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Tables And Data Grids

Build tables and data grids in Python with Reflex. Use rx.table for simple semantic tables, rx.data_table for searchable pandas DataFrames, rx.data_editor for spreadsheet-style editing, or the enterprise AG Grid component for advanced features like filtering, pivoting, and cell selection. All in pure Python.

Which table component should I use?

  • rx.table: a composable semantic table. Build headers, rows, and cells yourself for full control over structure and styling. Best for small datasets and custom layouts.
  • rx.data_table: pass a pandas DataFrame or a list of rows and turn on search, sorting, and pagination with search=True, sort=True, and pagination=True. Read-only; best for displaying data from CSV files or database queries.
  • rx.data_editor: a spreadsheet-like grid with cell selection and inline editing. Use it when users edit data directly, as in an admin panel or data entry form.
  • AG Grid (enterprise): advanced filtering, column pivoting, row grouping, master-detail, tree data, and Excel export. See the AG Grid docs to get started.
Data Editor
Data Table
Table