R检查并计算向量中的字符串，group_by，考虑字符串的出现顺序

Question

数据采用以下格式，我必须 group_by 使用日期。为方便起见，我将其显示为数字。

Msg <- c("Errors","Errors", "Start","Stop","Start","Stop","Errors","Errors","Start","Stop",
         "Stop" ,"Start","Errors","Start","Stop","Start" ,"Stop" ,
         "Errors", "Start","Errors","Stop", "Start", "LostControl","LostControl", "Errors",
         "Failed", "Stop", "Start","Failed","Stop","Stop","Start","Stop","Start","Error","Start",
         "Failed", "Stop")
Date <- c(11,11,11,11,11,11,11,12,12,12,12,12,12,14,14,14,14, 19,19,19,19,
        20,20,20,20,20,20,21,21,21,21,22,22,22,22,22,22,22)
data<- data.frame(Msg,Date)

我需要统计每个 START-STOP 循环中 Failed 的次数，按日期汇总。
数据具有三种类型的消息。 Errors 和 Failed 是两种类型的失败消息，而 LostControl 不是失败。条件是 Failed 消息在该 START-STOP 周期中不应在 LostControl 消息之前。如果前面只有 Errors，则为 Failure。此外，如果仅发现“错误”消息，也不会被视为失败。

Edit: 在Msg向量中，一个START_STOP循环是从极端开始到极端停止当且仅当两个开始或找到停靠点。如果 START 后面没有 STOP，则会被忽略。

编辑一行添加为 - (Msg =Stop, Date=20)

Answer 1

我们可以修改我昨天在您中写的那个函数。

between_valid_anchors <- function(x, bgn = "Start", end = "Stop") {
  are_anchors <- x %in% c(bgn, end)
  xid <- seq_along(x)
  id <- xid[are_anchors]
  x <- x[are_anchors]
  start_pos <- id[which(x == bgn & c("", head(x, -1L)) %in% c("", end))]
  stop_pos <- id[which(x == end & c(tail(x, -1L), "") %in% c("", bgn))]
  if (length(start_pos) < 1L || length(stop_pos) < 1L)
    return(logical(length(xid)))
  xid %in% unlist(mapply(`:`, start_pos, stop_pos))
}

然后

library(dplyr)

data %>% 
  group_by(Date) %>% 
  filter(between_valid_anchors(Msg)) %>% 
  summarise(Msg = sum(Msg %in% c("Err", "Errors", "Failed")))

输出

`summarise()` ungrouping output (override with `.groups` argument)
# A tibble: 6 x 2
   Date   Msg
  <dbl> <int>
1    11     0
2    12     0
3    14     0
4    19     1
5    21     1
6    22     2

更新

您可以再添加一个过滤器以 select 只有感兴趣的消息（即开始、停止、失败、LostControl）。然后，只求和所有 Msg == "Failed" 但不求 lag(Msg) == "LostControl"

library(dplyr)

data %>% 
  group_by(Date) %>% 
  filter(between_valid_anchors(Msg)) %>% 
  filter(Msg %in% c("Start", "Stop", "Failed", "LostControl")) %>% 
  summarise(Msg = sum(Msg == "Failed" & lag(Msg, default = "") != "LostControl"))

输出

`summarise()` ungrouping output (override with `.groups` argument)
# A tibble: 7 x 2
   Date   Msg
  <dbl> <int>
1    11     0
2    12     0
3    14     0
4    19     0
5    20     0
6    21     1
7    22     1

R检查并计算向量中的字符串，group_by，考虑字符串的出现顺序

R check and count Strings in a vector, group_by, considering order of appearance of the strings

group-by

r

count

dataframe

summarize