# How to Count Duplicates in R (With Examples)

You can use the following methods to count duplicates in a data frame in R:

Method 1: Count Duplicate Values in One Column

```sum(duplicated(df\$my_column))
```

Method 2: Count Duplicate Rows

`nrow(df[duplicated(df), ])`

Method 3: Count Duplicates for Each Unique Row

```library(dplyr)

df %>% group_by_all() %>% count```

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'),
position=c('G', 'G', 'G', 'F', 'G', 'G', 'F', 'F'),
points=c(5, 5, 8, 10, 5, 7, 10, 10))

#view data frame
df

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

## Example 1: Count Duplicate Values in One Column

The following code shows how to count the number of duplicate values in the points column:

```#count number of duplicate values in points column
sum(duplicated(df\$points))

 4```

We can see that there are 4 duplicate values in the points column.

## Example 2: Count Duplicate Rows

The following code shows how to count the number of duplicate rows in the data frame:

```#count number of duplicate rows
nrow(df[duplicated(df), ])

 2```

We can see that there are 2 duplicate rows in the data frame.

We can use the following syntax to view these 2 duplicate rows:

```#display duplicated rows
df[duplicated(df), ]

team position points
2    A        G      5
8    B        F     10
```

## Example 3: Count Duplicates for Each Unique Row

The following code shows how to count the number of duplicates for each unique row in the data frame:

```library(dplyr)

#count number of duplicate rows in data frame
df %>% group_by_all() %>% count

# A tibble: 6 x 4
# Groups:   team, position, points 
team  position points     n

1 A     F            10     1
2 A     G             5     2
3 A     G             8     1
4 B     F            10     2
5 B     G             5     1
6 B     G             7     1```

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