如何通过R中的算术条件为组生成随机值

Question

我有这种结构的数据集

mydata=structure(list(supps = c("KR", "KR", "KR", "KR", "KR", "KR", 
"KR", "KR", "KR", "KR", "aeroclub", "aeroclub", "aeroclub", "aeroclub", 
"aeroclub", "aeroclub", "aeroclub", "aeroclub", "aeroclub", "aeroclub"
), date = c("01.05.2021", "01.06.2021", "02.05.2021", "02.06.2021", 
"03.05.2021", "03.06.2021", "04.05.2021", "04.06.2021", "05.05.2021", 
"05.06.2021", "01.05.2021", "01.06.2021", "02.05.2021", "02.06.2021", 
"03.05.2021", "03.06.2021", "04.05.2021", "04.06.2021", "05.05.2021", 
"05.06.2021"), turnover = c(0, 0, 32159.00888, 25220.0027, 0, 
0, 245312.682, 189901.1224, 0, 0, 1531959.833, 1591612, 1834696.667, 
1885169, 1871615.167, 1823398, 4891342, 5253701.167, 0, 0), fee = c(0, 
0, 651, 37, 0, 0, 2341, 7548, 0, 0, 40519.5, 30415, 34767.66667, 
39289, 39175.66667, 45798, 94819.5, 116803.1667, 0, 0), comiss = c(0, 
0, 764.81, 537.67, 0, 0, 8578.25, 6198.115, 0, 0, -2023.41, -1941.67, 
-550.82, 1323.23, -1029.47, -638.47, -1034.58, -1332.95, 0, 0
), intencive = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 26.4, 1945.8, 
2199.48, 3740.76, 6499.2, 32188.68, 42337.44, 0, 0)), class = "data.frame", row.names = c(NA, 
-20L))

我需要通过支持列（KR 和 aeroclub）为每组提供 vriables 营业额费用 comissin injective 计算下一个条件的价值。例如，我们采用 KR 和营业额变量。最后 2 个值属于日期 03.06.2021-04.06.2021。如果最近的值大于前一个值，则计算值的总和 189901 0=189901。然后，对于日期 05.06.2021-08.06.2021（4 天）的每个变量生成随机值。这以随机顺序计算了189901总和（2%-10%）。更清楚 对于考试输出（对于营业额变量）

05.06.2021  189901+2%=193699,02
06.06.2021 189901+10%=208891,1
07.06.2021  189901+6%=208891,1
08.06.2021 189901+7%=203194

但有时最后一个值可能是负值。例如组=空中俱乐部。变量comiss，最后2个值03.06.2021-04.06.202104.06.22021值-1332，但在03.06.22022值-632，因此在04.06.202值小于03.06.221值。我们将这些值-1332-632=-1954相加，但我们不加和，我们以随机顺序对1954-（2%-10%）进行子跟踪。因此，对于这组comiss期望的输出

05.06.2021  -1954-2%=-1914,92
06.06.2021 -1954-7%=-1817,22
07.06.2021  -1954-6%=-1836,76
08.06.2021 -1954-8%=-1797,68

我怎样才能改正呢？

Answer 1

下面的回答假设了一些问题中不完全清楚的事情:

1. 计算从第3列开始到最后一列
2. 当有0时，保持为0。不添加随机%。如果你愿意的话，你可以改变
3. 很少有两个连续值具有不同符号的情况。对于这些情况，在问题之后应用最新值的规则

#storing the unique category of supps
col_supps <- unique(mydata$supps)
#storing the columns for which the calculations will be done
col_names <- colnames(mydata)[3:ncol(mydata)]

#the data frame which will contain the output
output_df <- data.frame()
#Iterating over different supps values

for (x in col_supps) {
#storing one type of supps in a temporary data frame
  mydata %>%
    filter(supps %in% x)-> temp
  temp1<- temp

#temp will act as a reference frame, in temp1 values will be updated
  
#Now, iterating over columns which we need
  
  for (y in col_names) {
    i<- 1
#with while loop, we will iterate over each elememnt of the column and save the result in temp1
    while (i<=(nrow(temp)-1)) {
      if(temp[i+1,y]>0 & temp[i+1,y]>=temp[i,y]){
        temp1[i+1,y] <- (temp[i,y]+temp[i+1,y]) * (runif(1,1.02,1.1))
      }else if(temp[i+1,y]<0 & temp[i+1,y]<=temp[i,y]){
        temp1[i+1,y] <- (temp[i,y]+temp[i+1,y]) * (runif(1,1.02,1.1))
      }else if(temp[i+1,y]>0 & temp[i+1,y]<temp[i,y]){
        temp1[i+1,y] <- (temp[i+1,y]) * (runif(1,1.02,1.1))
      }else if(temp[i+1,y]<0 & temp[i+1,y]>temp[i,y]){
        temp1[i+1,y] <- (temp[i+1,y]) * (runif(1,1.02,1.1))
      }else if(temp[i+1,y]==0){
        temp[i+1,y] <- 0
      }
      i <- i+1
    }
  }
#saving the output in the output data frame before repeating the process for another type of supps
  output_df %>%
    bind_rows(temp1) -> output_df
  
}

现在< code>output_df将得到您想要的最终输出。如果希望随机值具有再现性，可以在< code>while循环下< code>set.seed()。如果这不是我们想要的，那么你可以继续下去。