Use this page to learn more about these built-in and custom transforms. For example, you can delete multipleĬan apply the Process numeric and Handle missing You can apply transforms to multiple columns at once. Some transforms operate in place, while others create a new output You can also add custom transformations using PySpark, Python (User-Defined Function), Transforms apply to the resulting dataframe.ĭata Wrangler includes built-in transforms, which you can use to transform columns without anyĬode.
Transform you add modifies your dataset and produces a new dataframe. When you add a transform, it adds a step to the data flow. Amazon SageMaker Data Wrangler provides numerous ML data transforms to streamline cleaning, transforming, andįeaturizing your data.
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