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knowledge-base/grouping-data-using-radspreadprocessing.md

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## Description
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This article shows how to generate a worksheet with **grouped** data having a **flat** collection of records as an input.
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This article shows how to generate a worksheet with **grouped** data from a **flat** collection of records as an input.
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>caption Flat vs. Grouped Data
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![Flat vs Grouped Data in Excel ><](images/build-grouped-data-in-spreadprocessing.png)
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## Solution
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Note that if you want to perform grouping, this data operation should be performed separately and then populate the Worksheet with the grouped rows.
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Note that the grouping should be performed separately beforehand, and only then can the Worksheet be populated with the grouped data.
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Once you have the grouped data, then, the SpreadProcessing functionality (in a similar way like MS Excel) allows you to assign the outline level to all rows that belong to the same group. To make it clearer, let's have the following example: a flat list of products stored in CSV data for simplicity.
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To group data in a worksheet, follow these steps:
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Once you have the grouped data, the SpreadProcessing functionality (in a similar way to MS Excel) allows you to assign the outline level to all rows that belong to the same group.
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To make it clear and simple, let's take the following example - a flat list of products stored in CSV data:
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### Preparing Grouped Data
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1. Perform grouping on your flat data (e.g. Northwind.Products) before populating the worksheet.
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1. Group your flat data (e.g. Northwind.Products) before populating the worksheet.
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2. Use LINQ or other methods to group rows based on a specific column (e.g. CategoryID).
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Use the following code snippet to group rows in a worksheet:
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// Apply grouping and outlining
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Workbook groupedWorkbook= ApplyGroupingToWorksheet(dataTable, new Workbook());
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Telerik.Windows.Documents.Spreadsheet.FormatProviders.IWorkbookFormatProvider xlsx_formatProvider =
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new Telerik.Windows.Documents.Spreadsheet.FormatProviders.OpenXml.Xlsx.XlsxFormatProvider();
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}
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}
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```
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Modify the example to suit your specific data structure and requirements.
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## See Also

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