R，根据单独列中的值删除前一行

Question

我是 R 的新手。我试图根据另一列设置的条件删除先前的行。
我找到了 dplyr 和 data.table 的解决方案，我相信它们与我正在寻找的很接近，因为它们正好相反。
样本数据:

Cust_ID | Date                 | Value
500219  | 2016-04-11 12:00:00  | 0
500219  | 2016-04-12 16:00:00  | A
500219  | 2016-04-14 11:00:00  | A
500219  | 2016-04-15 12:00:00  | B
500219  | 2016-05-23 09:00:00  | B
500219  | 2016-05-02 19:00:00  | C
500220  | 2016-04-11 12:00:00  | C
500220  | 2016-04-14 11:00:00  | C
500220  | 2016-04-15 12:00:00  | A
500220  | 2016-05-23 09:00:00  | A
500220  | 2016-05-02 19:00:00  | A

对于每个 Cust_ID，我只想保留 Value == "A"之后的行，包括该行。这应该导致以下数据框:

Cust_ID | Date                 | Value
500219  | 2016-04-12 16:00:00  | A
500219  | 2016-04-14 11:00:00  | A
500219  | 2016-04-15 12:00:00  | B
500219  | 2016-05-23 09:00:00  | B
500219  | 2016-05-02 19:00:00  | C
500220  | 2016-04-15 12:00:00  | A
500220  | 2016-05-23 09:00:00  | A
500220  | 2016-05-02 19:00:00  | A

这些是我已经找到的解决方案 ( R delete rows based on values in previous rows )

library(data.table)
setDT(df1)[df1[,  if(any(Value == "A")) .I[seq(max(which(Value == "A")))]
                                 else .I[1:.N] , by = Cust_ID]$V1]


library(dplyr)
df1 %>% 
     group_by(Cust_ID) %>% 
     slice(if(any(Value=="A")) seq(max(which(Value=="A"))) else row_number())

Answer 1

这是否有效:

> library(dplyr)
> df %>% group_by(Cust_ID) %>% filter(row_number() >= min(which(Value == 'A')))
# A tibble: 8 x 3
# Groups:   Cust_ID [2]
  Cust_ID Date                Value
    <dbl> <chr>               <chr>
1  500219 2016-04-12 16:00:00 A    
2  500219 2016-04-14 11:00:00 A    
3  500219 2016-04-15 12:00:00 B    
4  500219 2016-05-23 09:00:00 B    
5  500219 2016-05-02 19:00:00 C    
6  500220 2016-04-15 12:00:00 A    
7  500220 2016-05-23 09:00:00 A    
8  500220 2016-05-02 19:00:00 A    
>