I'm working with a large dataset and doing some calculation with the aggregate() function.
我正在使用大型数据集并使用aggregate()函数进行一些计算。
This time I need to group by two different columns and for my calculation I need a user defined function that also uses two columns of the data.frame. That's where I'm stuck.
这次我需要按两个不同的列进行分组,对于我的计算,我需要一个用户定义的函数,它也使用data.frame的两列。那就是我被困住的地方。
Here's an example data set:
这是一个示例数据集:
dat <- data.frame(Kat = c("a","b","c","a","c","b","a","c"),
Sex = c("M","F","F","F","M","M","F","M"),
Val1 = c(1,2,3,4,5,6,7,8)*10,
Val2 = c(2,6,3,3,1,4,7,4))
> dat
Kat Sex Val1 Val2
a M 10 2
b F 20 6
c F 30 3
a F 40 3
c M 50 1
b M 60 4
a F 70 7
c M 80 4
Example of user defined function:
用户定义函数示例:
sum(Val1 * Val2) # but grouped by Kat and Sex
I tried this:
我试过这个:
aggregate((dat$Val1),
by = list(dat$Kat, dat$Sex),
function(x, y = dat$Val2){sum(x*y)})
Output:
Group.1 Group.2 x
a F 1710
b F 600
c F 900
a M 300
b M 1800
c M 2010
But my expected output would be:
但我的预期输出是:
Group.1 Group.2 x
a F 610
b F 120
c F 90
a M 20
b M 240
c M 370
Is there any way to do this with aggregate()?
有没有办法用aggregate()做到这一点?
Thank you in advance!
先感谢您!
1 个解决方案
#1
2
As @jogo suggested :
正如@jogo建议:
aggregate(Val1 * Val2 ~ Kat + Sex, FUN = sum, data = dat)
Or in a tidyverse
style
或者是整齐的风格
library(dplyr)
dat %>%
group_by(Kat, Sex) %>%
summarize(sum(Val1 * Val2))
Or with data.table
或者使用data.table
library(data.table)
setDT(dat)
dat[ , sum(Val1 * Val2), by = list(Kat, Sex)]
#1
2
As @jogo suggested :
正如@jogo建议:
aggregate(Val1 * Val2 ~ Kat + Sex, FUN = sum, data = dat)
Or in a tidyverse
style
或者是整齐的风格
library(dplyr)
dat %>%
group_by(Kat, Sex) %>%
summarize(sum(Val1 * Val2))
Or with data.table
或者使用data.table
library(data.table)
setDT(dat)
dat[ , sum(Val1 * Val2), by = list(Kat, Sex)]