Table of Contents
To create a table and include NA values in R, you can use the data frame function to create a data frame containing the data you wish to include. To add NA values, you can use the is.na function to identify which values to replace with NA. Once the data is in the data frame and the NA values are identified, you can use the na.omit function to remove all rows that contain NA values. Finally, you can use the View command to check your table for accuracy.
By default, the table() function in R creates a table of frequency values but does not include the frequency of NA values.
However, you can use the following methods to create a table and include NA values:
Method 1: Create Table and Always Display Number of NA Values
table(df$my_column, useNA = "always") Method 2: Create Table and Only Display Number of NA Values if there are Some
table(df$my_column, useNA = "ifany")
The following examples show how to use each method in practice.
Example 1: Create Table and Always Display Number of NA Values
Suppose we have the following data frame in R that contains information about various basketball players:
#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),
points=c(20, 25, 14, 18, 19, 12, 12, 15))
#view data frame
df
team points
1 A 20
2 A 25
3 A 14
4 A 18
5 B 19
6 B 12
7 B 12
8 B 15
We can use the following syntax to create a table for the frequency of values in the team column and display the number of NA values whether or not any exist:
#create frequency table of values in team column, including NA values
table(df$team, useNA = "always")
A B <NA>
4 4 0
Notice that the resulting table shows that there are 0 NA values in the team column of the data frame.
Since we used the argument useNA = “always”, the table still displayed the number of NA values even though there weren’t any.
Example 2: Create Table and Only Display Number of NA Values if there are Some
Once again suppose we have the following data frame in R that contains information about various basketball players:
#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),
points=c(20, 25, 14, 18, 19, 12, 12, 15))
#view data frame
df
team points
1 A 20
2 A 25
3 A 14
4 A 18
5 B 19
6 B 12
7 B 12
8 B 15
#create frequency table of values in team column, including NA values if any exist
table(df$team, useNA = "ifany")
A B
4 4 Notice that the resulting table shows the frequency for the values “A” and “B” in the team column, but does not show the frequency of NA values since there aren’t any.
The following tutorials explain how to perform other common operations in R: