You can use the NMISS function in SAS to count the number of missing values for each numeric variable in a dataset.

Here is one common way to use this function in practice:

proc meansdata=my_data nmiss;
run;

This particular example will count the number of missing values for each numeric variable in the dataset called my_data.

The following example shows how to use NMISS in practice.

Example: Use NMISS in SAS to Count Number of Missing Values for Each Numeric Variable

Suppose we have the following dataset in SAS called my_data that contains information about various basketball players:

/*create dataset*/
data my_data;
    input team $ points assists rebounds;
    datalines;
A 10 2 .
A 17 5 .
A 17 . .
A 18 3 4
A 15 0 5
B . 4 5
B 29 0 8
B . 2 9
C 12 1 9
. 30 1 .
;
run;

/*view dataset*/
proc printdata=my_data;

Notice that there are missing values for each variable in the dataset.

We can use the NMISS function to count the number of missing values in each variable:

/*count number of missing values in each variable*/proc meansdata=my_data nmiss;
run;

From the output table we can see:

• The points variable has 2 missing values.
• The assists variable has 1 missing value.
• The rebounds variable has 4 missing values.

And so on.

By default, the NMISS function does not count the number of missing values for character variables in a dataset.

/*count number of missing values for team variable*/proc sql; 
    select nmiss(team) as missing_team_values
    from my_data;
quit;

From the output we can see that there is 1 missing value in the team column.

Note: You can find the complete documentation for the SAS NMISS function .

The following tutorials explain how to perform other common tasks in SAS: