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SAS stores missing values differently depending on the variable type.
It is important to understand how SAS handles missing values when you execute statements. Depending on the statements being used, SAS might handle missing values in different ways. For example, it might treat a missing value as the lowest possible value (e.g., frequency tables in PROC FREQ), or it might omit the value from the computation (e.g., regression).
Internally, SAS treats numeric missing values as an extremely small or an extremely large number. Most of the time, the user will probably not be affected by this. In general, if you are subsetting data or doing any kind of conditional logic based on continuous numeric values, you should always explicitly tell SAS how to handle missing values first.
Your SAS help manual will help you understand how missing values are treated in the statements you are executing.
SAS automatically detects blank cells in external data files as missing values. You do not need to enter a period character in blank cells.