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ANY Function

Extracts a non-null and non-missing value from a specified column. If all values are missing or null, the function returns a null value.

This function is intended to be used as part an aggregation to return any single value. When run at scale, there is some randomness to the value that is returned from the aggregated groupings, although randomness in not guaranteed.

In a flat aggregation, in which no aggregate function is applied, it selects the first value that it can retrieve from a column, which is the first value. This function has limited value outside of an aggregation. See Pivot Transform.

Input column might be of Integer, Decimal, String, Object, or Array type.

Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.

Basic Usage

any(myRating)

Output: Returns a single value from the myRating column.

Syntax and Arguments

any(function_col_ref) [group:group_col_ref] [limit:limit_count]

Argument

Required?

Data Type

Description

function_col_ref

Y

string

Name of column to which to apply the function

For more information on syntax standards, see Language Documentation Syntax Notes.

For more information on the group and limit parameters, see Pivot Transform.

function_col_ref

Name of the column from which to extract a value based on the grouping.

  • Literal values are not supported as inputs.

  • Multiple columns and wildcards are not supported.

Usage Notes:

Required?

Data Type

Example Value

Yes

String (column reference)

myValues

Examples

Tip

For additional examples, see Common Tasks.

Example - Aggregating on one customer per month

You want to do some sampling of customer orders on a monthly basis. For your sample, you want to select the sum of orders for one customer each month.

Source:

Here are the orders for 1Q 2015:

OrderId

Date

CustId

Qty

1001

1/8/15

C0001

12

1002

2/12/15

C0002

65

1003

1/16/15

C0004

23

1004

1/31/15

C0002

92

1005

2/2/15

C0005

56

1006

3/2/15

C0006

83

1007

3/16/15

C0005

62

1008

2/21/15

C0002

43

1009

3/28/15

C0001

86

Transformation:

To aggregate this date by month, you must extract the month value from the Date column:

Transformation Name

New formula

Parameter: Formula type

Single row formula

Parameter: Formula

dateformat(Date, 'MMM')

Parameter: New column name

'month_Date'

You should now have a new column with three-letter month abbreviations. You can use the following aggregation to gather the sum of one customer's orders for each month:

Transformation Name

Pivot columns

Parameter: Row labels

month_Date

Parameter: Values

any(CustId),sum(Qty)

Parameter: Max columns to create

1

Results:

month_Date

any_CustId

sum_Qty

Jan

C0001

127

Feb

C0002

164

Mar

C0006

211