DataframeSkew / Aggregation Layer

Calculate skewness across specified columns, similar to scipy.stats.skew or pandas skew(). Measures the asymmetry of data distribution around its mean.

Mathematical form: $Skewness = \frac{\sum _{i = 1}^{n} ( x _{i} - x ˉ ) ^{3} / n}{s ^{3}}$ Where:

$\overset{x}{ˉ}$ is the mean
$s$ is the standard deviation
$n$ is the number of observations

Interpretation:

Positive skew: Long right tail (mean > median)
Negative skew: Long left tail (mean < median)
Zero skew: Symmetric distribution

Common applications:

Financial return analysis
Process control monitoring
Medical outcome distributions
Environmental data analysis
Population demographics
Response time studies

Provides multiple configuration options for detailed distribution analysis.

Table

Select

[column, ...]

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

Skewness

[, ...]

Configuration for skewness calculation, allowing control over bias correction in the statistical estimation.

Bias

bool

true

Controls bias correction in calculation:

true (default): Use biased moment estimators
false: Apply bias correction for small samples

Bias correction affects accuracy in small samples but increases variance.