r - 循环 r 中的字符串

Question

我想知道我的代码有什么问题而不是解决方案。我希望遍历一些字符串我的数据如下:

id    source    transaction

 1     a > b       6 > 0
 2     J > k       5
 3     b > c       4 > 0

我有一个列表，希望查看此列表并找到包含该元素的行并计算平均值。

mylist <- c ("a", "b") 

所以我想要的输出列表中的元素之一是

source  avg
a        6 
b        2      

我不知道谁来遍历列表并将它们发送到 csv 文件。我试过这个

mylist <- c( "a", "b" )

for(i in mylist)
{

  KeepData <- df [grepl(i, df$source), ]
   KeepData <- cSplit(KeepData, "transaction", ">", "long")

  avg<- mean(KeepData$transactions)
  result <- list(i,avg )

  write.table(result ,file="C:/Users.csv", append=TRUE,sep=",",col.names=FALSE,row.names=FALSE)

}

但它给了我“NA”结果并带有以下警告

Warning messages: 1: In mean.default(KeepData$transactions) :
argument is not numeric or logical: returning NA 2: In mean.default(KeepData$transactions) : argument is not numeric or logical: returning NA

Answer 1

我们可以使用 cSplit拆分“源”并将数据集转换为“长”格式，然后指定“i”，按“源”分组，得到mean '交易'(使用 data.table 方法)

library(splitstackshape)
cSplit(df1, "source", " > ", "long")[source %in% mylist, .(avg = mean(transaction)), source]
#   source avg
#1:      a   6
#2:      b   5

或者另一个选项是 separate_rows来自 tidyr转换为“长”格式，然后使用 dplyr方法 summarise按“来源”分组后

library(tidyr)
library(dplyr)
separate_rows(df1, source) %>%
        filter(source %in% mylist) %>%
        group_by(source) %>% 
        summarise(avg  = mean(transaction))

更新

对于新数据集('df2')，我们需要将两列拆分为'long'格式，然后得到 mean按“来源”分组的“交易”

cSplit(df2, 2:3,  " > ", "long")[source %in% my_list, .(avg = mean(transaction)), source]
#   source avg
#1:      a   6
#2:      b   2

for循环可以修改为

for(i in mylist) {
   KeepData <-  cSplit(df2, 2:3,  ">", "long")
   KeepData <- KeepData[grepl(i, source)]
   avg<- mean(KeepData$transaction)
   result <- list(i,avg )
   print(result)
   write.table(result ,file="C:/Users.csv", 
             append=TRUE,sep=",",col.names=FALSE,row.names=FALSE)
 }
#[[1]]
#[1] "a"

#[[2]]
#[1] 6

#[[1]]
#[1] "b"

#[[2]]
#[1] 2

数据

df1 <- structure(list(id = 1:3, source = c("a > b", "J > k", "b > c"
 ), transaction = c(6L, 5L, 4L)), .Names = c("id", "source", "transaction"
), class = "data.frame", row.names = c(NA, -3L))


df2 <- structure(list(id = 1:3, source = c("a > b", "J > k", "b > c"
), transaction = c("6 > 0", "5", "4 > 0")), .Names = c("id", 
"source", "transaction"), class = "data.frame", row.names = c(NA, 
-3L))