Dropping missing values
Dropping missing values is the simplest way of handling them. While it sometimes makes sense to replace them, other times it is better to drop them altogether. In this exercise, you'll be working with the wages dataset, which contains missing values in all columns. So let's drop them all! Or not…
The wages dataset and the DataFrames package have been loaded for you.
Deze oefening maakt deel uit van de cursus
Data Manipulation in Julia
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
println(size(wages))
# Drop all missing values
____
# Print describe and size functions
println(____)
println(____)