Removing partial duplicates
Now that you've identified and removed the full duplicates, it's time to check for partial duplicates. Partial duplicates are a bit tricker to deal with than full duplicates. In this exercise, you'll first identify any partial duplicates and then practice the most common technique to deal with them, which involves dropping all partial duplicates, keeping only the first.
dplyr is loaded and bike_share_rides is available.
Deze oefening maakt deel uit van de cursus
Cleaning Data in R
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Find duplicated ride_ids
bike_share_rides %>%
# Count the number of occurrences of each ride_id
___ %>%
# Filter for rows with a count > 1
___