Perform time series analysis with group functions to aggregate operations and compare side by side summarized and detailed information.
What are group functions?
Group functions, or g_functions, are a powerful specialized tool used to perform aggregation operations on rows that have the same values in a given set of columns. With group functions, aggregated and detailed information live together in one place so you can compare individual row data with summarized data.
How can I get started with group functions?
See the quick reference, Popular Time Series Functions for a list of group functions and examples of how they’re used. Try these with your own data. Start with summarization functions, then experiment with other types. Remember, you are always working with a copy of your data, so explore.
What operations can be used with group functions?
Use the Expression Editor to enter group functions with Filter and New Column operations.
What do I need to know before using a group function?
Tables of 8 million rows or less do not need to be segmented. Tables with more than 8 million rows must be segmented before you can use group functions. From the View dropdown in the Data Grid, check the metadata. This information lets you know if a table is segmented and which column(s) must be included in the G, or group, parameter.
The table segmentation I have doesn’t provide the group I need. Can I change how a table is segmented?
Yes, you can adjust how a table is segmented. For example, analytics on retail transaction data may need to be grouped by date in some analyses, and location in others. Consider creating copies of the table with different segmentations to support efficient analyses. You can also adjust segmentation when you save a worksheet as a table.
What group functions does DSCVR offer?
DSCVR offers many different group functions including summarization, statistics, time and order, conditional, modeling, matrix, and signal processing. For a list of group functions, see the Function Reference.