R 如何在列表中存储函数的输出

这是我的数据帧的一个子集

library(arsenal)
library(tidyverse)

   mydata2=structure(list(Hospital = structure(c(1L, 1L, 2L, 3L, 4L, 5L, 
4L, 2L, 4L, 3L, 2L, 1L, 3L, 3L, 1L, 4L, 4L, 4L, 5L, 5L, 1L, 4L, 
4L, 1L, 1L, 5L, 2L, 4L, 4L, 5L, 1L, 2L, 2L, 5L, 1L, 5L, 1L, 1L, 
4L, 2L, 4L, 4L, 2L, 1L, 4L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 4L, 2L, 
2L, 4L, 4L, 1L, 3L, 3L, 5L, 4L, 2L, 5L, 1L, 4L, 1L, 4L, 4L, 2L, 
2L, 2L, 2L, 3L, 1L, 3L, 1L, 3L, 5L, 5L, 4L, 3L, 3L, 2L, 3L, 1L, 
1L, 1L, 5L, 3L, 1L, 1L, 2L, 1L, 2L, 4L, 3L, 3L, 1L, 2L, 5L, 1L, 
3L, 2L, 2L, 1L, 1L, 1L, 2L), .Label = c("A", "B", "C", "D", "E"
), class = "factor"), ZipCode = structure(c(1L, 5L, 16L, 23L, 
42L, 18L, 46L, 49L, 36L, 61L, 33L, 28L, 58L, 60L, 3L, 40L, 8L, 
45L, 35L, 37L, 55L, 45L, 14L, 15L, 59L, 41L, 42L, 44L, 42L, 41L, 
17L, 49L, 43L, 34L, 55L, 41L, 52L, 63L, 42L, 38L, 8L, 45L, 49L, 
7L, 13L, 26L, 63L, 39L, 59L, 38L, 59L, 50L, 8L, 49L, 38L, 45L, 
43L, 53L, 24L, 22L, 34L, 48L, 33L, 29L, 62L, 42L, 32L, 48L, 33L, 
19L, 49L, 49L, 38L, 25L, 4L, 51L, 30L, 57L, 47L, 35L, 9L, 23L, 
51L, 12L, 58L, 63L, 59L, 27L, 37L, 57L, 2L, 54L, 38L, 56L, 49L, 
64L, 11L, 20L, 56L, 49L, 34L, 21L, 23L, 49L, 49L, 10L, 31L, 59L, 
6L), .Label = c("27000", "45490", "72470", "75011", "75015", 
"75018", "76480", "77270", "77340", "77350", "77380", "77440", 
"77580", "77C01", "78125", "78200", "80000", "91090", "91100", 
"91130", "91160", "91200", "91210", "91270", "91350", "91410", 
"91540", "91700", "92000", "92220", "92310", "92350", "93000", 
"93100", "93110", "93120", "93130", "93150", "93200", "93220", 
"93230", "93270", "93290", "93300", "93420", "93440", "93500", 
"93600", "93700", "94110", "94190", "94200", "94230", "94240", 
"94250", "94270", "94290", "94310", "94400", "94480", "94520", 
"94550", "94800", "95190"), class = "factor")), row.names = c(NA, 
-109L), class = "data.frame")

我创建了一个函数，允许我计算每家医院的第一个n Zipcode，它占住院人数的60%。然后，我想将每个医院的Zipcode存储在向量列表中

Zone<-function(choice){
  mydata2<-mydata2%>%filter(Hospital==choice)
  TABcode <-table(mydata2$ZipCode, useNA = "ifany")
  TABcode <- freqlist(TABcode, na.options = "include", digits.pct = 1)
  TABcode<-summary(sort(TABcode,decreasing = T))
  TABcode<-as.data.frame(TABcode$object)
  TABcode<-TABcode%>%filter(cumPercent<=60)
  TABcode$Var1
}

所以我想为所有医院做这件事。我们的目标是将所有输出存储在一个列表中，以便以后能够提取占住院人数60%的每家医院的邮政编码，如下所示。我需要一个功能，使我能够自动化所有这一切，因为我有数百家医院在我的完整数据集（这只是一个子集）

---

您的代码不可复制，因为您没有给我们

freqlist

，但这应该可以做到：

lapply(unique(mydata2$Hospital), Zone)

要保留医院ID，请执行以下操作：

ids <- unique(mydata2$Hospital)
result <- lapply(ids, Zone)
names(result) <- ids

---

ids我正在使用
data.table
库。我试着理解你的功能。我可能在这里犯了错误（例如，我不明白您为什么要对频率表进行排序）。另外，我注意到您的预期结果与此处输出中的区域不匹配。如果你有任何问题，请告诉我

library(data.table)
setDT(mydata2)
mydata2[, .N, by = .(Hospital, ZipCode)][, .(ZipCode, freq = cumsum(prop.table(N))), by = .(Hospital)][freq <= 0.6, ZipCode, by = .(Hospital)]

#Explanation of above one-liner by splitting the chain into parts
mydata2 <- mydata2[, .N, by = .(Hospital, ZipCode)] # find the total number in each zipcode in each hospital
mydata2 <- mydata2[, .(ZipCode, freq = cumsum(prop.table(N))), by = .(Hospital)]  # find the cumulative frequency of above for each hospital
mydata2[freq <= 0.6, ZipCode, by = .(Hospital)] # extract ZipCodes with less than or equal to 60% for each hospital

抱歉@Limey，
freklist
来自软件包
arsenal
。您的代码有效，但医院名称不再可用。它们被数字所取代
ids <- unique(mydata2$Hospital)
result <- lapply(ids, Zone)
names(result) <- ids

library(data.table)
setDT(mydata2)
mydata2[, .N, by = .(Hospital, ZipCode)][, .(ZipCode, freq = cumsum(prop.table(N))), by = .(Hospital)][freq <= 0.6, ZipCode, by = .(Hospital)]

#Explanation of above one-liner by splitting the chain into parts
mydata2 <- mydata2[, .N, by = .(Hospital, ZipCode)] # find the total number in each zipcode in each hospital
mydata2 <- mydata2[, .(ZipCode, freq = cumsum(prop.table(N))), by = .(Hospital)]  # find the cumulative frequency of above for each hospital
mydata2[freq <= 0.6, ZipCode, by = .(Hospital)] # extract ZipCodes with less than or equal to 60% for each hospital

#    Hospital ZipCode
# 1:        A   27000
# 2:        A   75015
# 3:        A   91700
# 4:        A   72470
# 5:        A   94250
# 6:        A   78125
# 7:        A   94400
# 8:        A   80000
# 9:        A   94200
#10:        A   94800
#11:        A   76480
#12:        A   91410
#13:        B   78200
#14:        B   93700
#15:        B   93000
#16:        B   93270
#17:        C   91210
#18:        C   94520
#19:        C   94310
#20:        C   94480
#21:        C   91270
#22:        C   91200
#23:        D   93270
#24:        D   93440
#25:        D   93120
#26:        D   93220
#27:        D   77270
#28:        E   91090
#29:        E   93110
#30:        E   93130
#    Hospital ZipCode