创建"其他"字段

Question

现在,我有以下由original.df %.% group_by(Category) %.% tally() %.% arrange(desc(n)).创建的data.frame .

DF <- structure(list(Category = c("E", "K", "M", "L", "I", "A", 
"S", "G", "N", "Q"), n = c(163051, 127133, 106680, 64868, 49701, 
47387, 47096, 45601, 40056, 36882)), .Names = c("Category", 
"n"), row.names = c(NA, 10L), class = c("tbl_df", "tbl", "data.frame"
))

         Category      n
1               E 163051
2               K 127133
3               M 106680
4               L  64868
5               I  49701
6               A  47387
7               S  47096
8               G  45601
9               N  40056
10              Q  36882

我想从nie排名最低的类别中创建一个"其他"字段

        Category      n
1              E 163051
2              K 127133
3              M 106680
4              L  64868
5              I  49701
6          Other 217022

现在,我在做

rbind(filter(DF, rank(rev(n)) <= 5), 
  summarise(filter(DF, rank(rev(n)) > 5), Category = "Other", n = sum(n)))

它将不在前5名中的所有类别折叠为其他类别.

但我很好奇是否有更好的方式dplyr或其他现有的包."更好"我的意思是更简洁/可读.我也对使用更聪明或更灵活的方法进行选择的方法感兴趣Other.

Answer 1

这是另一种方法,假设每个类别(至少前5个)只出现一次:

df %.% 
  arrange(desc(n)) %.%       #you could skip this step since you arranged the input df already according to your question
  mutate(Category = ifelse(1:n() > 5, "Other", Category)) %.%
  group_by(Category) %.%
  summarize(n = sum(n))

#  Category      n
#1        E 163051
#2        I  49701
#3        K 127133
#4        L  64868
#5        M 106680
#6    Other 217022

编辑:

我只是注意到我的输出不再是减少顺序n.在再次运行代码之后,我发现订单一直保留到之后,group_by(Category)但是当我summarize之后运行时,订单消失了(或者更确切地说,它似乎是按顺序排序Category).这应该是那样的吗？

以下是三种方式:

m <- 5    #number of top results to show in final table (excl. "Other")
n <- m+1

#preserves the order (or better: reesatblishes it by index)
df <- arrange(df, desc(n)) %.%    #this could be skipped if data already ordered 
  mutate(idx = 1:n(), Category = ifelse(idx > m, "Other", Category)) %.%
  group_by(Category) %.%
  summarize(n = sum(n), idx = first(idx)) %.%
  arrange(idx) %.%
  select(-idx)

#doesnt preserve the order (same result as in first dplyr solution, ordered by Category)
df[order(df$n, decreasing=T),]     #this could be skipped if data already ordered 
df[n:nrow(df),1] <- "Other"
df <- aggregate(n ~ Category, data = df, FUN = "sum")

#preserves the order (without extra index)
df[order(df$n, decreasing=T),]     #this could be skipped if data already ordered 
df[n:nrow(df),1] <- "Other"
df[n,2] <- sum(df$n[df$Category == "Other"]) 
df <- df[1:n,]

Answer 2

不同的包/不同的语法版本:

library(data.table)

dt = as.data.table(DF)

dt[order(-n), # your data is already sorted, so this does nothing for it
   if (.BY[[1]]) .SD else list("Other", sum(n)),
   by = 1:nrow(dt) <= 5][, !"nrow", with = F]
#   Category      n
#1:        E 163051
#2:        K 127133
#3:        M 106680
#4:        L  64868
#5:        I  49701
#6:    Other 217022