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KTHLARGESTDATE Function

Extracts the ranked Datetime value from the values in a column, where k=1 returns the maximum value. The value for k must be between 1 and 1000, inclusive. Inputs must be valid Datetime values.

For purposes of this calculation, two instances of the same value are treated as separate values. So, if your dataset contains three rows with column values 2020-02-15, 2020-02-14, and 2020-02-14, then KTHLARGESTDATE returns 2020-02-14 for k=2 and k=3.

When used in apivottransform, the function is computed for each instance of the value specified in thegroupparameter. See Pivot Transform.

Input column must be Datetime type. Other values column are ignored. If a row contains a missing or null value, it is not factored into the calculation.

For a version of this function that applies to non-Datetime values, see KTHLARGEST Function.

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

kthlargestdate(myDate, 2)

Output: Returns the second highest Datetime value from the myDate column.

Syntax and Arguments

kthlargestdate(function_col_ref, k_integer) [ 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

k_integer

Y

integer (positive)

The ranking of the value to extract from the source column

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

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

function_col_ref

Name of the column the values of which you want to calculate the mean. Inputs must be Datetime values.

  • 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)

transactionDate

k_integer

Integer representing the ranking of the value to extract from the source column.

Note

The value for k must be an integer between 1 and 1,000 inclusive.

  • k=1 represents the maximum value in the column.

  • If k is greater than or equal to the number of values in the column, the minimum value is returned.

  • Missing and null values are not factored into the ranking of k.

Usage Notes:

Required?

Data Type

Example Value

Yes

Integer (positive)

4

Examples

Astuce

For additional examples, see Common Tasks.

Example - KTHLARGESTDATE functions

This example illustrates how you can apply conditionals to calculate minimum, maximum, and most common date values.

Functions:

Item

Description

KTHLARGESTDATE Function

Extracts the ranked Datetime value from the values in a column, where k=1 returns the maximum value. The value for k must be between 1 and 1000, inclusive. Inputs must be valid Datetime values.

KTHLARGESTUNIQUEDATE Function

Extracts the ranked unique Datetime value from the values in a column, where k=1 returns the maximum value. The value for k must be between 1 and 1000, inclusive. Inputs must be Datetime.

KTHLARGESTDATEIF Function

Extracts the ranked Datetime value from the values in a column, where k=1 returns the maximum value, when a specified condition is met. The value for k must be between 1 and 1000, inclusive. Inputs must be Datetime.

KTHLARGESTUNIQUEDATEIF Function

Extracts the ranked unique Datetime value from the values in a column, where k=1 returns the maximum value, when a specified condition is met. The value for k must be between 1 and 1000, inclusive. Inputs must be Datetime.

Source:

Here is some example transaction data:

Date

Product

Units

UnitCost

OrderValue

3/28/2020

ProductA

4

10.00

40.00

3/8/2020

ProductB

4

20.00

80.00

3/12/2020

ProductC

2

30.00

60.00

3/23/2020

ProductA

1

10.00

10.00

3/20/2020

ProductB

2

20.00

40.00

3/12/2020

ProductC

9

30.00

270.00

3/28/2020

ProductA

5

10.00

50.00

3/23/2020

ProductB

8

20.00

160.00

3/16/2020

ProductC

9

30.00

270.00

3/8/2020

ProductA

5

10.00

50.00

3/10/2020

ProductB

3

20.00

60.00

3/13/2020

ProductC

1

30.00

30.00

3/12/2020

ProductA

7

10.00

70.00

3/10/2020

ProductB

7

20.00

140.00

3/24/2020

ProductC

9

30.00

270.00

3/15/2020

ProductA

8

10.00

80.00

3/10/2020

ProductB

5

20.00

100.00

3/10/2020

ProductC

4

30.00

120.00

Transformation:

The following transformation computes the third highest date in the Date column:

Transformation Name

New formula

Parameter: Formula type

Single row formula

Parameter: Formula

kthlargestdate(Date, 3)

Parameter: New column name

'kthlargestdate'

This transformation computes the third highest unique value in the Date column:

Transformation Name

New formula

Parameter: Formula type

Single row formula

Parameter: Formula

kthlargestuniquedate(Date, 3)

Parameter: New column name

'kthlargestuniquedate'

Following transformation calculates the 3rd highest date value when the OrderValue > 200:

Transformation Name

New formula

Parameter: Formula type

Single row formula

Parameter: Formula

kthlargestdateif(Date, 3, OrderValue > 200)

Parameter: New column name

'kthlargestdateif'

Following transformation calculates the 3rd highest unique date value when the OrderValue > 200:

Transformation Name

New formula

Parameter: Formula type

Single row formula

Parameter: Formula

kthlargestuniquedateif(Date, 3, OrderValue > 200)

Parameter: New column name

'kthlargestuniquedateif'

Results:

Date

Product

Units

UnitCost

OrderValue

kthlargestdate

kthlargestuniquedate

kthlargestdateif

kthlargestuniquedateif

3/28/2020

ProductA

4

10.00

40.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/8/2020

ProductB

4

20.00

80.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/12/2020

ProductC

2

30.00

60.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/23/2020

ProductA

1

10.00

10.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/20/2020

ProductB

2

20.00

40.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/12/2020

ProductC

9

30.00

270.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/28/2020

ProductA

5

10.00

50.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/23/2020

ProductB

8

20.00

160.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/16/2020

ProductC

9

30.00

270.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/8/2020

ProductA

5

10.00

50.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/10/2020

ProductB

3

20.00

60.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/13/2020

ProductC

1

30.00

30.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/12/2020

ProductA

7

10.00

70.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/10/2020

ProductB

7

20.00

140.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/24/2020

ProductC

9

30.00

270.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/15/2020

ProductA

8

10.00

80.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/10/2020

ProductB

5

20.00

100.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020

3/10/2020

ProductC

4

30.00

120.00

03-24-2020

03-23-2020

03-23-2020

03-23-2020