r - 子组的新列和另一列中的百分比范围

Question

我有一个样本 df，如下所示:

df_test<- data.frame("Group.Name"=c("Group1","Group2","Group1","Group2","Group2","Group2","Group1"),
                "Sub_group_name"=c("A","A","B","C","D","E","C"),
                "Total%"=c(35,26,10,9,5,11,13))

原来的df比较大，关于这个df需要记住的几点:

• 只有“Group1”和“Group2”两个组
• 一个组下有多个子组，上面的df显示了部分子组
• 组 + 子组的总百分比加起来为 100%。在上面不是，因为它只是一个示例。所以，对于 Group1所有子组，如 A, B, C等等将为“Group2”添加多达 100 等。 Group1 和 Group2 的子组大致相同

提问:

我需要创建一个名为 Category 的列它可以在 Total% 范围内工作在 Group.Name 上等级。创建新列的条件是:

• 对于每个 Group.Name无论在哪里Total%是最高的，类别列是Sub_group_name名字是。

• 对于每个 Group.Name和 Total%在 10-30 之间，类别列为“New_Group1”。

• 对于每个 Group.Name和 Total%小于 10，类别列为“New_Group2”。

预期输出:

df_output<- data.frame("Group.Name"=c("Group1","Group2","Group1","Group2","Group2","Group2","Group1"),
                     "Sub_group_name"=c("A","A","B","C","D","E","C"),
                     "Total%"=c(35,26,10,9,5,11,13),
                     "category"=c("A","A","New_Group1","New_Group1","New_Group2","New_Group1","New_Group1"))

Answer 1

我们可以使用 cut 来创建带有相应 breaks 的 labels，然后替换“Total”。这是每个 'Group.Name' 中最高的，具有相应的 'Sub_group_name'

library(dplyr)
df_test %>% 
  group_by(Group.Name) %>%
  mutate(category = as.character(cut(`Total%`, breaks = c(-Inf,10, 30, Inf), 
          labels = c("New_Group2", "New_Group1", "Other"), right = FALSE)), 
         category = case_when(`Total%` == max(`Total%`) ~ 
                          Sub_group_name,
                                   TRUE ~ category))
# A tibble: 7 x 4
# Groups:   Group.Name [2]
#  Group.Name Sub_group_name `Total%` category  
#  <chr>      <chr>             <dbl> <chr>     
#1 Group1     A                    35 A         
#2 Group2     A                    26 A         
#3 Group1     B                    10 New_Group1
#4 Group2     C                     9 New_Group2
#5 Group2     D                     5 New_Group2
#6 Group2     E                    11 New_Group1
#7 Group1     C                    13 New_Group1

数据

df_test<- data.frame("Group.Name"=c("Group1","Group2","Group1","Group2","Group2",
        "Group2","Group1"),
             "Sub_group_name"=c("A","A","B","C","D","E","C"),
          "Total%"=c(35,26,10,9,5,11,13), stringsAsFactors = FALSE, 
              check.names = FALSE)