Chapter 24 16. Discussion Question: NA vs Zero

In this practice, we used values_drop_na = TRUE. This removes missing values while reshaping the dataset.

This can be reasonable when we know that missing values represent combinations that were not recorded in the dataset. However, an NA is not always the same as zero:

• NA means the value is missing or unknown.
• 0 means the value is known and equal to zero.

Before dropping missing values, it is important to understand how missing values are used in the dataset.