通过在R的每个回合中添加新的子集变量来重复子集函数

问题描述

我有一个函数(foo)可以对列表L中的任何变量进行子集化.完美的作品！但是我可以默认将变量weeks添加到子集的变量中吗?

I have a function (foo) to subset any variable from the list L. It works perfect! But can I by default add variable weeks to whatever variable being subsetted?

例如，假设我想对type == 1进行子集设置，我是否还可以默认将weeks的所有唯一值(在我的数据weeks具有3唯一值，但不包括NA)添加到循环时尚:

For example, suppose I want to subset type == 1, can I also by default add all unique values of weeks (in my data weeks has 3 unique values excluding NA) to that in a looped fashion:

type==1 & weeks==1(第1回合); type==1 & weeks==2(第二回合); type==1 & weeks==3(第三回合)

type==1 & weeks==1(Round 1) ; type==1 & weeks==2(Round 2) ; type==1 & weeks==3(Round 3)

foo <- function(List, what){     
  s <- substitute(what) 
  h <- lapply(List, function(x) do.call("subset", list(x, s)))
 h1 <- Filter(NROW, h)      
 h2 <- lapply(List[names(h1)], function(x) subset(x, control))
 Map(rbind, h1, h2)      
}
## EXAMPLE OF USE:
D <- read.csv("https://raw.githubusercontent.com/rnorouzian/m/master/k.csv", h = T) # DATA
L <- split(D, D$study.name) ; L[[1]] <- NULL   # list `L`
## RUN:
foo(L, type == 1)  # Requested
# Repeat Requested above in a loop:
foo(L, type==1 & weeks==1) # (Round 1)
foo(L, type==1 & weeks==2) # (Round 2)
foo(L, type==1 & weeks==3) # (Round 3)

推荐答案

您可以这样做:

foo <- function(List, what, time = 1){     
  s <- substitute(what)
  s <- bquote(.(s) & weeks == time)
  h <- lapply(List, function(x) do.call("subset", list(x, s)))
 h1 <- Filter(NROW, h)      
 h2 <- lapply(List[names(h1)], function(x) subset(x, control))
 Map(rbind, h1, h2)      
}

# AND THEN:
lapply(1:3, function(i) foo(L, type == 1, time = i))

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