嵌套循环输出到 data.frame

Question

我在 R 中有两个数据集（下面的这些 table 只是较小的版本），我想将它们合并到一个新的数据框中。

> meetingtime2     
#two columns of datetime that class=factor

               ST                  ET
1 2014-12-22 07:00:00 2014-12-22 07:30:00
2 2014-12-22 07:30:00 2014-12-22 08:00:00
3 2014-12-22 08:00:00 2014-12-22 08:30:00
4 2014-12-22 08:30:00 2014-12-22 09:00:00
5 2014-12-22 09:00:00 2014-12-22 09:30:00

> roomdata2 
#three columns; Room=factor, Capacity=integer, Video Conference=numeric

   Room Capacity Video.Conference
1 0M02A       16                1
2 0M03A        8                0
3 0M03B       12                1

所需的输出将是一个 15 行乘 5 列的矩阵。简而言之，输出是每个房间的每个时间段。

#the following is a MANUALLY created output of what the first few rows should look like

    Room Capacity Video.Conference        ST                ET
 1 0M02A   16           1       2014-12-22 07:00:00 2014-12-22 07:30:00
 2 0M02A   16           1       2014-12-22 07:30:00 2014-12-22 08:00:00
 3 0M02A   16           1       2014-12-22 08:00:00 2014-12-22 08:30:00
 4 0M02A   16           1       2014-12-22 08:30:00 2014-12-22 09:00:00
 5 0M02A   16           1       2014-12-22 09:00:00 2014-12-22 09:30:00
 6 0M03A   16           1       2014-12-22 07:00:00 2014-12-22 07:30:00
 7 0M03A   16           1       2014-12-22 07:30:00 2014-12-22 08:00:00
#and so forth to 15 rows.

我试过使用嵌套循环

#note, the code is written so I can apply to a bigger (1000's of rows) dataset

 >mylist<-list() 
 >for(i in 1:(nrow(roomdata2)))   
   +{   for(j in 1:(nrow(meetingtime2)))   
 +mylist[[j]]<-      data.frame(roomdata2[i,1],roomdata2[i,2],roomdata2[i,3],
 +meetingtime2[j,1],meetingtime2[j,2])  
  } 
   >df<-do.call("rbind",mylist)  
>df

我得到的输出。我正在获取最后一个房间的所有时间段，而不是前面的房间

roomdata2.i..1. roomdata2.i..2. roomdata2.i..3.  meetingtime2.j..1.  meetingtime2.j..2.
1    0M03B          12             1         2014-12-22 07:00:00    2014-12-22 07:30:00
2    0M03B          12             1         2014-12-22 07:30:00    2014-12-22 08:00:00
3    0M03B          12             1         2014-12-22 08:00:00    2014-12-22 08:30:00
4    0M03B          12             1         2014-12-22 08:30:00    2014-12-22 09:00:00
5    0M03B          12             1         2014-12-22 09:00:00    2014-12-22 09:30:00

我知道我的代码远非正确，正在给我循环的最后一次迭代。

我看待这个的另一种方式是每次迭代的连续打印函数

 >for(i in 1:(nrow(roomdata2))) 
 >for(j in 1:(nrow(meetingtime2))) 
 >print(paste(roomdata2[i,1],roomdata2[i,2],roomdata2[i,3],
 +meetingtime2[j,1],meetingtime2[j,2]))

输出

 [1] "0M02A 16 1 2014-12-22 07:00:00 2014-12-22 07:30:00"
 [1] "0M02A 16 1 2014-12-22 07:30:00 2014-12-22 08:00:00"
 [1] "0M02A 16 1 2014-12-22 08:00:00 2014-12-22 08:30:00"
 [1] "0M02A 16 1 2014-12-22 08:30:00 2014-12-22 09:00:00"
 [1] "0M02A 16 1 2014-12-22 09:00:00 2014-12-22 09:30:00"
 [1] "0M03A 8 0 2014-12-22 07:00:00 2014-12-22 07:30:00"
 [1] "0M03A 8 0 2014-12-22 07:30:00 2014-12-22 08:00:00"
 [1] "0M03A 8 0 2014-12-22 08:00:00 2014-12-22 08:30:00"
 [1] "0M03A 8 0 2014-12-22 08:30:00 2014-12-22 09:00:00"
 [1] "0M03A 8 0 2014-12-22 09:00:00 2014-12-22 09:30:00"
 [1] "0M03B 12 1 2014-12-22 07:00:00 2014-12-22 07:30:00"
 [1] "0M03B 12 1 2014-12-22 07:30:00 2014-12-22 08:00:00"
 [1] "0M03B 12 1 2014-12-22 08:00:00 2014-12-22 08:30:00"
 [1] "0M03B 12 1 2014-12-22 08:30:00 2014-12-22 09:00:00"
 [1] "0M03B 12 1 2014-12-22 09:00:00 2014-12-22 09:30:00"

#however the values are not separated, they are just in one set of string for each row.

期望的结果是 table 就像上面直接的那样，但是每个值都在单独的列中的数据框（每个日期和时间都设置在一列中）。

我查看了列表，lapply，foreach，但我就是无法理解解决方案。任何帮助将不胜感激，我是初学者所以我很想学习。

干杯 *输入

>dput(meetingtime2)

结构（列表（ST =结构（1:5，.Label = c（“22/12/2014 7:00”， "22/12/2014 7:30", "22/12/2014 8:00", "22/12/2014 8:30", "22/12/2014 9:00 “ ), class = "factor"), ET = 结构(1:5, .Label = c("22/12/2014 7:30", "22/12/2014 8:00", "22/12/2014 8:30", "22/12/2014 9:00", "22/12/2014 9:30 “ ), class = "factor")), .Names = c("ST", "ET"), row.names = c(NA, -5L), class = "data.frame")

>dput(roomdata2)

结构（列表（房间=结构（1:3，.Label = c（“0M02A”，“0M03A”， "0M03B"), class = "factor"), 容量 = c(16L, 8L, 12L), Video.Conference = c(1L, 0L, 1L)), .Names = c("Room", "Capacity", "Video.Conference"), row.names = c(NA, -3L), class = "data.frame")

Answer 1

使用您的数据：

meetingtime2 <- read.csv(text = "ST,ET
2014-12-22 07:00:00,2014-12-22 07:30:00
2014-12-22 07:30:00,2014-12-22 08:00:00
2014-12-22 08:00:00,2014-12-22 08:30:00
2014-12-22 08:30:00,2014-12-22 09:00:00
2014-12-22 09:00:00,2014-12-22 09:30:00")

roomdata2 <- read.csv(text = "Room,Capacity,Video_Conference
0M02A,16,1
0M03A,8,0
0M03B,12,1")

然后 merge 方便地 returns 笛卡尔积，因为 none 的列匹配。

merge(meetingtime2, roomdata2)[, c(3:5, 1:2)]

##     Room Capacity Video_Conference                  ST                  ET
## 1  0M02A       16                1 2014-12-22 07:00:00 2014-12-22 07:30:00
## 2  0M02A       16                1 2014-12-22 07:30:00 2014-12-22 08:00:00
## 3  0M02A       16                1 2014-12-22 08:00:00 2014-12-22 08:30:00
## 4  0M02A       16                1 2014-12-22 08:30:00 2014-12-22 09:00:00
## 5  0M02A       16                1 2014-12-22 09:00:00 2014-12-22 09:30:00

Answer 2

这很丑陋，但应该可以完成工作。给定以下数据：

ST <- c('2014-12-22 07:00:00', '2014-12-22 07:30:00', '2014-12-22 08:00:00', '2014-12-22 08:30:00', '2014-12-22 09:00:00')
ET <- c('2014-12-22 07:30:00', '2014-12-22 08:00:00', '2014-12-22 08:30:00', '2014-12-22 09:00:00', '2014-12-22 09:30:00')

RoomName <- c('0M02A', '0M03A', '0M03B')
Capacity <- c(16, 8, 12)
VideoCap <- c(1, 0, 1)

Times <- data.frame(ST, ET, stringsAsFactors = FALSE)
Rooms <- data.frame(RoomName, Capacity, VideoCap,stringsAsFactors = FALSE)

下面的函数应该可以满足您的需求：

Smash <- function(DF1, DF2){
  nm <- dim(DF1)
  pq <- dim(DF2)    
  maxrow <- nm[[1]] * pq[[1]]
  maxcol <- nm[[2]] + pq[[2]]
  MAT <- matrix('A', nrow = maxrow, ncol = maxcol)
  currow <- 1
    for (i1 in seq_len(nm[[1]])) {
      for (i2 in seq_len(pq[[1]])) {
        curcol <- 1
        for (j in seq_len(nm[[2]])) {
          MAT[currow, curcol] <- DF1[i1, j]
          curcol <- curcol + 1
        }
        for (j in seq_len(pq[[2]])) {
          MAT[currow, curcol] <- DF2[i2, j]
          curcol <- curcol + 1
        }
        currow <- currow + 1
      }
    }
  DF <- data.frame(MAT)
  names(DF) <- c(names(DF1), names(DF2))
  return(DF)
}

粉碎（房间，时间）returns：

> Smash(Rooms, Times)
   RoomName Capacity VideoCap                  ST                  ET
1     0M02A       16        1 2014-12-22 07:00:00 2014-12-22 07:30:00
2     0M02A       16        1 2014-12-22 07:30:00 2014-12-22 08:00:00
3     0M02A       16        1 2014-12-22 08:00:00 2014-12-22 08:30:00
4     0M02A       16        1 2014-12-22 08:30:00 2014-12-22 09:00:00
5     0M02A       16        1 2014-12-22 09:00:00 2014-12-22 09:30:00
6     0M03A        8        0 2014-12-22 07:00:00 2014-12-22 07:30:00
7     0M03A        8        0 2014-12-22 07:30:00 2014-12-22 08:00:00
8     0M03A        8        0 2014-12-22 08:00:00 2014-12-22 08:30:00
9     0M03A        8        0 2014-12-22 08:30:00 2014-12-22 09:00:00
10    0M03A        8        0 2014-12-22 09:00:00 2014-12-22 09:30:00
11    0M03B       12        1 2014-12-22 07:00:00 2014-12-22 07:30:00
12    0M03B       12        1 2014-12-22 07:30:00 2014-12-22 08:00:00
13    0M03B       12        1 2014-12-22 08:00:00 2014-12-22 08:30:00
14    0M03B       12        1 2014-12-22 08:30:00 2014-12-22 09:00:00
15    0M03B       12        1 2014-12-22 09:00:00 2014-12-22 09:30:00

嵌套循环输出到 data.frame

Nested loop output to a data.frame

r

loops

nested-loops