Missing values bring in a lot of chaos to the data. Thus, it is always important to deal with the missing values before we build any models.
Consider an example:
An employee data-set which consists of missing values:
The following code gives the number of missing values->
This code deletes the missing values:
So, you can use is.na to find the number of missing values, and na.omit to delete the missing values.