> ## Documentation Index
> Fetch the complete documentation index at: https://docs.activeviam.com/llms.txt
> Use this file to discover all available pages before exploring further.

# std()

<span id="atoti.agg.std" />

> @overload<br />
> atoti.agg.std(<br />
>     *operand*: LevelOrVariableColumnConvertible,<br />
>     /,<br />
>     \*,<br />
>     *mode*: [Literal](https://docs.python.org/3/library/typing.html#typing.Literal)\['sample', 'population'] = `'sample'`,<br />
> ) → MeasureDefinition

> @overload<br />
> atoti.agg.std(<br />
>     *operand*: VariableMeasureConvertible,<br />
>     /,<br />
>     \*,<br />
>     *mode*: [Literal](https://docs.python.org/3/library/typing.html#typing.Literal)\['sample', 'population'] = `'sample'`,<br />
>     *scope*: [CumulativeScope](./atoti.scope.CumulativeScope#atoti.CumulativeScope) | [SiblingsScope](./atoti.scope.SiblingsScope#atoti.SiblingsScope) | [OriginScope](./atoti.scope.OriginScope#atoti.OriginScope),<br />
> ) → MeasureDefinition

Return a measure equal to the standard deviation of the passed operand across the specified scope.

### Parameters

<h4 id="atoti.agg.std.operand">
  *operand*
</h4>

The operand to get the standard deviation of.

<h4 id="atoti.agg.std.mode">
  *mode*
</h4>

One of the supported modes:

* The `sample` standard deviation, similar to Excel’s `STDEV.S`, is $\sqrt{\frac{\sum_{i=1}^{n} (X_i - m)^{2}}{n - 1}}$ where `m` is the sample mean and `n` the size of the sample.
  Use this mode if the data represents a sample of the population.
* The `population` standard deviation, similar to Excel’s `STDEV.P` is $\sqrt{\frac{\sum_{i=1}^{n}(X_i - m)^{2}}{n}}$ where `m` is the mean of the `Xi` elements and `n` the size of the population.
  Use this mode if the data represents the entire population.

<h4 id="atoti.agg.std.scope">
  *scope*
</h4>

The [`aggregation scope`](./atoti.scope#module-atoti.scope).