How to sum a variable by group in R

Question

I have a data frame of consisting two columns "Players" & "points"

x<-data.frame(Players=c("Player1","Player2","Player3","Player2","Player3","Player1"),points=c(10,20,30,13,17,18))

 Players points
1 Player1     10
2 Player2     20
3 Player3     30
4 Player2     13
5 Player3     17
6 Player1     18

I want to sort the data by players and sum the points:

Like this:

Players  x
1 Player1 28
2 Player2 33
3 Player3 47

 

Comments

how could I use mutate in dplyr to add variable x into the dataframe

---

Hi, @Jackiechan,

mutate(): compute and add new variables into a data table. It preserves existing variables. Look at the below picture for better understanding.

Eg: my_data %>% mutate(data_frama, X = [existing_var])

I hope this will be helpful.

Answer 1

Easily by using Aggregate Func():

aggregate(x$points, by=list(Players=x$Players), FUN=sum)

or By Using tapply:

tapply(x$points, x$Players, FUN=sum)

Answer 2

You can also try this way,

x_new = x %>% group_by(Players) %>% summarise(x = sum(points))

Comments

The first operator, i.e., the one after x_new, should be <- not =.

Answer 3

An advantage of the aggregate function is that it is already included in your Base R installation. Therefore we do not need to install any add-on packages.

The aggregate function can be used to calculate the summation of each group as follows.

aggregate(x = iris$Sepal.Length,               
          by = list(iris$Species),              
          FUN = sum)