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.
Este ejercicio forma parte del curso
Data Manipulation in Julia
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
println(size(wages))
# Drop all missing values
____
# Print describe and size functions
println(____)
println(____)