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.

Standard deviation comes in two flavors:

• Population standard deviation computes the variance from all possible values.
• Sample standard deviation computes from a subset or sample of all values.
• Since has access to all available values, the computation for population standard deviation is used across the entire dataset.

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 .

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.

Output: Generates a two-column table containing the unique values from the postal_code column and the standard deviation of the group of values from the myRating column for the postal_code value. The limit parameter defines the maximum number of output columns.

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.