Question

这可能是一个愚蠢的问题，但我似乎不明白为什么nrow和length向量的行为不同。

示例：

   #Create a dummy data frame
   dff = data.frame(X = c(35,18,17,35), Y =c(1,2,3,4))

   #Test whether 1:nrow(dff) and 1:length(dff[,1]) are identical

   identical(1:nrow(dff), 1:length(dff[,1]))
   #[1] TRUE

   #Run a nested for-loop 
    step1 = matrix(0, nrow=nrow(dff), ncol = nrow(dff)) #create a placeholder
    for (i in 1:nrow(dff)) {# for each row in the first column 
      for (j in 1:nrow(dff)) { # for each row in the second column 
    step1[i, j] <-  dff$Y[i] + dff$X[j] # add them in the placeholder
        }
      }

     #       [,1] [,2] [,3] [,4]
     # [1,]   36   19   18   36
     # [2,]   37   20   19   37
     # [3,]   38   21   20   38
     # [4,]   39   22   21   39

    # Now run the same example using 1:length(dff[,1])

    step1 = matrix(0, nrow=nrow(dff), ncol = nrow(dff)) #create a placeholder
    for (i in 1:length(dff[,1])) {# for each row in the first column 
      for (j in 1:length(dff[,2])) { # for each row in the second column 
    step1[i, j] <-  dff$Y[i] + dff$X[j] # add them in the placeholder
       }
    }

   #       [,1] [,2] [,3] [,4]
   # [1,]    0    0    0    0
   # [2,]    0    0    0    0
   # [3,]    0    0    0    0
   # [4,]    0    0    0    0

有什么区别？为什么我得到两个不同的答案，请给出一个虚拟的解释。感谢

Answer 1

您的第二个for循环包含step1变量而不是step2：D

Answer 2

您的代码中存在拼写错误：

正如Patronus所说：

  step2 = matrix(0, nrow=nrow(dff), ncol = nrow(dff)) #create a placeholder
  for (i in 1:length(dff[,1])) {# for each row in the first column 
    for (j in 1:length(dff[,2])) { # for each row in the second column 
  step2[i, j] <-  dff$Y[i] + dff$X[j] # add them in the placeholder
       }
   }
  #       [,1] [,2] [,3] [,4]
  # [1,]   36   19   18   36
  # [2,]   37   20   19   37
  # [3,]   38   21   20   38
  # [4,]   39   22   21   39

for循环中nrow和length的区别？

2 个答案: