Aggregate across an entire column:
| Transformation Name | New formula |
|---|---|
| Parameter: Formula type | Single row formula |
| Parameter: Formula | average(Scores) |
Output: Generates a new column containing the average of all values in the Scores column.
| Transformation Name | Pivot columns |
|---|---|
| Parameter: Values | average(Score) |
| Parameter: Max number of columns to create | 1 |
Output: Generates a single-column table with a single value, which contains the average of all values in the Scores column. The limit defines the maximum number of columns that can be generated.
NOTE: When aggregate functions are applied as part of a pivot transformation, they typically involve multiple parameters as part of an operation to reshape the dataset. See below.
Aggregate across groups of values within a column:
Aggregate functions can be used with the pivot transformation to change the structure of your data. Example:
| Transformation Name | Pivot columns |
|---|---|
| Parameter: Row labels | StudentId |
| Parameter: Values | average(Score) |
| Parameter: Max number of columns to create | 1 |
In the above instance, the resulting dataset contains two columns:
studentId- one row for each distinct student ID valueaverage_Scores- average score by each student (studentId)
NOTE: You cannot use aggregate functions inside of conditionals that evaluate to true or false.
A pivot transformation can include multiple aggregate functions and group columns from the pre-aggregate dataset.
For more information on the transformation, see Pivot Data.
NOTE: Null values are ignored as inputs to these functions.
These aggregate functions are available:
This page has no comments.