> For the complete documentation index, see [llms.txt](https://docs.fabricplan.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.fabricplan.com/planning-sheets/how-tos/infobridge/data-transformations/pivot-columns-unpivot-columns.md).
# Pivot and unpivot columns
Use the **Pivot Column** and **Unpivot Column** transformations in Infobridge to reorganize data into formats that are easier to analyze and report on.
Pivoting converts values from a selected column into multiple columns, while unpivoting converts multiple columns back into rows.
### Pivot column
The **Pivot Column** transformation converts values from a selected dimension into separate columns. This transformation lets you compare measures across categories more effectively.
#### Example: Pivot segment sales data
The following example shows sales data in a tabular format, where each segment appears as a row.
| Country | Segment | Sales |
| ------- | ---------------- | ------- |
| Canada | Channel Partners | 491.16K |
| Canada | Enterprise | 3.97M |
| Canada | Government | 10.74M |
| Canada | Midmarket | 510.21K |
| Canada | Small Business | 9.18M |
| France | Channel Partners | 372.09K |
| France | Enterprise | 3.89M |
| France | Government | 12.13M |
| France | Midmarket | 593.80K |
| France | Small Business | 7.37M |
After you pivot the **Segment** column, each segment value appears as a separate column.
| Country | Enterprise | Government | Midmarket | Small Business | Channel Partners |
| ------------------------ | ---------- | ---------- | --------- | -------------- | ---------------- |
| Canada | 3.97M | 10.74M | 510.21K | 9.18M | 491.16K |
| France | 3.89M | 12.13M | 593.80K | 7.37M | 372.09K |
| Germany | 4.09M | 11.45M | 301.34K | 7.33M | 336.43K |
| Mexico | 3.32M | 9.79M | 511.14K | 7.10M | 234.38K |
| United States of America | 4.35M | 8.39M | 465.39K | 11.46M | 366.53K |
#### Create a pivot column
The following procedure pivots the **Segment** column and aggregates values from the **Sum of Sales** measure.
1. On the **Transform** tab, select **Pivot Column**.
2. In **Category**, select **Segment**.
3. In **Operations**, select the aggregation type.
4. In **Values**, select **Sum of Sales**.
5. Select **Apply**.
After you apply the transformation, each segment value becomes a separate column.
#### Choose an aggregation type
The **Operations** field determines how to aggregate values when multiple records exist for the same combination of dimensions.
Available aggregation options include:
* Sum
* Average
* Minimum
* Maximum
### Unpivot column
The **Unpivot Column** transformation reverses a pivot operation by converting multiple columns into rows.
#### Select columns to unpivot
For example, after pivoting the **Segment** column, each segment exists as an individual column. Unpivoting converts those segment columns back into row values.
1. On the **Transform** tab, select **Unpivot Column**.
2. In **Category**, select the columns to convert into rows.
3. Select **Apply**.
The following example selects all segment columns.
After you apply the transformation, the selected columns become two new columns:
* **Attribute**: Contains the original column names.
* **Value**: Contains the corresponding measure values.
For example, segment names such as Enterprise, Government, and Small Business move into the **Attribute** column, and their corresponding sales values appear in the **Value** column.
### Rename unpivoted columns
After unpivoting, the generated **Attribute** and **Value** column names might not match your business terminology.
Use **Rename Column** to replace the default column names with names that better reflect your business data.
1. On the **Transform** tab, select **Rename Column**.
2. Select the column to rename.
3. Enter a new column name.
4. Select **Apply**.
The following example renames the **Value** column to **Sales**.
After you apply the rename operation, the column displays the updated name.
You can use the renamed column in subsequent transformations, calculations, and reporting scenarios.
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