How to Filter Columns

This workflow demonstrates several approaches to filtering columns in a dataset, using different criteria such as name patterns, explicit exclusions, and data types. It guides you through selecting only the columns you need for further analysis.

• Select columns based on naming patterns to quickly isolate related data.
• Exclude sensitive or irrelevant columns to streamline datasets.
• Filter columns by data type to focus on specific kinds of information.

The workflow first shows how to select columns whose names match a specific pattern, such as all columns starting with "capital". This helps you quickly isolate groups of related columns without manually specifying each one.

Next, it demonstrates how to remove a particular column, such as one containing sensitive payment information, from your dataset. This step ensures that only the necessary data moves forward in your process.

Finally, the workflow filters columns based on their data type, such as keeping only those that contain text. This is useful when you want to focus your analysis on a particular kind of data, like product names or categories.