If you do not like the results of the split, you can go to the Data pane and edit the calculated fields that are created by the split. In the Data pane, right-click the field you want to split, and then select Transform > Split. Note: You can also use the split option from the Data pane in the worksheet. On the Data Source page, in the grid, click the drop-down arrow next to the field name. For more information, see the Custom split section. Note: In some cases, if the split takes too long to generate new fields or Tableau cannot find a common separator, a custom split dialog box displays. The data type of the new fields generated by the split can vary depending on the pattern combination that Tableau detects in the separator that is used to split the original field. Split fields automaticallyĪ string field can be split automatically based on a common separator that Tableau detects in the field.ĭepending on the connection type, a split can automatically separate a field’s values in up to ten new fields. On the Data pane in the worksheet, check the menu for Transform > Split and Custom Split.īecause different connection types support different functionality in Tableau, you may need to check both places to determine if your data supports the split and custom split options.
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On the Data Source page, check the menu for Split and Custom Split. You can tell if your data supports the SPLIT function by checking the field drop-down menu: For more information, see String Functions.
![email separator comma or semicolon online email separator comma or semicolon online](https://cdn.extendoffice.com/images/stories/doc-outlook/doc-allow-comma-as-address-seperator/doc-allow-comma-as-separator-4.png)
Splits and custom splits are based on the SPLIT string function. The new fields created by the split or custom split are added to the data source as calculated fields. In this example, the common separator is a space character ( ). You can use split or custom split options in Tableau to separate the values based on a separator or a repeated pattern of values present in each row of the field. If you have string fields in your data that contain multiple units of information, for example, the first and last name of a customer, it might be easier to analyze the data if you split the values in that field into separate fields.