You can use the argument na.rm = TRUE to exclude missing values when calculating descriptive statistics in R.

#calculate mean and exclude missing values
mean(x, na.rm = TRUE)

#calculate sum and exclude missing values 
sum(x, na.rm = TRUE)

#calculate maximum and exclude missing values 
max(x, na.rm = TRUE)

#calculate standard deviation and exclude missing values 
sd(x, na.rm = TRUE)

The following examples show how to use this argument in practice with both vectors and data frames.

Example 1: Use na.rm with Vectors

Suppose we attempt to calculate the mean, sum, max, and standard deviation for the following vector in R that contains some missing values:

#define vector with some missing values
x <- c(3, 4, 5, 5, 7, NA, 12, NA, 16)

mean(x)

[1] NA

sum(x)

[1] NA

max(x)

[1] NA

sd(x)

[1] NA

Each of these functions returns a value of NA.

To exclude missing values when performing these calculations, we can simply include the argument na.rm = TRUE as follows:

#define vector with some missing values
x <- c(3, 4, 5, 5, 7, NA, 12, NA, 16)

mean(x, na.rm = TRUE)

[1] 7.428571

sum(x, na.rm = TRUE)

[1] 52

max(x, na.rm = TRUE)

[1] 16

sd(x, na.rm = TRUE)

[1] 4.790864

Notice that we were able to complete each calculation successfully while excluding the missing values.

Example 2: Use na.rm with Data Frames

Suppose we have the following data frame in R that contains some missing values:

#create data frame
df <- data.frame(var1=c(1, 3, 3, 4, 5),
                 var2=c(7, 7, NA, 3, 2),
                 var3=c(3, 3, NA, 6, 8),
                 var4=c(1, 1, 2, 8, NA))

#view data frame
df

  var1 var2 var3 var4
1    1    7    3    1
2    3    7    3    1
3    3   NA   NA    2
4    4    3    6    8
5    5    2    8   NA

We can use the apply() function to calculate descriptive statistics for each column in the data frame and use the na.rm = TRUE argument to exclude missing values when performing these calculations:

#calculate mean of each column
apply(df, 2, mean, na.rm = TRUE)

var1 var2 var3 var4 
3.20 4.75 5.00 3.00 

#calculate sum of each column
apply(df, 2, sum, na.rm = TRUE)

var1 var2 var3 var4 
  16   19   20   12 

#calculate max of each column
apply(df, 2, max, na.rm = TRUE)

var1 var2 var3 var4 
   5    7    8    8 

#calculate standard deviation of each column
apply(df, 2, sd, na.rm = TRUE)

    var1     var2     var3     var4 
1.483240 2.629956 2.449490 3.366502

Once again, we were able to complete each calculation successfully while excluding the missing values.