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.
Это упражнение является частью курса
Data Manipulation in Julia
Интерактивное практическое упражнение
Попробуйте выполнить это упражнение, дополнив этот пример кода.
println(size(wages))
# Drop all missing values
____
# Print describe and size functions
println(____)
println(____)