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Computes the standard deviation across all column values of Integer or Decimal type.

The standard deviation of a set of values attempts to measure the spread in values around the mean and is used to measure confidence in statistical results. A standard deviation of zero means that all values are the same, and a small standard deviation means that the values are closely bunched together. A high value for standard deviation indicates that the numbers are spread out widely. Standard deviation is always a positive value.

• If a row contains a missing or null value, it is not factored into the calculation.
• If no numeric values are detected in the input column, the function returns 0.

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 the entire population.

• For more information on a sampled version of this function, see STDEVSAMP Function.

The square of standard deviation is variance. See VAR Function.

For a version of this function computed over a rolling window of rows, see ROLLINGSTDEV 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

stdev(myRating)

Output: Returns the standard deviation of the values from the myRating column.

Syntax and Arguments

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

ArgumentRequired?Data TypeDescription
function_col_refYstringName of column to which to apply the function

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

function_col_ref

Name of the column the values of which you want to calculate the variance. Column must contain Integer or Decimal values.

• Literal values are not supported as inputs.
• Multiple columns and wildcards are not supported.

Usage Notes:

Required?Data TypeExample Value
YesString (column reference)myValues

Examples

This example illustrates how you can apply statistical functions to your dataset. Calculations include average (mean), max, min, standard deviation, and variance.

Functions:

ItemDescription
AVERAGE Function Computes the average (mean) from all row values in a column or group. Input column can be of Integer or Decimal.
MIN Function Computes the minimum value found in all row values in a column. Input column can be of Integer, Decimal or Datetime.
MAX Function Computes the maximum value found in all row values in a column. Inputs can be Integer, Decimal, or Datetime.
VAR Function Computes the variance among all values in a column. Input column can be of Integer or Decimal. If no numeric values are detected in the input column, the function returns 0
STDEV Function Computes the standard deviation across all column values of Integer or Decimal type.
NUMFORMAT Function Formats a numeric set of values according to the specified number formatting. Source values can be a literal numeric value, a function returning a numeric value, or reference to a column containing an Integer or Decimal values.
MODE Function Computes the mode (most frequent value) from all row values in a column, according to their grouping. Input column can be of Integer, Decimal, or Datetime type.

Source:

Students took a test and recorded the following scores. You want to perform some statistical analysis on them:

StudentScore
Anna84
Ben71
Caleb76
Danielle87
Evan85
Faith92
Gabe85
Hannah99
Ian73
Jane68

Transformation:

You can use the following transformations to calculate the average (mean), minimum, and maximum scores:

Transformation Name New formula Single row formula AVERAGE(Score) 'avgScore'

Transformation Name New formula Single row formula MIN(Score) 'minScore'

Transformation Name New formula Single row formula MAX(Score) 'maxScore'

To apply statistical functions to your data, you can use the VAR and STDEV functions, which can be used as the basis for other statistical calculations.

Transformation Name New formula Single row formula VAR(Score) var_Score

Transformation Name New formula Single row formula STDEV(Score) stdev_Score

For each score, you can now calculate the variation of each one from the average, using the following:

Transformation Name New formula Single row formula ((Score - avg_Score) / stdev_Score) 'stDevs'

Now, you want to apply grades based on a formula:

AstDevs > 1
BstDevs > 0.5
C-1 <= stDevs <= 0.5
DstDevs < -1
FstDevs < -2

You can build the following transformation using the IF function to calculate grades.

Transformation Name New formula Single row formula IF((stDevs > 1),'A',IF((stDevs < -2),'F',IF((stDevs < -1),'D',IF((stDevs > 0.5),'B','C'))))

To clean up the content, you might want to apply some formatting to the score columns. The following reformats the stdev_Score and stDevs columns to display two decimal places:

Transformation Name Edit column with formula stdev_Score NUMFORMAT(stdev_Score, '##.00')

Transformation Name Edit column with formula stDevs NUMFORMAT(stDevs, '##.00')

Transformation Name New formula Single row formula MODE(Score) 'modeScore'

Results:

Anna8485826899

87.00000000000001

9.330.21C
Ben718582689987.000000000000019.33-1.18D
Caleb768582689987.000000000000019.33-0.64C
Danielle878582689987.000000000000019.330.54B
Evan858582689987.000000000000019.330.32C
Faith928582689987.000000000000019.331.07A
Gabe858582689987.000000000000019.330.32C
Hannah998582689987.000000000000019.331.82A
Ian738582689987.000000000000019.33-0.96C
Jane688582689987.000000000000019.33-1.50D

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