滞后没有看到mutate对上一行的影响

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问题描述

我似乎偶然发现了我无法解释的 mutate / lag / ifelse 行为。我有以下（简化的）数据框：

  test<-data.frame（type = c（ START， END， START， START， START， START， END），
个字符串AsFactors = FALSE）
 
>测试
 
类型
 1 START 
 2 END 
 3 START 
 4 START 
 5 START 
 6 START 
 7 START 
 8 END

我想修改列类型，以便具有交替的 START 和 END 对的序列（请注意， test 数据框只能使用 START 的序列， END 永远不会重复）：

 >所需的
 
类型
 1 START 
 2 END 
 3 START 
 4 END 
 5 START 
 6 END 
 7 START 
 8 END

我想我可以用以下代码实现目标：

  test％>％
 mutate（type = ifelse（type == START& 
 dplyr :: lag（type，n = 1，default = END）== START&
 dplyr :: lead（type，n = 1，default = END）== START ， END，类型））

代码应检测到所在的行START 之前是 START ，然后是 START ，在这种情况下， type 的值更改为 END 。进行此更改之后，以下 START （ test 的第5行）不应该匹配，因为它以前的 type 的值现在为 END 。不幸的是，该命令的输出如下：

 类型
 1 START 
 2 END 
 3 START 
 4 END 
 5 END 
 6 END 
 7 START 
 8 END

就像 lag 看到的值不受变异影响。这是应该如何工作的吗？有没有一种方法可以使 lag 看到 mutate 在上一行中的效果？

版本：R版本3.2.3（2015-12-10），dplyr_0.4.3

更新：原因下面的Paul Rougieux解释了为什么上面的代码不起作用的原因：超前和滞后是固定的，并且不考虑进一步的修改。因此，我猜正确的答案是使用dplyr无法直接完成。

解决方案

在 mutate（）中分别定义滞后和前导变量您对 ifelse（type == START& lag == START& Lead == START， END，键入）的呼叫是无法正常工作：

  test<-data.frame（type = c（ START， END， START， START， START， START， END），stringsAsFactors = FALSE）
测试％&％;％
 mutate（lag = dplyr :: lag（type，n = 1，default = END），
 lead = dplyr :: lead（type，n = 1，default = END），
 type2 = ifelse（type == START& lag == START& Lead == START，
 END，类型））
 
＃类型滞后线索type2 
＃1 START END END START 
＃2结束开始开始结束
＃3开始结束开始开始
＃4开始开始开始结束
＃5开始开始开始结束
＃6开始开始结束开始
＃7 END START END END

dplyr :: mutate（）整体修改向量。超前和滞后是固定的，不考虑对 type 向量的进一步修改。在这种情况下，您需要一个`Reduce（）̀函数。检查帮助（减少）。

I seem to have stumbled upon a mutate/lag/ifelse behaviour that I cannot explain. I have the following (simplified) dataframe:

test <- data.frame(type = c("START", "END", "START", "START", "START", "START", "END"),
                   stringsAsFactors = FALSE)

> test

  type
1 START
2   END
3 START
4 START
5 START
6 START
7 START
8   END

I would like to modify the column type in order to have a sequence of alternating START and END pairs (note that in the test dataframe only sequences of START are possible, END is never repeated):

> desired

  type
1 START
2   END
3 START
4   END
5 START
6   END
7 START
8   END

I thought I could achieve my goal with the following code:

test %>%
 mutate(type = ifelse( type == "START" &
                       dplyr::lag(type, n=1, default="END") == "START" &
                       dplyr::lead(type, n=1, default="END") == "START", "END" , type))

The code should detect rows in which START is preceded by a START and followed by a START, in which case the type value is changed to END. After this change, the following START (row number 5 of test) should not be matched, since its previous type value is now END. Unfortunately, the output of the command is the following:

   type
1 START
2   END
3 START
4   END
5   END
6   END
7 START
8   END

It's like the value seen by lag is not affected by mutate. Is this how it is supposed to work? Is there a way to code it in a way that lag sees the effects of mutate on the previous row?

Versions: R version 3.2.3 (2015-12-10), dplyr_0.4.3

UPDATE: The reason why the above code doesn't work is explained by Paul Rougieux below: lead and lag are fixed and do not take into account further modification. So I guess the correct answer is "it cannot be done straightforwardly using dplyr".

解决方案

Defining lag and lead variables separately in mutate() will show you that your call to ifelse(type == "START" & lag == "START" & lead == "START", "END" , type) is not going to work:

test <- data.frame(type = c("START", "END", "START", "START", "START", "START", "END"), stringsAsFactors = FALSE)
test %>%
    mutate(lag = dplyr::lag(type, n=1, default="END"),
           lead = dplyr::lead(type, n=1, default="END"),
           type2 = ifelse(type == "START" & lag == "START" & lead == "START",
                          "END" , type))

#   type   lag  lead type2
#1 START   END   END START
#2   END START START   END
#3 START   END START START
#4 START START START   END
#5 START START START   END
#6 START START   END START
#7   END START   END   END

dplyr::mutate() modifies the vector as a whole. Lead and lag are fixed and do not take into account further modification to the type vector. What you want is a `Reduce()̀ function in this case. Check help(Reduce).

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滞后没有看到mutate对上一行的影响

问题描述