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.
Questo esercizio fa parte del corso
Data Manipulation in Julia
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
println(size(wages))
# Drop all missing values
____
# Print describe and size functions
println(____)
println(____)