To apply cleaning operations to fields, use the toolbar options or click More options on the field profile card, data grid or Results pane to open the menu. If the field is created with fields from both tables, the change is applied after the join. Note: For joins, if the field is a calculated field that was created using a field from one table, the change is applied before the join. The following table shows where the cleaning action is performed in Aggregate, Pivot, Join and Union step types depending on where the field is in the step. The change is performed prior to the join action to give the corrected results. The following example shows a field change from a single table in a Join step. Where the change was made is shown in the Changes pane for the step. Changes made in Aggregate, Pivot, Join and Union step types are performed either before or after those reshaping actions, depending on where the field is when you make the change. The order that you apply your changes matters. If you make changes in the Input step, the annotation shows to the left of the step in the Flow pane and is also shown in the Input profile in the field list. The following table shows which cleaning operations are available in each step type:Īs you make changes to your data, annotations are added to the corresponding step in the Flow pane and an entry is added in the Changes pane to track your actions. For more information about applying cleaning operations in the Input step, see Apply cleaning operations in an input step (Link opens in a new window). You can apply limited cleaning operations in the Input step and can't apply cleaning operations in the output step. You can also perform cleaning operations in the data grid in a cleaning step. You can perform cleaning operations in most step types in your flow. You clean data by applying cleaning operations such as filtering, adding, renaming, splitting, grouping, or removing fields. For more information, see Pivot Your Data (Link opens in a new window) or Use R and Python scripts in your flow (Link opens in a new window). Script steps are not supported in Tableau Online. You can also clean your data using a pivot step or a script step to apply R or Python scripts to your flow. Cleaning up dirty data makes it easier to combine and analyze your data or makes it easier for others to understand your data when sharing your data sets. Tableau Prep provides various cleaning operations that you can use out of the box to clean and shape your data. For more information about authoring flows on the web, see Tableau Prep on the Web in the Tableau Server (Link opens in a new window) and Tableau Online (Link opens in a new window) help. The content in this topic applies to all platforms, unless specifically noted. Note: Starting in version 2020.4.1, you can now create and edit flows in Tableau Server and Tableau Online.
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