Pivot columns

Description

The Pivot Columns activity restructures tabular data by converting unique values in a column into new columns, effectively transposing selected rows into columns. This transformation is useful when converting long-format data into wide-format, making it easier to visualize and analyze grouped or categorized datasets.

It creates a matrix where:

• Each unique value in the Index Column becomes a row
• Each unique value in the Labels Column becomes a new column
• The cell values come from the Values Column

Use this activity to:

• Convert transactional or long-form data into cross-tab reports
• Generate summaries where categories are converted into columns
• Restructure datasets for dashboarding or pivot-based analytics

Use case: A retail company wants to analyze product prices across departments. Using Pivot Columns, they can convert individual product rows into columns under each department, making comparisons easier.

Input

Type	Status	Description
Data	Required	A table with at least three columns: one for row identifiers (index), one for labels (column names), and one for values.

Output

Output Type	Format	Description
Data	Table	Transformed table with rows as index values and columns as labels.

Configuration Fields

Field Name	Description
Index Column	The column whose unique values will be used to create the output rows. A new row is generated for each unique index value.
Labels Column	The column whose unique values will become column headers in the output. Each distinct value in this column becomes a column in the result.
Values Column	The column that provides the values to fill in the pivoted table. If multiple entries exist for the same index-label pair, the last one is used.

If multiple rows have the same combination of index and label, only the last one is retained in the output.

Sample Input

id	category	product	price	in_stock
1	Electronics	Laptop	500	true
2	Electronics	Camera	350	false
3	Electronics	Tablet	250	true
4	Furniture	Sofa	600	true
5	Furniture	Bed	450	true
6	Furniture	Table	150	false

In this example, we want to create one row per category, one column per product, and fill the table with price values.

Sample Configuration

Field	Value
Index Column	category
Labels Column	product
Values Column	price

Sample Output

category	Laptop	Camera	Tablet	Sofa	Bed	Table
Electronics	500	350	250
Furniture				600	450	150