R Language
데이터 프레임 집계

소개

베이스 R로 집계

이를 위해 다음과 같이 사용할 수있는 aggregate 함수를 사용합니다.

aggregate(formula,function,data)

다음 코드는 집계 함수를 사용하는 다양한 방법을 보여줍니다.

암호:

df = data.frame(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))

# sum, grouping by one column
aggregate(value~group, FUN=sum, data=df)

# mean, grouping by one column
aggregate(value~group, FUN=mean, data=df)

# sum, grouping by multiple columns
aggregate(value~group+subgroup,FUN=sum,data=df)

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

산출:

> df = data.frame(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(df)
    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
> aggregate(value~group, FUN=sum, data=df)
    group value
1 Group 1   4.5
2 Group 2   4.5
> 
> # mean, grouping by one column
> aggregate(value~group, FUN=mean, data=df)
    group value
1 Group 1  2.25
2 Group 2  1.50
> 
> # sum, grouping by multiple columns
> aggregate(value~group+subgroup,FUN=sum,data=df)
    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.
> aggregate(value~group, FUN=function(x) sum(x[x>2]), data=df)
    group value
1 Group 1   2.5
2 Group 2   0.0

dplyr로 집계

dplyr로 집계하는 것은 쉽습니다! 이를 위해 group_by () 및 summarize () 함수를 사용할 수 있습니다. 몇 가지 예가 아래에 나와 있습니다.

암호:

# Aggregating with dplyr
library(dplyr)

df = data.frame(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(df)

# sum, grouping by one column
df %>% group_by(group) %>% summarize(value = sum(value)) %>% as.data.frame()

# mean, grouping by one column
df %>% group_by(group) %>% summarize(value = mean(value)) %>% as.data.frame()

# sum, grouping by multiple columns
df %>% group_by(group,subgroup) %>% summarize(value = sum(value)) %>% as.data.frame()

# custom function, grouping by one column
# in this example we want the sum of all values larger than 2 per group.
df %>% group_by(group) %>% summarize(value = sum(value[value>2])) %>% as.data.frame()

산출:

> library(dplyr)
> 
> df = data.frame(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(df)
    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
> df %>% group_by(group) %>% summarize(value = sum(value)) %>% as.data.frame()
    group value
1 Group 1   4.5
2 Group 2   4.5
> 
> # mean, grouping by one column
> df %>% group_by(group) %>% summarize(value = mean(value)) %>% as.data.frame()
    group value
1 Group 1  2.25
2 Group 2  1.50
> 
> # sum, grouping by multiple columns
> df %>% group_by(group,subgroup) %>% summarize(value = sum(value)) %>% as.data.frame()
    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.
> df %>% group_by(group) %>% summarize(value = sum(value[value>2])) %>% as.data.frame()
    group value
1 Group 1   2.5
2 Group 2   0.0

data.table로 집계하기

data.table 패키지를 사용하여 그룹화하는 것은 dt[i, j, by] 구문을 사용하여 수행됩니다. " dt를 가져 와서 i를 사용하여 행을 부분 집합 한 다음 j로 그룹화합니다. "dt 문 내에서 , 여러 계산 또는 그룹을 목록에 넣어야합니다. list() 의 별칭은 .() 이므로 둘 다 서로 바꿔서 사용할 수 있습니다. 아래 예제에서는 .() 사용 .() .

암호:

# 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]

산출:

> # 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