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Sklearn Simple Imputer

Handle missing values using scikit-learn SimpleImputer

Actions2

Transform

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Summary

Transform data by imputing missing values in specified columns using a fitted scikit‑learn SimpleImputer.

Inputs

  • imputerData (required) — JSON string containing the fitted imputer
  • transformColumns (required) — Comma-separated list of columns to transform
  • pythonPath — Path to the Python executable with scikit‑learn installed

Output shape

a list of workflow items with imputed values for the specified columns

When operation is 'fitTransform' the items also include imputer statistics; 'transform' returns only imputed values.

Examples

Example 1: Fit and transform missing values in 'age' and 'salary' using mean strategy

operation=transform, imputerData='', transformColumns='age,salary', strategy='mean'

Example 2: Transform using a previously fitted imputer

operation=transform, imputerData='', transformColumns='id', strategy='median'

Example 3: Use constant fill value for missing entries

operation=transform, imputerData='', transformColumns='score', strategy='constant', fillValue='0'

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