按某些列创建具有数据表顺序的新列不起作用[重复]

Question

我有以下data.table：

library (data.table)
dt <- structure(list(variable = c("var1", "var1", 
                            "var2", "var2", "var3", "var3", 
                            "var4", "var4", "var5", "var5"
), src = c("A", "B", 
           "A", "B", 
           "A", "B", 
           "A", "B", 
           "A", "B"
), effect = c(0.00479503189634099, 0.00520945223353099, 0.0414826536175954, 
              0.0534395645078372, 0.00321202935447758, 0.00426201973099257, 
              0.0207942299790097, 0.0268992334286609, 0.304833654398739, 0.291310303107859
)), .Names = c("variable", "src", "effect" ), class = c("data.table", "data.frame"), row.names = c(NA, -10L))

并且我想要src列的效果排名。所以对于src 的variable var5 应该有rank 等于1（对于src 的var5 有最高的effect）。所以我跑了

dt[, rank:=order(effect,  decreasing = T), by=c('src')]

但我明白了

> dt
    variable src       effect rank
 1:     var1   A 0.0047950319    5
 2:     var1   B 0.0052094522    5
 3:     var2   A 0.0414826536    2
 4:     var2   B 0.0534395645    2
 5:     var3   A 0.0032120294    4
 6:     var3   B 0.0042620197    4
 7:     var4   A 0.0207942300    1
 8:     var4   B 0.0268992334    1
 9:     var5   A 0.3048336544    3
10:     var5   B 0.2913103031    3

任何想法为什么会发生这种情况？

Answer 1

另一个数据表

setorder(dt, src, -effect)[, rank := 1:.N, by = src][]

Answer 2

使用dplyr：

dt %>%
  group_by(src) %>%
  mutate(rank = dense_rank(desc(effect)))

# A tibble: 10 x 4
# Groups:   src [2]
   variable src    effect  rank
   <chr>    <chr>   <dbl> <int>
 1 var1     A     0.00480     4
 2 var1     B     0.00521     4
 3 var2     A     0.0415      2
 4 var2     B     0.0534      2
 5 var3     A     0.00321     5
 6 var3     B     0.00426     5
 7 var4     A     0.0208      3
 8 var4     B     0.0269      3
 9 var5     A     0.305       1
10 var5     B     0.291       1

或者data.table:

dt[, rank := rank(desc(effect)), by = list(src)]

    variable src      effect rank
 1:     var1   A 0.004795032    4
 2:     var1   B 0.005209452    4
 3:     var2   A 0.041482654    2
 4:     var2   B 0.053439565    2
 5:     var3   A 0.003212029    5
 6:     var3   B 0.004262020    5
 7:     var4   A 0.020794230    3
 8:     var4   B 0.026899233    3
 9:     var5   A 0.304833654    1
10:     var5   B 0.291310303    1