以编程方式对数据帧进行重新排序，而不是对其进行子集化

Question

我正在尝试将数据帧转换为特定格式，以便从R中导出数据并在AMPL中使用它。

我的初始数据帧如下

test <- structure(list(from = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), 
to = c(1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3), beta = c(0.0214674078064637, 
0.0205966237172006, 0.0197611613089226, 0.0214674078064637, 
0.0205966237172006, 0.0197611613089226, 0.0214674078064637, 
0.0205966237172006, 0.0197611613089226, 0.0214674078064637, 
0.0205966237172006, 0.0197611613089226), Time = c(0L, 0L, 
0L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L)), class = "data.frame", row.names = c(NA, 
-12L), .Names = c("from", "to", "beta", "Time"))

这是测试数据框架

   from to       beta Time
1     1  1 0.02146741    0
2     1  2 0.02059662    0
3     1  3 0.01976116    0
4     1  1 0.02146741    1
5     1  2 0.02059662    1
6     1  3 0.01976116    1
7     1  1 0.02146741    2
8     1  2 0.02059662    2
9     1  3 0.01976116    2
10    1  1 0.02146741    3
11    1  2 0.02059662    3
12    1  3 0.01976116    3

我想要的最终结果是这个：

        V T1          0 T2          1 T3          2 T4          3 line
1 [1,1,*]  0 0.02146741  1 0.02146741  2 0.02146741  3 0.02146741   \n
2 [1,2,*]  0 0.02059662  1 0.02059662  2 0.02059662  3 0.02059662   \n
3 [1,3,*]  0 0.01976116  1 0.01976116  2 0.01976116  3 0.01976116   \n

我目前的操作方式是：

Betas <- unite_(test, col = "V", sep = ",", from = c("from", "to"))
Betas <- spread(Betas, key = Time, value = beta)
Betas$V <- paste("[", Betas$V, ",*]", sep = "")
Betas$T1 <- 0
Betas$T2 <- 1
Betas$T3 <- 2
Betas$T4 <- 3
Betas <- Betas[,c(1,6,2,7,3,8,4,9,5)]
Betas$line <- "\n"

我喜欢我的前三行代码的过程

Betas <- unite_(test, col = "V", sep = ",", from = c("from", "to"))
Betas <- spread(Betas, key = Time, value = beta)
Betas$V <- paste("[", Betas$V, ",*]", sep = "")

但是我想替换下面的行，原因是时间列可以重复X次。现在时间总是从0到X，我如何以编程方式知道X的值呢？

Betas$T1 <- 0
Betas$T2 <- 1
Betas$T3 <- 2
Betas$T4 <- 3
Betas <- Betas[,c(1,6,2,7,3,8,4,9,5)]
Betas$line <- "\n"

Answer 1

Base R解决方案

temp = split(test, test$Time)
do.call(cbind, lapply(1:length(temp), function(i){
    if (i == 1){
        setNames(data.frame(paste(temp[[i]][["from"]], ",", temp[[i]][["to"]], ",*", sep = ""), temp[[i]]["Time"], temp[[i]]["beta"]), 
                 c("V", paste("T", i, sep = ""), i-1))
    } else if (i == length(temp)){
        setNames(data.frame(temp[[i]]["Time"], temp[[i]]["beta"], rep("\n", NROW(temp[[i]]))), 
                 c(paste("T", i, sep = ""), i-1, "line"))
    } else {
        setNames(data.frame(temp[[i]]["Time"], temp[[i]]["beta"]),
                 c(paste("T", i, sep = ""), i-1))
    }
}))
#      V T1          0 T2          1 T3          2 T4          3 line
#1 1,1,*  0 0.02146741  1 0.02146741  2 0.02146741  3 0.02146741   \n
#2 1,2,*  0 0.02059662  1 0.02059662  2 0.02059662  3 0.02059662   \n
#3 1,3,*  0 0.01976116  1 0.01976116  2 0.01976116  3 0.01976116   \n

Answer 2

这是我的看法：

library(dplyr)
NR <- 3
df <- as.data.frame(cbind(paste0("[1,", 1:NR  , ",*]"),
                matrix(test$beta,nrow=NR  ),
                matrix(test$Time,nrow=NR  ),
                rep("\n",NR  ))) %>%
      select(V1,V6,V2,V7,V3,V8,V4,V9,V5,V10)

newnames <- c("V","T1","0","T2","1","T3","2","T4","3","line")
colnames(df) <- newnames

Answer 3

tidyverse的解决方案。 Betas2是最终输出。

# Load package
library(tidyverse)

# Create example data frame
Betas <- unite_(test, col = "V", sep = ",", from = c("from", "to"))
Betas <- spread(Betas, key = Time, value = beta)
Betas$V <- paste("[", Betas$V, ",*]", sep = "")

# A function to split the data frame
split_df <- function(Begin, End, dt){
  dt2 <- dt %>% select(Begin, End)
  return(dt2)
}

# A function to Add Time and values
add_time <- function(dt) {
  # Extract column names and value
  Colname <- colnames(dt)
  Value <- as.numeric(Colname[2])
  Value2 <- Value + 1
  Value <- enquo(Value)
  Value2 <- enquo(Value2)
  Col <- paste0("T", quo_name(Value2))
  # Add column based on the Colname
  dt2 <- dt %>%
    mutate(!!Col := !!Value) %>%
    select(1, 3, 2)
  return(dt2)
}

# Apply functions
dt_list <- map2(1, 2:ncol(Betas), .f = split_df, dt = Betas)
dt_list2 <- map(dt_list, .f = add_time)

# Merge all data frames
Betas2 <- reduce(dt_list2, left_join, by = "V") %>%
  # Create the line column
  mutate(line = "\n")