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How to Loop Over Subsamples of Data

Looping over subsamples of data means systematically processing distinct groups within a dataset—such as categories or classes—so you can analyze each group separately and compare results.

AutomationData TransformationData basics how-to
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Workflow
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How to Loop Over Subsamples of Data

How This Workflow Works

This workflow takes a dataset, loops over groups in a selected column, and then calculates summary statistics for each group. It repeats this process for every group in the column, collecting the results at each iteration for easy comparison.

Key Features:

  • Analyze each group in your data independently
  • Automatically compute summary statistics for both numeric and categorical columns
  • Aggregate results for side-by-side comparison
  • Reduce manual effort by automating repetitive analysis

Step-by-step:

1. Iterate Through Each Category:

The workflow loops over groups in a chosen column, such as iris species. It then processes each group one at a time, ensuring that the analysis is specific to each subset.

2. Compute Group-Specific Statistics:

For every group, the workflow calculates summary statistics. This includes measures like averages for numeric fields and frequency counts for categorical fields, providing a detailed profile for each group.

3. Aggregate and Organize Results:

After processing all groups, the workflow collects the results into a single, organized table. This makes it easy to compare statistics across all groups.

How to Get Started