在“整洁"之后重新组织具有多种标头类型的数据帧R中的方法 [英] Reorganizing dataframe with multiple header types following "tidy" approach in R

问题描述

我有一个看起来像这样的数据框:

I have a dataframe that looks like somewhat like this:

Age  A1U_sweet  A2F_dip  A3U_bbq  C1U_sweet  C2F_dip  C3U_bbq  Comments
23   1          2        1        NA         NA       NA       Good
54   NA         NA       NA       4          1        2        ABCD
43   2          4        7        NA         NA       NA       HiHi

我正在尝试以如下所示的方式重新组织它，使其更加整洁".有没有一种方法可以让我做到这一点，它也以与下面其他变量所示相同的样式合并了 Age 和 Comments 列?您建议如何合并它们 - 下面显示了一个想法，但我愿意接受其他建议.我将如何修改以下代码以考虑多种不同样式的列名?

I am trying to reorganize it in way shown below to make it more "tidy". Is there a way for me to do this that also incorporates the Age and Comments columns in the same style as shown for the other variables below? How would you suggest incorporating them - one idea is shown below, but I am open to other suggestions. How would I modify the following code in order to account for multiple different styles of column name?

library(tidyr)

df <- data.frame(id = 1:nrow(df), df)
dfl <- gather(df, key = "key", value = "value", -id)
dfl <- separate(dfl, key, into = c("key", "kind", "type"), sep = c(1, 4))
df2 <- spread(dfl, key, value)
df2
##   id kind  type     A    C
## 1  1  Age   Age    23   23
## 2  1  1U_ sweet     1   NA
## 3  1  2F_   dip     2   NA
## 4  1  3U_   bbq     1   NA
## 5  1  Com   Com  Good Good
## 6  2  Age   Age    54   54
## 7  2  1U_ sweet    NA    4
## 8  2  2F_   dip    NA    1
## 9  2  3U_   bbq    NA    2
##10  2  Com   Com  ABCD ABCD
##11  3  Age   Age    43   43
##12  3  1U_ sweet     2   NA
##13  3  2F_   dip     4   NA
##14  3  3U_   bbq     7   NA
##15  3  Com   Com  HiHi HiHi

我将如何修改以下代码以将数据恢复到原来的状态?

And how would I modify the following code to return the data back to how it originally was?

df <- gather(df2, key = "key", value = "value", A, B, C)
df <- unite(df, "key", key, kind, type, sep = "")
df <- spread(df, key, value)

对于上下文，这个问题是由 Ista 在这个问题下的评论提示的:根据匹配的列标题名称开头组合 R 中的列

For context, this question was prompted by Ista's comment under this question: Combining columns in R based on matching beginnings of column title names

推荐答案

因为 Age 和 Comments 大概是在原始数据中的任何一行的级别上衡量的，带上他们去兜风:

Since Age and Comments are presumably measured at the level of whatever a row in your original data is, just bring them along for the ride:

df <- data.frame(id = 1:nrow(df), df)

dfl <- gather(df, key = "key", value = "value", -id, -Age, -Comments)
dfl <- separate(dfl, key, into = c("key", "kind", "type"), sep = c(1, 4))
df2 <- spread(dfl, key, value)
df2

df2 <- transform(df2, B = ifelse(is.na(A), C, A))
df2

df <- gather(df2, key = "key", value = "value", A, B, C)
df <- unite(df, "key", key, kind, type, sep = "")
df <- spread(df, key, value)
df

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