Actions8
- Descriptive Statistic Actions
- Finance Math Actions
- Group Aggregate Actions
- Outlier Analysis Actions
- Relationship Actions
Descriptive Statistic → Z Score
AI-generatedSummary
Calculate the z-score for each row based on a specified numeric column in the input data, appending the z-score as a new column to every output row.
Inputs
- Value Column (required) — Name of the numeric column in the input data used to calculate the z-scores.
- Result Column — Name of the column to add to the output data containing the calculated z-scores. Defaults to 'zScore'.
Output shape
A single JSON object including the original input rows augmented with an additional column for z-scores, plus metadata about the calculation such as mean, standard deviation, counts of valid and ignored values, a list of individual z-scores per row, warnings, and errors.
The operation validates and parses the numeric values. Rows with non-numeric or missing values for the specified column are recorded as ignored, and their z-scores are set to null. If the standard deviation is zero, z-scores cannot be computed and all scores will be null with a warning issued. The output includes both the list of rows with z-scores and a detailed scores array indexed by row.
Examples
Example 1: Calculate z-score of sales amounts.
Set 'Value Column' to the sales amount field name (e.g., 'sales'), and optionally specify a 'Result Column' name (e.g., 'salesZScore'). The node outputs the input data with an added column containing each row's z-score for sales.