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How to Filter Rows

Filtering rows is a core data analysis task that lets you focus on the most relevant records in your dataset. By applying different criteria, you can isolate, review, or act on subsets of data that meet specific business needs.

Data basics how-toData Transformation
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Workflow
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How to Filter Rows

How This Workflow Works

This workflow demonstrates several practical methods for filtering rows in the Adult dataset. It applies a range of conditions, such as pattern matching, exclusion of missing values, or row number, to extract targeted subsets, helping you analyze only the records that matter for your scenario.

Key Features:

  • Filter by matching pattern or by matching pattern with wildcard
  • Retain only rows without missing records
  • Isolate rows included in a specific numeric range
  • Isolate data based on custom numeric criteria

Step-by-step:

1. Apply Pattern-based Filters:

The workflow shows how to narrow down the dataset by selecting a specific income pattern, or by matching country patterns with a wildcard.

2. Retain Only Non-Missing Values and Data by Range:

Next, the workflow demonstrates how to exclude entries with missing values, retain only the last ten rows, and filter records within a defined range.

3. Separate and Compare Data Subsets:

Finally, the workflow splits the filtered data into included and excluded groups, allowing you to compare or further process each subset independently. This supports more detailed analysis or reporting based on your filtering criteria.

How to Get Started