly.
  • Sort by any column — single-column or multi-column (Shift-click for secondary sort).
  • Filter — by column condition (greater than, equals, contains, regex match) or by free-text search across all columns.
  • Edit cells — inline editing. Adding rows, deleting rows, adding columns.
  • Basic formulas — sum, average, min, max, count over selected cells or a column. Not full Excel formulas (no VLOOKUP across sheets, no INDIRECT).
  • Format — number, date, currency, percentage formats per column.
  • Export — CSV, TSV, JSON, SQL INSERT, Markdown table, HTML table.
  • Aggregations — pivot-like grouping for sum/count/avg by column value.

Working example: cleaning a CSV export

Input

A 5000-row CSV export from your CRM with inconsistent emails

Output

Workflow:
  1. Paste CSV → table renders.
  2. Filter "email" column where email is empty → 142 rows.
  3. Sort by signup date → see if recent signups have empty emails (data-entry bug).
  4. Delete those rows OR export them separately for re-collection.
  5. Apply lowercase formula to email column → standardize.
  6. Trim whitespace from name fields.
  7. Deduplicate by email column.
  8. Export cleaned data as CSV → re-import to CRM.

Time: 5-10 minutes vs ~30 in Excel with manual filtering / formulas.

For ad-hoc data cleanup, a lightweight table editor is faster than Excel because no startup time, no save-as dialogs, no "do you want to enable macros" prompts. For sustained data analysis, switch to pandas / SQL.

When NOT to use a table editor

  • Multi-million-row datasets — browser table editors handle ~100k-1M rows comfortably. Beyond that, use a database (SQL playground in this app, or DuckDB, or a real database).
  • Complex analytics requiring joins across multiple tables — use SQL.
  • Time-series analysis with rolling windows, lag, lead — pandas or a dedicated time-series tool.
  • Stats beyond basic aggregation — variance, regression, correlation — statistics calculator or scipy/R.
  • Permanent dashboards — use a BI tool (Metabase, Looker, Tableau).

When to reach for this tool

  • You have a CSV / TSV export and need to scan / filter / clean it quickly.
  • You are preparing data for a SQL INSERT or JSON file format and want to assemble it row-by-row.
  • You are reviewing a database query result (paste TSV from your DB client) and want to sort and filter.
  • You are creating a markdown table for documentation and want to enter data visually then export.

What this tool will not do

  • It will not replace Excel for complex spreadsheet work. Pivot tables (full feature), pivot charts, conditional formatting, named ranges, cross-sheet formulas — Excel territory.
  • It will not connect to data sources. No live database connections; data comes in via paste, drag-and-drop, or file import.
  • It will not collaborate in real-time. For multi-user editing, use Google Sheets, Excel Online, or Airtable.
  • It will not enforce schemas. Each cell can hold anything; for type-strict data work, define a schema in your downstream tool.

All data stays in your browser tab. Useful for sensitive exports (customer data, internal financials, employee records) where uploading to Google Sheets is a compliance issue.

Frequently asked questions

Can I paste from Excel?

Yes — Excel copies as TSV (tab-separated) by default. Most browser table editors detect tabs and parse into columns. For Excel formulas, only the displayed values copy, not the formulas themselves.

How big a dataset can I edit?

Up to ~100k-500k rows performs well in browser editors. Beyond that, scrolling and filtering slow down. For multi-million-row datasets, use SQL or pandas.

Does it auto-save?

Most browser editors save to localStorage or session storage. Refresh-safe for short sessions; not safe across days. For longer work, export to file periodically.

Can I import from JSON?

Yes — flat JSON arrays of objects parse cleanly. Nested JSON requires unnesting choices (flatten paths to dot-notation columns, or pick one nested array to import).

How do I do a SQL-like join?

Browser table editors typically don't — they're single-table. For joins, use SQL playground (load both tables, JOIN them). Pandas, jq, or any real query tool also works.

Why does my date column show as numbers?

Spreadsheet date encoding. Excel stores dates as serial numbers (days since 1900-01-01); pasting from Excel sometimes carries the serial numbers, not the formatted dates. Apply "date" format to the column to re-interpret.

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Last updated · E-Utils editorial team