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
NaN
values in thesex
column. 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
NaN
by default. Choose the!=
operator. -
The preview is updated. Press the
button. -
The code is inserted into the notebook and run immediately. Records with missing values in the
sex
column are removed.
-
Group and aggregate records to generate summary data.