在R中使用dplyr :: contains（）和dplyr :: select（）的正负子集 [英] Positive and negative subsetting using dplyr::contains() and dplyr::select() in R

问题描述

我正在尝试使用 dplyr :: select（）和dplyr :: contains（）`的组合来实现正子集化，目标是子集化

I'm trying to achieve positive subsetting specifically using a combination of dplyr::select() and dplyr::contains()`, with the goal being to subset by multiple string matches.

最小工作示例：以 df1 开始并进行负子集设置时，我生成 df2 如预期。相反，当尝试对 df1 进行正子集设置时，当我期望有某些结果时，会生成 df3 （无列）例如 df4 。谢谢你的帮助。

Minimal working example: when starting off with df1 and doing negative subsetting, I generate df2 as expected. In contrast, when attempting positive subsetting of df1, I generate df3 (no columns) when I'd have expected something like df4. Thanks for any help.

df1 <- data.frame("ppt_paint"=c(45,98,23),"het_heating"=c(1,1,2) ,"orm_wood"=c("QQ","OA","BB"), "hours"=c(4,6,4), "distance"=c(23,65,21))
df2 <- df1 %>% select(-contains("ppt_")) %>% select(-contains("het_")) %>% select(-contains("orm_"))
df3 <- df1 %>% select(contains("ppt_")) %>% select(contains("het_")) %>% select(contains("orm_")) 
df4 <- data.frame("ppt_paint"=c(45,98,23),"het_heating"=c(1,1,2) ,"orm_wood"=c("QQ","OA","BB"))

推荐答案

思考（并查看生成的 data.frame ）在以下情况下会发生什么： df1％>％select（contains（ ppt _））。如所要求的，它仅保留 only 列，其中包含 ppt _ 。进一步的表达式无法按您期望的那样工作，因为其他列（无论您用什么填充 select ）都不再存在。

Think (and have a look to the resulting data.frame) to what happens after: df1 %>% select(contains("ppt_")). As asked, it only retains the only column that contains "ppt_". Further expressions cannot work as you expect since other columns, no matter what you're feeding select with, are "no longer" there.

您可以保留相同的想法，但在同一选择中的 combine 中使用三个键：

You can keep the same idea but combine in the same select you three keys:

df1 %>% select(matches("ppt_"), matches("het_"), matches("orm_"))
  ppt_paint het_heating orm_wood
1        45           1       QQ
2        98           1       OA
3        23           2       BB

或者，您可以使用匹配项来实现，该匹配项接受正则表达式：

Alternatively, you can do it with matches, that accepts regular expressions:

df1 %>% select(matches(c("ppt_|het_|orm_")))
  ppt_paint het_heating orm_wood
1        45           1       QQ
2        98           1       OA
3        23           2       BB

而且，您也可以使用它来缩短负数 索引：

And by the way you can also use it to shorten your "negative" indexing:

df1 %>% select(-matches("ppt_|het_|orm_"))
  hours distance
1     4       23
2     6       65
3     4       21

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