在R中按索引组合行 [英] Combining rows by index in R

问题描述

我知道已经回答了一个类似的问题，但它对我在下面提供的数据集上不起作用.上面的数据帧是我使用扩展函数的结果.我仍然不确定如何整合它.

I am aware there is a similar question that has been answered, but it does not work for me on the dataset I have provided below. The above dataframe is the result of me using the spread function. I am still not sure how to consolidate it.

我意识到我之前在数据上使用的 group_by 函数阻止了扩展函数以我最初希望的方式工作.使用 ungroup 后，我可以直接从原始数据集(下图未显示)转到下图中的第二个数据框.

I realized that the group_by function, which I had previously used on the data, is what was preventing the spread function from working in the way I wanted it to work originally. After using ungroup, I was able to go straight from the original dataset (not pictured below) to the 2nd dataframe pictured below.

我有一个如下所示的数据框.我正在尝试使每个 ID 号只有 1 行.

I have a dataframe that looks like the following. I am trying to make it so that there is only 1 row for each id number.

id  init_cont  family  1  2  3
1   I          C       1  NA NA
1   I          C       NA 4  NA
1   I          C       NA NA 3
2   I          D       2  NA NA
2   I          D       NA 1  NA
2   I          D       NA NA 4
3   K          C       3  NA NA
3   K          C       NA 4  NA
3   K          C       NA NA 1

我希望生成的数据框看起来像这样.

I would like the resulting dataframe to look like this.

id  init_cont  family  1  2  3
1   I          C       1  4  3
2   I          D       2  1  4
3   K          C       3  4  1

推荐答案

我们可以group_by 'd', 'init_cont', 'family' 然后做一个summarise_all 删除列 1:3

We cangroup_by the 'd', 'init_cont', 'family' and then do a summarise_all to remove all the NA elements in the columns 1:3

library(dplyr)
df1 %>%
   group_by_at(names(.)[1:3]) %>%
   summarise_all(na.omit)
   #Or
   #summarise_all(funs(.[!is.na(.)]))
# A tibble: 3 x 6
# Groups: d, init_cont [?]
#      d init_cont family   `1`   `2`   `3`
#   <int> <chr>     <chr>  <int> <int> <int>
#1     1 I         C          1     4     3
#2     2 I         D          2     1     4
#3     3 K         C          3     4     1

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