R-按组名求和并重新计算列

我使用R从Google Analytics API获取一些数据。在这个特定的场景中，我获得了按性别和年龄组划分的用户的亲和力兴趣信息。我得到的数据结构与以下类似：

gender ageGroup interest        sessions
male   18-24    Autos           4
male   18-24    Autos/Luxury    1
male   18-24    Autos/Vans      1
male   25-34    Autos           8
male   25-34    Autos/Luxury    2
male   25-34    Autos/Vans      2
male   25-34    Autos/Compacts  1
...
female 65+      Fashion         20

然而，这种结构的问题是，作为主要兴趣的汽车也包含子类别的会话，如果我在透视表中使用这些数据，我将得到错误的信息

因此，我将子类别“通才”添加到每个主要类别中，作为其自己的子类别，并将此列一分为二：

for (i2 in 1:nrow(ga.genderAgeAffinityTable) ) {

# main categories <- chrFound = integer(0)            
chrFound <- grep("[/]", ga.genderAgeAffinityTable$interest[i2] )

if (length(chrFound) < 1) {
ga.genderAgeAffinityTable$interest[i2] <- 
sprintf("%s/Generalists", ga.genderAgeAffinityTable$interest[i2])
}

ga.genderAgeAffinityTable <- as.data.frame
(cSplit(ga.genderAgeAffinityTable, "interest", sep = "/"))

}

View(ga.genderAgeAffinityTable)

            gender ageGroup interest        subcategory        sessions
            male   18-24    Autos           Generalists        4
            male   18-24    Autos           Luxury             1
            male   18-24    Autos           Vans               1
            male   25-34    Autos           Generalists        8
            male   25-34    Autos           Luxury             2
            male   25-34    Autos           Vans               2
            male   25-34    Autos           Compacts           1
            ...
            female 65+      Fashion         Generalists        20

for（i2 in 1:nrow（ga.genderAgeAffinityTable））{
#主要类别您看过
data.table
包了吗？它具有惊人的汇总功能，可能会对您有所帮助

e、 g

解决方案
分阶段构建，以帮助解释和展示它的强大。这将得到除多面手之外的所有东西的总和

notgensum <- DT[subcategory  != "Generalists", mysum := sum(sessions),
                by = .(gender, ageGroup, interest)]

    gender ageGroup interest subcategory sessions mysum
1:   male    18-24    Autos Generalists        4    NA
2:   male    18-24    Autos      Luxury        1     2
3:   male    18-24    Autos        Vans        1     2
4:   male    25-34    Autos Generalists        8    NA
5:   male    25-34    Autos      Luxury        2     5
6:   male    25-34    Autos        Vans        2     5
7:   male    25-34    Autos    Compacts        1     5

最后，如果您想摆脱mysum临时列，语法是

genadjsum3[, mysum := NULL]

你会喜欢没有循环！
我想这里的很多人都会乐意帮助你，但你的例子并不完全是一个
最小可重复性的例子
library(data.table)
DT <- data.table(gender = c("male", "male", "male", "male", "male","male", "male"), 
ageGroup = c("18-24", "18-24", "18-24", "25-34","25-34", "25-34", "25-34"),
interest = c("Autos", "Autos", "Autos","Autos", "Autos", "Autos", "Autos"),
subcategory = c("Generalists","Luxury", "Vans", "Generalists", "Luxury", "Vans", "Compacts"), 
sessions = c(4L, 1L, 1L, 8L, 2L, 2L, 1L) )

notgensum <- DT[subcategory  != "Generalists", mysum := sum(sessions),
                by = .(gender, ageGroup, interest)]

    gender ageGroup interest subcategory sessions mysum
1:   male    18-24    Autos Generalists        4    NA
2:   male    18-24    Autos      Luxury        1     2
3:   male    18-24    Autos        Vans        1     2
4:   male    25-34    Autos Generalists        8    NA
5:   male    25-34    Autos      Luxury        2     5
6:   male    25-34    Autos        Vans        2     5
7:   male    25-34    Autos    Compacts        1     5

genadjsum2 <- notgensum[, myadjsessions := (sessions - mean(mysum, na.rm = T)),
                        by = .(gender, ageGroup, interest)]

#   gender ageGroup interest subcategory sessions mysum myadjsessions   
#1:   male    18-24    Autos Generalists        4    NA             2
#2:   male    18-24    Autos      Luxury        1     2            -1
#3:   male    18-24    Autos        Vans        1     2            -1
#4:   male    25-34    Autos Generalists        8    NA             3
#5:   male    25-34    Autos      Luxury        2     5            -3
#6:   male    25-34    Autos        Vans        2     5            -3
#7:   male    25-34    Autos    Compacts        1     5            -4

genadjsum3 <- notgensum[, 
             myadjsessions := (sessions - mean(mysum, na.rm = T)),
             by = .(gender, ageGroup, interest)][subcategory  == "Generalists"]

#  gender ageGroup interest subcategory sessions mysum myadjsessions
#1:   male    18-24    Autos Generalists        4    NA             2
#2:   male    25-34    Autos Generalists        8    NA             3

genadjsum3[, mysum := NULL]