Probably the most common filtering operation is to remove missing values.
For the examples below we’ll be using the Palmer Penguins data.
Launch the Transformation widget. Select the data frame that you want to filter.
Hover over the kebab icon to the right of any of the
NaNvalues in the
sexcolumn. Then click on the Filter values like this popup button.
A dialog appears with fields to choose a column, an operator and a value. The value is set to
NaNby default. Choose the
The preview is updated. Press thebutton.
The code is inserted into the notebook and run immediately. Records with missing values in the
sexcolumn are removed.