Filter Data Tables Window
Filters a list of data tables.
The Filter data tables editor windows allow the user to filter the user-specified data tables based on given filter criteria.
The filter input section is divided into six columns, each serving a specific purpose in specifying the filtration criteria for the data tables.
DataTable Operation: The first column contains a dropdown list with three operations: ColumnCount, RowCount, and ColumnName. Here, you can select the desired operation that will determine how the data tables are filtered.
Relational Operator: The second column provides a dropdown list of relational operators. These operators establish the relationship between the selected DataTable operation and the filter value.
Filter Value: In the third column, you can specify the value that will be used with the relational operator for filtration. This value helps define the condition for filtering the data table.
Keep/Remove: The fourth column features a dropdown with options to either keep or remove the filtered data table from the list of data tables. You can choose the option that best suits your filtering requirements.
Add Button (+): The fifth column includes a "+" button, which allows you to create a new filter condition in the editor window. You can add multiple filter conditions to fine-tune the filtration of your data table list.
Remove Button (x): The sixth column contains an "x" button, which enables you to remove a specific filter condition from the editor window. Use this button to eliminate any unnecessary or unwanted filter conditions.
If you wish to start fresh and remove all filter conditions, you can use the "Clear" button located next to the Preview button. This button clears or removes all filter conditions, except for the default condition.
To save your changes and the filter conditions you have created using the window, click the Ok button. Alternatively, if you want to discard your changes and close the window, click the Cancel button.
By utilizing the Filter Data Tables feature, you can easily apply custom filters to your data tables, allowing you to extract the specific information you need for your RPA automation tasks.
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