Date: Sun, 23 Jan 2022 22:46:42 +0000 (GMT) Message-ID: <1594088006.107108.1642978002731@9c5033e110b2> Subject: Exported From Confluence MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_Part_107107_1930267550.1642978002731" ------=_Part_107107_1930267550.1642978002731 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Content-Location: file:///C:/exported.html Aggregate Functions

Aggregate Functions

Aggregate functions perform a computation against a set of = values to generate a single result. For example, you could use an aggregate= function to compute the average (mean) order over a period of time. Aggreg= ations can be applied as standard functions or used as part of a transform = step to reshape the data.

Aggregate across an entire column:

derive type:single value:AVERAGE(Sco= res)

Output: Generates a new column containing the average= of all values in the  Scores column.

=20

pivot value: AVERAGE(Score) limit: 1

Output: Generates a single-column table with a sin= gle value, which contains the average of all values in the Score= s column. The limit defines the maximum number of columns that can b= e generated.

NOTE: When aggregate functions are applied as part of a= pivot transform, they typically involve multiple parameters a= s 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 tr= ansform to change the structure of your data. Example:

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pivot group: StudentId value: AVERAGE(Score) limi= t: 1

In the above instance, the resulting dataset contains two columns:

• studentId - one row for each distinct student ID valu= e
• average_Scores - average score by each student (stud= entId)

NOTE: You cannot use aggregate functions inside of cond= itionals that evaluate to true or false.

A pivot transform can include multiple aggregate functions and group&nbs= p;columns from the pre-aggregate dataset.