Selecting unique rows
If you have a categorical variable stored in a factor, it is often useful to know what the individual categories are; you do this with the levels() function. For a tibble, the more general concept is to find rows with unique data. Following the terminology from SQL, this is done using the distinct() function. You can use it directly on your dataset, so you find unique combinations of a particular set of columns. For example, to find the unique combinations of values in the x, y, and z columns, you would write the following.
a_tibble %>%
distinct(x, y, z)
This exercise is part of the course
Introduction to Spark with sparklyr in R
Exercise instructions
A Spark connection has been created for you as spark_conn. A tibble attached to the track metadata stored in Spark has been pre-defined as track_metadata_tbl.
- Find the distinct values of the
artist_namecolumn fromtrack_metadata_tbl.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# track_metadata_tbl has been pre-defined
track_metadata_tbl
track_metadata_tbl %>%
# Only return rows with distinct artist_name
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