Unpivot columns

The Unpivot columns step will take every column that you choose and line them up into a single column called ‘Value’. A new column will be made next to it called ‘Type’ that holds the value of the column header that data points used to be in.

Input/output

The input data we’ll use for this step is a table of three columns: “Store Location”, “Profit”, and “Loss”.

Below is a screenshot of our output data after using this Unpivot columns step. It has taken our columns “Profit” and “Loss” and merged them into a single column called “Value”. The “Type” column holds the value of the column header these values came from.

Custom settings

After you connect your data into this step, select the dropdown menu of Unique Identifier Column to choose the column (type of data) you’d like to use as an identifier for this data set. This should be the column you don’t want pivoted, and will be used as a key if the data needs to be pivoted back into shape. This could be a customer ID, store name, store location, customer full name, or more.

Then, select the remaining column headers (data categories) that you’d like to merge the values of those columns into a single column.

Finish by clicking Show Updated Results to save the step’s settings.

Helpful tips

• Optionally, in the Pivot These Columns section, you can choose to select the columns to exclude from the unpivot operation.

Frequently asked questions

What’s the difference between unpivoting and pivoting?

Pivot columns takes values in a column and turns them into headers. Unpivot columns does the reverse — it collapses multiple column headers into a single column of values, producing a longer, narrower table.

Why would I need an identifier column?

The identifier column is the key that links each unpivoted value back to its source row. Without one, you can’t tell which entity each value originally belonged to.

Can I rename the Value and Type columns?

The unpivot output uses “Value” and “Type” by default. To rename them, follow this step with Edit columns and apply your preferred names.

Related steps

• Pivot columns — reshape long data back into a wide format.
• Stack tables — combine multiple sources by stacking rows vertically.
• Sum by group — aggregate numeric values once they’re in long form.
• Filter rows — narrow the unpivoted output to a specific Type.
• Edit columns — rename the default Value and Type columns.