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.

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How to Use

1. Open the Unpivot Table Task

• Go to the menu: Tasks > ETL > Unpivot Table

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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).

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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.

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4. Sort Values (Optional)

• Sort values: Choose Ascending or Descending if you want to control the order of unpivoted rows by column category.

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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 or At end of the result.

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6. Save and Run

• Click Save to store the task in your flow.

• Click Run to execute the task in your flow.

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Best Practices

• Use clear numeric fields (e.g., valor, quantidade) as the "Value to pivot" to avoid confusion in the resulting quantity column.

• Ensure your column names are correct — in the screenshot, Novemvro should be corrected to Novembro.

• Always preview the output and validate if your new table preserves the desired relationships.

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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

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Example Output

Given the configuration shown in the screenshot, the output table will include:

Tipo	category	quantity
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 column

• category was generated from the selected month columns

• quantity holds the original values