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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.

For more information on how the platform calculates variance, see VAR 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 > 0) && (testScores < 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

varsampif(col_ref, test_expression) [group:group_col_ref] [limit:limit_count]


ArgumentRequired?Data TypeDescription
col_refYstringReference to the column you wish to evaluate.
test_expressionYstringExpression that is evaluated. Must resolve to true or false

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

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 TypeExample Value
YesString that corresponds to the name of the columnmyValues

test_expression

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

Usage Notes:

Required?Data TypeExample Value
YesString expression that evaluates to true or false(LastName == 'Mouse' && FirstName == 'Mickey')

Examples

Tip: For additional examples, see Common Tasks.

Example - Conditional Calculation Functions

This example shows some of the statistical functions that use the sample method of computation. These include:
  • STDEVSAMP - computes standard deviation using the sample method. See STDEVSAMP Function.
  • VARSAMP - computes variance using the sample method. See VARSAMP Function.
  • STDEVSAMPIF - computes standard deviation based on a condition and using the sample method. See STDEVSAMPIF Function.
  • VARSAMPIF - computes standard deviation based on a condition and using the sample method. See VARSAMPIF Function

Source:

Students took tests on three consecutive Saturdays:


StudentDateScore
Andrew11/9/1981
Bella11/9/1984
Christina11/9/1979
David11/9/1964
Ellen11/9/1961
Fred11/9/1963
Andrew11/16/1973
Bella11/16/1988
Christina11/16/1978
David11/16/1967
Ellen11/16/1987
Fred11/16/1990
Andrew11/23/1976
Bella11/23/1993
Christina11/23/1981
David11/23/1997
Ellen11/23/1997
Fred11/23/1991

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
Parameter: Formula type Single row formula
Parameter: Formula round(stdevsamp(Score), 3)
Parameter: New column name 'stdevSamp'

Transformation Name New formula
Parameter: Formula type Single row formula
Parameter: Formula round(varsamp(Score), 3)
Parameter: New column name 'varSamp'

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

Transformation Name New formula
Parameter: Formula type Single row formula
Parameter: Formula round(stdevsampif(Score, Date != '11\/9\/2019'), 3)
Parameter: New column name 'stdevSampIf'

Transformation Name New formula
Parameter: Formula type Single row formula
Parameter: Formula round(varsampif(Score, Date != '11\/9\/2019'), 3)
Parameter: New column name 'varSampIf'

Results:


StudentDateScorevarSampIfstdevSampIfvarSampstdevSamp
Andrew11/9/198194.5159.722131.67311.475
Bella11/9/198494.5159.722131.67311.475
Christina11/9/197994.5159.722131.67311.475
David11/9/196494.5159.722131.67311.475
Ellen11/9/196194.5159.722131.67311.475
Fred11/9/196394.5159.722131.67311.475
Andrew11/16/197394.5159.722131.67311.475
Bella11/16/198894.5159.722131.67311.475
Christina11/16/197894.5159.722131.67311.475
David11/16/196794.5159.722131.67311.475
Ellen11/16/198794.5159.722131.67311.475
Fred11/16/199094.5159.722131.67311.475
Andrew11/23/197694.5159.722131.67311.475
Bella11/23/199394.5159.722131.67311.475
Christina11/23/198194.5159.722131.67311.475
David11/23/199794.5159.722131.67311.475
Ellen11/23/199794.5159.722131.67311.475
Fred11/23/199194.5159.722131.67311.475

 

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