如何使用 Tidyverse 将数据框连接到另一个数据框而不更改值
我正在处理多个 data.frames，我必须将它们相互连接起来，这正是我对 tidyverse 的 来说明我有以下数据集full_join 函数的期望
name<-c("AAA","AAA","AAA")
value<-c(1:3)
tag<-c(0,0,0)
part_a<-data.frame(name,value,tag)
name<-c("AAA","AAA","AAA")
value<-c(1:3)
key<-c(1,1,1)
part_b<-data.frame(name,value,key)
我想要的输出将是这样的：
| name | value | tag | key |
|---|---|---|---|
| AAA | 1 | 0 | NA |
| AAA | 2 | 0 | NA |
| AAA | 3 | 0 | NA |
| AAA | 1 | NA | 1 |
| AAA | 2 | NA | 1 |
| AAA | 3 | NA | 1 |
但我得到了这个：
> full_join(part_a,part_b)
Joining, by = c("name", "value")
name value tag key
1 AAA 1 0 1
2 AAA 2 0 1
3 AAA 3 0 1
这让我很困惑，因为我认为这个函数试图找到共同的值，然后聚合其余的数据，但我真正想要的只是将所有 dataframes 彼此重叠，包括它们没有共同的列，我知道我不能使用 rbind ，因为这个函数要求 dataframes 具有相同的列名，我会这样谢谢你们可以帮我吗！
I am working a multiple data.frames that I have to join on top of each other, which is kind of what I would expect from the function full_join of tidyverse to illustrate I have the following datasets
name<-c("AAA","AAA","AAA")
value<-c(1:3)
tag<-c(0,0,0)
part_a<-data.frame(name,value,tag)
name<-c("AAA","AAA","AAA")
value<-c(1:3)
key<-c(1,1,1)
part_b<-data.frame(name,value,key)
My desired output would be something like this:
| name | value | tag | key |
|---|---|---|---|
| AAA | 1 | 0 | NA |
| AAA | 2 | 0 | NA |
| AAA | 3 | 0 | NA |
| AAA | 1 | NA | 1 |
| AAA | 2 | NA | 1 |
| AAA | 3 | NA | 1 |
but instead I am getting this:
> full_join(part_a,part_b)
Joining, by = c("name", "value")
name value tag key
1 AAA 1 0 1
2 AAA 2 0 1
3 AAA 3 0 1
Which is very confusing to me as I think this function is trying to find common values and then aggreate the rest of the data but what I really want is just to put all dataframes on top of each other including the columns that they do not have in common, I know I cannot use rbind since this function requires dataframes to have the same column names, I would be so thankfull if you guys can help me out!
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full_join()正在合并您的数据框。由于您没有指定用作标识符的列，因此它使用公共字段（即name和value）。要简单地组合数据帧，您可以使用dplyr的bind_rows()：result <-bind_rows(part_a,part_b)请注意，还有
bind_cols()用于将多个数据帧中的变量（即列）合并为一个数据帧。full_join()is merging your data frames. Since you didn't specify the columns to use as identifiers, it's using the common fields (i.e.,nameandvalue). To simply combine data frames you can usedplyr'sbind_rows():result <- bind_rows(part_a, part_b)Note that there's also a
bind_cols()for combining variables (i.e., columns) from multiple data frames into a single one.