# How to Calculate the Sum by Group in R (With Examples)

Often you may want to calculate the sum by group in R. There are three methods you can use to do so:

Method 1: Use base R.

`aggregate(df\$col_to_aggregate, list(df\$col_to_group_by), FUN=sum) `

Method 2: Use the dplyr() package.

```library(dplyr)

df %>%
group_by(col_to_group_by) %>%
summarise(Freq = sum(col_to_aggregate))
```

Method 3: Use the data.table package.

```library(data.table)

dt[ ,list(sum=sum(col_to_aggregate)), by=col_to_group_by]
```

The following examples show how to use each of these methods in practice.

### Method 1: Calculate Sum by Group Using Base R

The following code shows how to use the aggregate() function from base R to calculate the sum of the points scored by team in the following data frame:

```#create data frame
df <- data.frame(team=c('a', 'a', 'b', 'b', 'b', 'c', 'c'),
pts=c(5, 8, 14, 18, 5, 7, 7),
rebs=c(8, 8, 9, 3, 8, 7, 4))

#view data frame
df

team pts rebs
1    a   5    8
2    a   8    8
3    b  14    9
4    b  18    3
5    b   5    8
6    c   7    7
7    c   7    4

#find sum of points scored by team
aggregate(df\$pts, list(df\$team), FUN=sum)

Group.1  x
1       a 13
2       b 37
3       c 14
```

### Method 2: Calculate Sum by Group Using dplyr

The following code shows how to use the group_by() and summarise() functions from the dplyr package to calculate the sum of points scored by team in the following data frame:

```library(dplyr)

#create data frame
df <- data.frame(team=c('a', 'a', 'b', 'b', 'b', 'c', 'c'),
pts=c(5, 8, 14, 18, 5, 7, 7),
rebs=c(8, 8, 9, 3, 8, 7, 4))

#find sum of points scored by team
df %>%
group_by(team) %>%
summarise(Freq = sum(pts))

# A tibble: 3 x 2
team   Freq
<chr> <dbl>
1 a        13
2 b        37
3 c        14
```

### Method 3: Calculate Sum by Group Using data.table

The following code shows how to use the data.table package to calculate the sum of points scored by team in the following data frame:

```library(data.table)

#create data frame
df <- data.frame(team=c('a', 'a', 'b', 'b', 'b', 'c', 'c'),
pts=c(5, 8, 14, 18, 5, 7, 7),
rebs=c(8, 8, 9, 3, 8, 7, 4))

#convert data frame to data table
setDT(df)

#find sum of points scored by team
df[ ,list(sum=sum(pts)), by=team]

team sum
1:    a  13
2:    b  37
3:    c  14```

Notice that all three methods return identical results.

Note: If you have an extremely large dataset, the data.table method will work the fastest among the three methods listed here.