The Blazor Pivot Table is a powerful control used to organize and summarize business data and display the result in a cross-table format. It includes major functionalities such as data binding, drilling up and down, Excel-like filtering and sorting, editing, Excel and PDF exporting, several built-in aggregations, pivot table field list, and calculated fields. A high volume of pivot data can be loaded without any performance degradation using row and column virtualization.
You can bind JSON data to the control to work smoothly in applications. The JSON data can be obtained from a local file, remote file, or web service.
You can also bind CSV data to the control. The CSV data can be obtained from a local file, remote file, or web service.
The Pivot Table can now be connected to OLAP cube and its result can be visualized in both tabular and graphical formats.
Binding the Blazor pivot table with RESTful services allows data from any sources, including Excel and CSV files, SQL databases like Microsoft SQL, MySQL, and PostgreSQL, and collections like IEnumerable, IList, and array lists through services, which are consumed using the data manager explicitly. It supports various data adaptors such as JSON, OData, ODataV4, URL, and Web API for working with particular data services.
Blazor pivot charts can be easily integrated with pivot data rendered independently, including functionality for plotting more than 20 pivot chart types. The end user experience is greatly enhanced by including a set of user interaction features such as zooming, panning, crosshair, trackball, events, selection, and tooltip. Highly interactive field list options are available for generating reports on top of the relational data dynamically.
All features will work on touch devices with ease. Features such as drill up/down, filtering, sorting, and report manipulation can be done on the fly.
Responsive support allows the component layout to view on various devices.
Allows the pivot table field list to view on various devices in a presentable manner.
Provides built-in drill down (expand) and drill up (collapse) capability to visualize data both in a detailed view and abstract view, respectively. By default, the data are displayed in a grouped manner.
Users can create, read, update, and delete operations for raw data at runtime and update their changes to the underlying data source, thereby reflecting the information in all corresponding cells. The component supports various edit modes such as inline, dialog, batch edit, and column edit through an interactive UI.
Built-in normal and Excel-like filters with advanced filtering options to easily filter and view data as required. It is also possible to filter programmatically.
Displays only selective values for a field. This can be achieved either through UI or code-behind.
Excel-like filtering option across column and row headers either based on label text, date, or number.
Sorting supports to order rows and columns based on either labels or values.
Orders the column and row header text either in ascending or descending order.
Users can perform calculations on a group of values using the aggregation option. By default, values are added together. The other aggregation types are: average, minimum, maximum, count, distinct count, product, index, population stdev, sample stdev, population var, sample var, running totals, difference from, % of difference from, and % of grand total.
The calculated field, otherwise known as unbound field generates unique field with our own calculated value by executing a simple user-defined formula.
Subtotals and grand totals are calculated automatically by the pivot engine inside the component and displayed in the pivot table. This helps users make decisions based on the totals. Also, users can show or hide subtotals and grand totals for rows and columns.
Number formatting and date formatting help to transform the appearance of the actual cell value.
The Pivot Table component automatically groups dates and numbers, so the date type can be formatted and displayed based on year, quarter, month, day, and more. The number type can be grouped by range, such as 1-5 or 6-10.
You can freeze row and column headers to scroll and compare cell values with the corresponding row and column headers.
Resizing allows changing column width at runtime by simply dragging the right-most boundary of the column header. The scroll bar will appear when the content width exceeds the component width.
You can reorder the columns either on user interaction or programmatically. Simply dragging and dropping a column header into the desired column position will reorder the columns.
A tooltip provides basic information about a cell while hovering over it with the pointer.
With cell templates, users can add features like images, checkboxes, and text nodes to any cells with ease.
The Toolbar feature provides a built-in interface for pivot tables to select frequently used features interactively for easy access. These features include New Report, Save Report, Save As Report, Rename Report, Delete Report, Report List, Show Grid, Show Chart, Show or Hide Totals, Export Reports, and more.
Exports Blazor pivot table data to Excel, PDF, and CSV formats. You can also customize the exported document by adding the header, footer, and cell properties like type, style, and position programmatically.
Ships with a set of 4 stunning, built-in themes namely material, fabric, bootstrap and high contrast.
You can customize the appearance of the component to any extent programmatically.
Enables users from different locales to use the component by formatting the date, currency, and numbering to suit locale preferences. This uses an internalization (i18n) library for handling value formatting.
Supports right-to-left rendering and allows the text direction and layout of the component to display from right to left.
You can localize all the component strings in the user interface as needed and use the localization (l10n) library to localize UI strings.
For a great developer experience, flexible built-in APIs are available to define and customize the Blazor Pivot Table component. Developers can optimize the data bound to the component and customize the user interface (UI) completely using code with ease.
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