R Language Aggregating data frames Aggregating with data.table


Example

Grouping with the data.table package is done using the syntax dt[i, j, by] Which can be read out loud as: "Take dt, subset rows using i, then calculate j, grouped by by." Within the dt statement, multiple calculations or groups should be put in a list. Since an alias for list() is .(), both can be used interchangeably. In the examples below we use .().

CODE:

# Aggregating with data.table
library(data.table)

dt = data.table(group=c("Group 1","Group 1","Group 2","Group 2","Group 2"), subgroup = c("A","A","A","A","B"),value = c(2,2.5,1,2,1.5))
print(dt)

# sum, grouping by one column
dt[,.(value=sum(value)),group]

# mean, grouping by one column
dt[,.(value=mean(value)),group]

# sum, grouping by multiple columns
dt[,.(value=sum(value)),.(group,subgroup)]

# custom function, grouping by one column
# in this example we want the sum of all values larger than 2 per group.
dt[,.(value=sum(value[value>2])),group]

OUTPUT:

> # Aggregating with data.table
> library(data.table)
> 
> dt = data.table(group=c("Group 1","Group 1","Group 2","Group 2","Group 2"), subgroup = c("A","A","A","A","B"),value = c(2,2.5,1,2,1.5))
> print(dt)
     group subgroup value
1: Group 1        A   2.0
2: Group 1        A   2.5
3: Group 2        A   1.0
4: Group 2        A   2.0
5: Group 2        B   1.5
> 
> # sum, grouping by one column
> dt[,.(value=sum(value)),group]
     group value
1: Group 1   4.5
2: Group 2   4.5
> 
> # mean, grouping by one column
> dt[,.(value=mean(value)),group]
     group value
1: Group 1  2.25
2: Group 2  1.50
> 
> # sum, grouping by multiple columns
> dt[,.(value=sum(value)),.(group,subgroup)]
     group subgroup value
1: Group 1        A   4.5
2: Group 2        A   3.0
3: Group 2        B   1.5
> 
> # custom function, grouping by one column
> # in this example we want the sum of all values larger than 2 per group.
> dt[,.(value=sum(value[value>2])),group]
     group value
1: Group 1   2.5
2: Group 2   0.0