In the interactivity features Go-to-URL, Custom events and Custom tooltip, you can include aggregated results from any columns of the dataset(s) used in a widget, even if these columns are not directly used in the widget's slots. The available aggregation types will depend on the column's data type. All filters and grouping on the widget will directly influence the result of the configuration

By using a simple mock dataset (included below), we'll explain the different aggregation types per column, and their expected result. Next to that, we use a custom tooltip configuration in two widgets to show how grouping and filters influence the result of the configuration.

Example dataset

Let's first focus on a very minimalistic example orders dataset, which contains one row per order (i.e. a total of 10 orders have been placed):

Transaction Datetime (UTC)
Total Order Value ($)
Destination Continent
Destination Country
2022-11-29 10:14:23.521
126.75
Europe
Germany
2022-12-11 17:26:44.187
119.12
Asia
Japan
2022-12-16 15:36:45.123
98.99
North America
United States
2022-12-24 06:44:28.843
88.46
Europe
France
2023-01-17 11:51:34.408
76.98
Europe
Germany
2023-01-31 12:42:11.789
50.00
North America
Canada
2023-02-01 09:21:54.246
75.00
Europe
France
2023-02-06 21:14:12.487
16.45
North America
United States
2023-02-15 14:56:37.891
149.99
North America
Canada
2023-02-19 17:13:52.723
187.75
North America
Canada

Visual examples

Each of the examples below contain two widgets: the first column chart does not group on anything, and the second column chart groups on the "destination country" column. When hovering over the different column elements in these widgets, the tooltip will show you examples of what to expect when setting up a specific aggregation type on a specific column type. You can select one or multiple countries by using the second widget's interactivity: this will influence the first widget's tooltip information to showcase how filters directly influence the result.
Together with the raw data above, this should hopefully give a good indication of what to expect when setting this up on your own dataset's columns!

Numeric columns

Numeric columns support the most aggregation types: 'Sum', '(Weighted) Average', 'Median', 'Count Rows', 'Count Distinct', 'Minimum', 'Maximum', 'Standard Deviation', and 'Rate'. Only 'Cumulative sum' is not available in this context.

Date(time) columns

Date(time) columns support 'Count Rows', 'Count Distinct', 'Minimum', and 'Maximum' aggregation types.

Hierarchy columns

Hierarchy columns support 'Count Rows', 'Count Distinct', 'Minimum', and 'Maximum' aggregation types. Note that 'Minimum' and 'Maximum' aggregations will use ascending alphabetical ordering: in case both values "a" and "b" would exist in your data source for the specific query context, 'Minimum' would return "a" while 'Maximum' would return "b". This result can also be seen in the first widget that does not group on anything.

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