# VARSAMPIF Function

Generates the variance of values by group in a column that meet a specific condition using the sample statistical method.

Note

When added to a transform, this function is applied to the current sample. If you change your sample or run the job, the computed values for this function are updated. Transforms that change the number of rows in subsequent recipe steps do not affect the values computed for this step.

Note

This function applies to a sample of the entire population. More information is below.

Terms...

Relevant terms:

Term

Description

Population

Population statistical functions are computed from all possible values. See https://en.wikipedia.org/wiki/Statistical_population.

Sample

Sample-based statistical functions are computed from a subset or sample of all values. See https://en.wikipedia.org/wiki/Sampling_(statistics).

These function names include SAMP in their name.

Note

Statistical sampling has no relationship to the samples taken within the product. When statistical functions are computed during job execution, they are applied across the entire dataset. Sample method calculations are computed at that time.

• This function is calculated across a sample of all values.

• For more information on a population version of this function, see VARIF 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

varsampif(testScores, ((testScores &gt; 0) &amp;&amp; (testScores &lt; 90)))

Output: Returns the variance of the testScores column when the testScores value is between 0 and 90 using the sample method of calculation.

## Syntax and Arguments

<span>varsampif</span>(col_ref, test_expression) [group:group_col_ref] [limit:limit_count]

Argument

Required?

Data Type

Description

col_ref

Y

string

Reference to the column you wish to evaluate.

test_expression

Y

string

Expression that is evaluated. Must resolve to true or false

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

### col_ref

Name of the column whose values you wish to use in the calculation. Column must be a numeric (Integer or Decimal) type.

Usage Notes:

Required?

Data Type

Example Value

Yes

String that corresponds to the name of the column

myValues

### test_expression

This parameter contains the expression to evaluate. This expression must resolve to a Boolean (true or false) value.

Usage Notes:

Required?

Data Type

Example Value

Yes

String expression that evaluates to true or false

(LastName == 'Mouse' && FirstName == 'Mickey')

## Examples

Astuce

### Example - Conditional Calculation Functions

This example shows some of the statistical functions that use the sample method of computation.

Functions:

Item

Description

STDEVSAMP Function

Computes the standard deviation across column values of Integer or Decimal type using the sample statistical method.

VARSAMP Function

Computes the variance among all values in a column using the sample statistical method. Input column can be of Integer or Decimal. If no numeric values are detected in the input column, the function returns 0.

STDEVSAMPIF Function

Generates the standard deviation of values by group in a column that meet a specific condition using the sample statistical method.

VARSAMPIF Function

Generates the variance of values by group in a column that meet a specific condition using the sample statistical method.

ROUND Function

Rounds input value to the nearest integer. Input can be an Integer, a Decimal, a column reference, or an expression. Optional second argument can be used to specify the number of digits to which to round.

Source:

Students took tests on three consecutive Saturdays:

Student

Date

Score

Andrew

11/9/19

81

Bella

11/9/19

84

Christina

11/9/19

79

David

11/9/19

64

Ellen

11/9/19

61

Fred

11/9/19

63

Andrew

11/16/19

73

Bella

11/16/19

88

Christina

11/16/19

78

David

11/16/19

67

Ellen

11/16/19

87

Fred

11/16/19

90

Andrew

11/23/19

76

Bella

11/23/19

93

Christina

11/23/19

81

David

11/23/19

97

Ellen

11/23/19

97

Fred

11/23/19

91

Transformation:

You can use the following transformations to calculate standard deviation and variance across all dates using the sample method. Each computation has been rounded to three digits.

 Transformation Name New formula Single row formula round(stdevsamp(Score), 3) 'stdevSamp'
 Transformation Name New formula Single row formula round(varsamp(Score), 3) 'varSamp'

You can use the following to limit the previous statistical computations to the last two Saturdays of testing:

 Transformation Name New formula Single row formula round(stdevsampif(Score, Date != '11\/9\/2019'), 3) 'stdevSampIf'
 Transformation Name New formula Single row formula round(varsampif(Score, Date != '11\/9\/2019'), 3) 'varSampIf'

Results:

Student

Date

Score

varSampIf

stdevSampIf

varSamp

stdevSamp

Andrew

11/9/19

81

94.515

9.722

131.673

11.475

Bella

11/9/19

84

94.515

9.722

131.673

11.475

Christina

11/9/19

79

94.515

9.722

131.673

11.475

David

11/9/19

64

94.515

9.722

131.673

11.475

Ellen

11/9/19

61

94.515

9.722

131.673

11.475

Fred

11/9/19

63

94.515

9.722

131.673

11.475

Andrew

11/16/19

73

94.515

9.722

131.673

11.475

Bella

11/16/19

88

94.515

9.722

131.673

11.475

Christina

11/16/19

78

94.515

9.722

131.673

11.475

David

11/16/19

67

94.515

9.722

131.673

11.475

Ellen

11/16/19

87

94.515

9.722

131.673

11.475

Fred

11/16/19

90

94.515

9.722

131.673

11.475

Andrew

11/23/19

76

94.515

9.722

131.673

11.475

Bella

11/23/19

93

94.515

9.722

131.673

11.475

Christina

11/23/19

81

94.515

9.722

131.673

11.475

David

11/23/19

97

94.515

9.722

131.673

11.475

Ellen

11/23/19

97

94.515

9.722

131.673

11.475

Fred

11/23/19

91

94.515

9.722

131.673

11.475