Practical Data Wrangling

Filtering the rows of a dataframe

You can filter rows as a function of the content of a row using the filter() function. (Recall from the previous chapters that you used filtering steps to remove outliers and NA values.)

In the filter() function, each of the arguments following the first is what the documentation refers to as a logical predicate. In other words, each of the arguments are assertions that some logical expression should be true.

The logical expressions used for filtering are defined in terms of the column names of the input dataframe.  Here are some possible examples of logical predicates that could be used as arguments to the filter() function:

• column.name > 6
• column.name == "abc"
• !is.na( column.name )

A good application ...