How to Filter for Unique Values Using dplyr


You can use the following methods to filter for unique values in a data frame in R using the dplyr package:

Method 1: Filter for Unique Values in One Column

df %>% distinct(var1)

Method 2: Filter for Unique Values in Multiple Columns

df %>% distinct(var1, var2)

Method 3: Filter for Unique Values in All Columns

df %>% distinct()

The following examples show how to use each method in practice with the following data frame in R:

#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),
                 points=c(10, 10, 8, 6, 15, 15, 12, 12),
                 rebounds=c(8, 8, 4, 3, 10, 11, 7, 7))

#view data frame
df

  team points rebounds
1    A     10        8
2    A     10        8
3    A      8        4
4    A      6        3
5    B     15       10
6    B     15       11
7    B     12        7
8    B     12        7

Example 1: Filter for Unique Values in Column

We can use the following code to filter for unique values in just the team column:

library(dplyr)

#select only unique values in team column
df %>% distinct(team)

  team
1    A
2    B

Notice that only the unique values in the team column are returned.

Example 2: Filter for Unique Values in Multiple Columns

We can use the following code to filter for unique values in the team and points columns:

library(dplyr)

#select unique values in team and points columns
df %>% distinct(team, points)

  team points
1    A     10
2    A      8
3    A      6
4    B     15
5    B     12

Notice that only the unique values in the team and points columns are returned.

Example 3: Filter for Unique Values in All Columns

We can use the following code to filter for unique values across all columns in the data frame:

library(dplyr)

#select unique values across all columns
df %>% distinct()

  team points rebounds
1    A     10        8
2    A      8        4
3    A      6        3
4    B     15       10
5    B     15       11
6    B     12        7

Notice that the unique values across all three columns are returned.

Note: You can find the complete documentation for the distinct function in dplyr here.

Additional Resources

The following tutorials explain how to perform other common operations in dplyr:

How to Select Columns by Index Using dplyr
How to Select the First Row by Group Using dplyr
How to Filter by Multiple Conditions Using dplyr
How to Filter Rows that Contain a Certain String Using dplyr

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