DataframeVar / Aggregation Layer

Calculate variance across specified columns, similar to numpy var() or pandas var(). Measures the average squared deviation from the mean.

Mathematical form: $σ^{2} = \frac{\sum _{i = 1}^{N} ( x _{i} - x ˉ ) ^{2}}{N - ddof}$ Where:

$σ^{2}$ is the variance
$\overset{x}{ˉ}$ is the mean
$N$ is the number of observations
ddof adjusts degrees of freedom

Common applications:

Investment risk analysis
Process control in manufacturing
Experimental error estimation
Quality assurance
Sensor calibration
Population studies

Provides multiple ddof configurations for detailed statistical analysis.

Table

Select

[column, ...]

Numeric columns to compute variance for. If empty, processes all numeric columns. Non-numeric columns are ignored. Selected columns should contain sufficient non-null values for meaningful variance calculation.

DdofValues

[, ...]

Configuration for variance calculation with specific degrees of freedom adjustment. Different ddof values suit different statistical scenarios.

Ddof

Delta Degrees of Freedom (ddof) for variance calculation:

1 (default): Sample variance (unbiased estimator)
0: Population variance (maximum likelihood estimator) Higher values increase the estimated variance.