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Often you may be interested in counting the number of observations by group in R.

Fortunately this is easy to do using the count() function from the dplyr library.

This tutorial explains several examples of how to use this function in practice using the following data frame:

#create data frame df #view data frame df team position points 1 A G 4 2 A G 13 3 A F 7 4 B G 8 5 B F 15 6 B F 15 7 B F 17 8 B G 9 9 C G 21 10 C F 22 11 C F 25 12 C F 31

**Example 1: Count by One Variable**

The following code shows how to count the total number of players by team:

library(dplyr) #count total observations by variable 'team' df %>% count(team) # A tibble: 3 x 2 team n 1 A 3 2 B 5 3 C 4

From the output we can see that:

- Team A has 3 players
- Team B has 5 players
- Team C has 4 players

This single count() function gives us a nice idea of the distribution of players by team.

Note that we can also **sort **the counts if we’d like:

#count total observations by variable 'team' df %>% count(team, sort=TRUE) # A tibble: 3 x 2 team n 1 B 5 2 C 4 3 A 3

**Example 2: Count by Multiple Variables**

We can also sort by more than one variable:

#count total observations by 'team' and 'position' df %>% count(team, position) # A tibble: 6 x 3 team position n 1 A F 1 2 A G 2 3 B F 3 4 B G 2 5 C F 3 6 C G 1

From the output we can see that:

- Team A has 1 player at the ‘F’ (forward) position and 2 players at the ‘G’ (guard) position.
- Team B has 3 players at the ‘F’ (forward) position and 2 players at the ‘G’ (guard) position.
- Team C has 3 players at the ‘F’ (forward) position and 1 player at the ‘G’ (guard) position.

**Example 3: Weighted Count**

We can also “weight” the counts of one variable by another variable. For example, the following code shows how to count the total observations per team, using the variable ‘points’ as the weight:

df %>% count(team, wt=points) # A tibble: 3 x 2 team n 1 A 24 2 B 64 3 C 99

*You can find the complete documentation for the count() function here.*