Var / List Layer

Calculate the variance of numeric lists. Similar to numpy.var() or R's var(). Returns the sample (n-1) or population (n) variance. Supports lists of different lengths.

Mathematical definition: For a list of values $x_{1}, x_{2}, ..., x_{n}$ with mean $μ = \frac{1}{n} \sum_{i = 1}^{n} x_{i}$ :

Population variance (ddof=0): $σ^{2} = \frac{1}{n} i = 1 \sum n (x_{i} - μ)^{2}$

Sample variance (ddof=1): $s^{2} = \frac{1}{n - 1} i = 1 \sum n (x_{i} - μ)^{2}$

Example transformation:

lists	variance (ddof=1)
[1, 2, 3, 4]	1.667
[10, 10, 10]	0.0
[1, null, 3, null]	2.0
[2, 4, 6, 8, 10]	10.0
[5]	null
[]	null

Common applications:

Analyzing price volatility in financial data
Measuring process stability in manufacturing
Evaluating measurement precision in lab data
Assessing performance consistency in systems
Computing risk metrics in portfolio analysis
Analyzing spread in experimental results

Note: Only works with numeric lists. Lists with fewer than 2 elements return null. Null values are ignored in calculation. The choice between population (ddof=0) and sample (ddof=1) depends on whether the data represents an entire population or a sample.

Table

Select

column

The variable-length numeric list column to analyze. Examples:

Price series: [10.5, 11.2, 10.8, 11.5]
Performance metrics: [85, 92, 88, 90]
Sensor readings: [1.1, 1.2, 1.15]
Response times: [0.1, 0.15, 0.12] Lists can have different lengths. Only numeric types supported.

Ddof

Delta Degrees of Freedom (DDOF) affecting variance calculation:

1 (default): Sample variance ( $s^{2} = \frac{\sum ( x _{i} - μ ) ^{2}}{n - 1}$ )
0: Population variance ( $σ^{2} = \frac{\sum ( x _{i} - μ ) ^{2}}{n}$ ) Use 1 for sample analysis (more common), 0 when data represents entire population.

AsColumn

name

Name for the new column. If not provided, the system generates a unique name. If AsColumn matches an existing column, the existing column is replaced. The name should follow valid column naming conventions.