Unpivot Table

The Unpivot Table task in Gaio DataOS allows you to transform a wide-format table (with multiple columns representing categories or dates) into a long-format table (where values are stacked into rows). This is especially useful for time series, monthly reports, and dashboards requiring dynamic filtering.
Important: This task can only be used when a table is selected in the flow.
How to Use
1. Open the Unpivot Table Task
Go to the menu: Tasks > ETL > Unpivot Table
2. Set Task Information
Task label: (optional) Name for identifying this step in your flow.
Result table: Enter the name of the new table that will contain the unpivoted data (e.g.,
unpivot_table
).
3. Select Unpivot Columns
Unpivot columns: Select the columns whose values will be transformed into rows (e.g.,
January
,February
).These columns will become the values in a new "category" field, and their corresponding values will move into a single “quantity” column.
4. Sort Values (Optional)
Sort values: Choose
Ascending
orDescending
if you want to control the order of unpivoted rows by column category.
5. Add Extra Columns (Optional)
Extra columns: Select columns that should remain unchanged and be repeated in the resulting unpivoted table (e.g.,
Region
,Product
).Position of extra columns: Choose whether they appear
At start
orAt end
of the result.
6. Save and Run
Click Save to store the task in your flow.
Click Run to execute the task in your flow.
Best Practices
Use clear numeric fields (e.g.,
valor
,quantidade
) as the "Value to pivot" to avoid confusion in the resultingquantity
column.Ensure your column names are correct — in the screenshot,
Novemvro
should be corrected toNovembro
.Always preview the output and validate if your new table preserves the desired relationships.
Use Cases
Convert monthly sales columns into a time series
Normalize survey responses or data from spreadsheets
Simplify data structure for dashboards and filtering
Prepare wide-format datasets for analytical models
Example Output

Given the configuration shown in the screenshot, the output table will include:
Pay
December
313088.1023
Pay
January
0
Pay
February
0
...
...
...
to receive
October
268242.7913
to receive
November
293688.738
Where:
Tipo
is preserved as an extra columncategory
was generated from the selected month columnsquantity
holds the original values
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