dplyr:如何在函数中使用group_by? [英] dplyr: How to use group_by inside a function?

查看:1016
本文介绍了dplyr:如何在函数中使用group_by?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我想在另一个函数中使用 dplyr :: group_by 函数,但是我不知道如何将参数传递给这个函数。



有人可以提供一个工作示例吗?

  library(dplyr)
data (iris)
iris%。%group_by(Species)%。%summarize(n = n())#
##来源:本地数据框[3 x 2]
##种n
## 1 virginica 50
## 2 versicolor 50
## 3 setosa 50

mytable0< - function(x,...)x% 。%group_by(...)%。%summary(n = n())
mytable0(iris,Species)#OK
##来源:本地数据帧[3 x 2]
##物种n
## 1 virginica 50
## 2 versicolor 50
## 3 setosa 50

mytable1< - function(x, key)x%。%group_by(as.name(key))%。%summarize(n = n())
mytable1(iris,Species)#错误!
#错误:列'as.name(key)'(SYMSXP)的不受支持的类型

mytable2< - function(x,key)x%。%group_by(key)%。 %summary(n = n())
mytable2(虹膜,物种)#错误!
#错误:index out of bounds


解决方案

对于编程, group_by _ group_by 的对应方:

  library(dplyr)

mytable< - function(x,...)x%>%group_by _(...)%>%summary (n = n())
mytable(iris,Species)
#或iris%>%mytable(Species)

其中:

 物种n 
1 setosa 50
2 versicolor 50
3 virginica 50

更新在这个时候,这个书写的dplyr使用%。%这是上面最初使用的,但现在%>%被赞成,所以改变了以上,以保持这个相关。



更新2 重新组合现在已被弃用,请改用group_by_。 p>

更新3 group_by_(list(...))现在变成 GROUP_BY _(...)在新版本的dplyr中按照Roberto的评论。



更新4 在评论中添加了小的变体。


I want to use use the dplyr::group_by function inside another function, but I do not know how to pass the arguments to this function.

Can someone provide a working example?

library(dplyr)
data(iris)
iris %.% group_by(Species) %.% summarise(n = n()) # 
## Source: local data frame [3 x 2]
##      Species  n
## 1  virginica 50
## 2 versicolor 50
## 3     setosa 50

mytable0 <- function(x, ...) x %.% group_by(...) %.% summarise(n = n())
mytable0(iris, "Species") # OK
## Source: local data frame [3 x 2]
##      Species  n
## 1  virginica 50
## 2 versicolor 50
## 3     setosa 50

mytable1 <- function(x, key) x %.% group_by(as.name(key)) %.% summarise(n = n())
mytable1(iris, "Species") # Wrong!
# Error: unsupported type for column 'as.name(key)' (SYMSXP)

mytable2 <- function(x, key) x %.% group_by(key) %.% summarise(n = n())
mytable2(iris, "Species") # Wrong!
# Error: index out of bounds

解决方案

For programming, group_by_ is the counterpart to group_by:

library(dplyr)

mytable <- function(x, ...) x %>% group_by_(...) %>% summarise(n = n())
mytable(iris, "Species")
# or iris %>% mytable("Species")

which gives:

     Species  n
1     setosa 50
2 versicolor 50
3  virginica 50

Update At the time this was written dplyr used %.% which is what was originally used above but now %>% is favored so have changed above to that to keep this relevant.

Update 2 regroup is now deprecated, use group_by_ instead.

Update 3 group_by_(list(...)) now becomes group_by_(...) in new version of dplyr as per Roberto's comment.

Update 4 Added minor variation suggested in comments.

这篇关于dplyr:如何在函数中使用group_by?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

查看全文
登录 关闭
扫码关注1秒登录
发送“验证码”获取 | 15天全站免登陆