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.
Den här övningen är en del av kursen
Data Manipulation in Julia
Interaktiv övning med praktiskt arbete
Testa den här övningen genom att slutföra den här exempelkoden.
println(size(wages))
# Drop all missing values
____
# Print describe and size functions
println(____)
println(____)