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在R中的数据帧上使用嵌套的if-else

[英]Using nested for-if-else on a data frame in R

I am trying to use an if-else loop nested in a for loop to go through a data frame and output a new data frame based on conditions from the first df. 我正在尝试使用嵌套在for循环中的if-else循环来遍历数据帧并根据来自第一个df的条件输出新的数据帧。

In this data frame I would like to compare each row N with row N+1, 在此数据帧中,我想将N行与N + 1行进行比较,

if column elements match in column 1 and 2 如果列元素在列1和2中匹配

and the difference between column values in columns 3 and 4 for row N and row N+1 are less than or equal to 1 并且第N行和第N + 1行的第3列和第4列的列值之差小于或等于1

then I would like to write a new row in the N+1 row spot 那么我想在N + 1行位置写一个新行

that has the same elements for col 1 and 2 as those in row N+1 第1行和第2行具有与N + 1行相同的元素

and the minimum value of column 3 when comparing N and N+1 for col 3 比较第3列的N和N + 1时的第3列的最小值

and the maximum value of column 4 for comparing N and N+1 for col 4 和第4列的最大值,用于比较col 4的N和N + 1

Example: 例:

aaa <- c(rep("cat",4), "dog", "dog")
bbb <- c("fit", rep("fat",2), rep("fat", 3))
ccc <- c(6,5,6,9,9,9)
ddd <- c(11,10,10,22,23,24)
df <- data.frame(aaa,bbb,ccc,ddd)

Go from this: 从此:

 aaa bbb ccc ddd
 cat fit   6  11
 cat fat   5  10
 cat fat   6  10
 cat fat   9  22
 dog fat   9  23
 dog fat   9  24

To the desired output: 到所需的输出:

 aaa bbb ccc ddd
 cat fit   6  11
 cat fat   5  10
 cat fat   9  22
 dog fat   9  24

My attempt is this: 我的尝试是这样的:

result <- data.frame()
for (i in c(1:as.numeric(nrow(df))-1)){      
  if(df[i,1] == df[i+1,1]
     &
     df[i,2] == df[i+1,2]
     &
     abs(df[i,3]-df[i+1,3]) <=1
     &
     abs(df[i,4]-df[i+1,4]) <=1)       
   {
    result[i+1,] <- c(df[i,1],df[i,2],min(df[i,3],df[i+1,3]),max(df[i,4],df[i+1,4]))
    result[i,] <- c(NA,NA,NA,NA)
    } else {
    result[i,] <- df[i,]
    }
}
result

I figured it out. 我想到了。 Posting for closure: 发布关闭:

result <- df
for (i in c(1:as.numeric(nrow(df)-1))){
  if(df[i,1] == df[i+1,1] &
     df[i,2] == df[i+1,2] &
     abs(df[i,3]-df[i+1,3])<=1 &
     abs(df[i,4]-df[i+1,4])<=1) {
    result[i+1,3] <- min(df[i,3],df[i+1,3])
    result[i+1,4] <- max(df[i,4],df[i+1,4])
    result[i,] <- c(NA,NA,NA,NA)
    } 
}
result <- na.omit(result)
result

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