Dash DataTable
Dash DataTable is an open-source Python library for building interactive data tables. It allows for filtering, sorting, pagination, editing, selecting rows, exporting, and more. Dash DataTable makes it easy to display large, dynamic datasets.
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Dash DataTable: Open-Source Python Library
Build interactive data tables with filtering, sorting, pagination, editing, and more. Easily display large, dynamic datasets.
What is Dash DataTable?
Dash DataTable is an open-source Python library for building interactive data tables and grids. It is part of the Plotly Dash library for building analytical web applications. Dash DataTable allows you to render large, dynamic datasets with full filtering, sorting, pagination, editing, selecting, and exporting capabilities.
Some key features of Dash DataTable include:
- Handling large datasets with lazy loading
- Sorting, filtering, pagination, row selection, and exports like CSV and Excel
- Inline editing and adding rows
- Column-level styling and conditional formatting
- Callback support to update the table on user actions
- Integration with Python data analysis libraries like Pandas and Numpy
Dash DataTable makes it very easy to display tabular data from databases or dataframes as an interactive table. The callbacks and integration with Python allows the table to stay in sync with underlying datasets. Overall, Dash DataTable is a full-featured library for displaying large datasets in analytical web dashboards and applications.
Dash DataTable Features
Features
- Interactive data tables
- Sorting
- Filtering
- Pagination
- Row selection
- Editing cells
- Exporting data
- Custom styling
- Column resizing
- Virtualization for large datasets
Pricing
- Open Source
- Free
Pros
Open source and free
Easy to use with Python/Dash
Highly customizable
Good performance with large datasets
Active development and support
Cons
Steep learning curve
Less features than some commercial options
Need to know Python and Dash
Official Links
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