You can use the following methods to find duplicate elements in a data frame using dplyr:

Method 1: Display All Duplicate Rows

library(dplyr)

#display all duplicate rows
df %>%
  group_by_all() %>%
  filter(n()>1) %>%
  ungroup()

Method 2: Display Duplicate Count for All Duplicated Rows

library(dplyr)#display duplicate count for all duplicated rows
df %>%
  add_count(col1, col2, col3) %>%
  filter(n>1) %>%
  distinct()

This tutorial explains how to use each method in practice with the following data frame:

#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),
                 position=c('G', 'G', 'F', 'F', 'G', 'G', 'F', 'F'),
                 points=c(10, 10, 8, 14, 15, 15, 17, 17))

#view data frame
df

  team position points
1    A        G     10
2    A        G     10
3    A        F      8
4    A        F     14
5    B        G     15
6    B        G     15
7    B        F     17
8    B        F     17

Example 1: Display All Duplicate Rows

The following code shows how to display all duplicate rows in the data frame:

library(dplyr)

#display all duplicate rows in data frame
df %>%
  group_by_all() %>%
  filter(n()>1) %>%
  ungroup()

# A tibble: 6 x 3
  team  position points
        
1 A     G            10
2 A     G            10
3 B     G            15
4 B     G            15
5 B     F            17
6 B     F            17

The result is a data frame that contains 6 rows, each of which is a duplicated row.

Note: If you only want to know which rows have duplicate values across specific columns, you could use something like group_by(team) instead to find rows that have duplicate values in the team column only.

Example 2: Display Duplicate Count for All Duplicated Rows

The following code shows how to display the duplicate count for all of the duplicated rows in the data frame:

library(dplyr)

#display duplicate count for each row
df %>%
  add_count(team, position, points) %>%
  filter(n>1) %>%
  distinct()

  team position points n
1    A        G     10 2
2    B        G     15 2
3    B        F     17 2

The n column displays the total number of duplicates for each row.

For example:

• The row with values A, G, and 10 occurs 2 times in the data frame.
• The row with values B, G, and 15 occurs 2 times in the data frame.
• The row with values B, F, and 17 occurs 2 times in the data frame.

Note: If you only want to know which rows have duplicate values across specific columns, then only include those specific columns within the add_count() function.