SPC -R中按组划分的控制图

Question

我希望为此数据中的每个名称创建一个统计过程控制图，并提取每个名称无法控制的行。

以下是数据文件：

DATE <- as.Date(c('2016-06-18', '2016-06-19', '2016-06-20', 
              '2016-06-21', '2016-06-22', '2016-06-23', 
              '2016-06-24', '2016-06-25', '2016-06-26', 
              '2016-06-27', '2016-06-28', '2016-06-29', 
              '2016-06-30', '2016-06-18', '2016-06-19', 
              '2016-06-20', '2016-06-21', '2016-06-22', 
              '2016-06-23', '2016-06-24', '2016-06-25', 
              '2016-06-26', '2016-06-27', '2016-06-28', 
              '2016-06-29', '2016-06-30', '2016-06-18',
              '2016-06-19', '2016-06-20', '2016-06-21',
              '2016-06-22', '2016-06-23', '2016-06-24',
              '2016-06-25', '2016-06-26', '2016-06-27',
              '2016-06-28', '2016-06-29', '2016-06-30'))

Name <- c('A', 'A', 'A', 'A', 'A', 'A','A', 'A', 'A', 'A', 'A', 'A', 'A',
          'B', 'B', 'B', 'B', 'B', 'B','B', 'B', 'B', 'B', 'B', 'B', 'B',
          'C', 'C', 'C', 'C', 'C', 'C','C', 'C', 'C', 'C', 'C', 'C', 'C')

Revenue <- c(0.08, 0.03, 0.09, 2, 0.09, 0.29, 0.56, 0.23, 0.12, 0.76, 0.23, 0.45,0.32,
             0.10, 0.14, 0.80, 0.3, 0.12, 0.75, 0.20, 0.09, 0.22, 0.11, 4, 0.30, 0.45,
             0.19, 0.23, 0.56, 0.77, 0.9, 9, 0.38, 0.11, 0.98, 0.87, 0.09, 0.20, 0.65)
df<-data.frame(DATE, Name, Revenue)

dput(df)
structure(list(DATE = structure(c(16970, 16971, 16972, 16973, 
16974, 16975, 16976, 16977, 16978, 16979, 16980, 16981, 16982, 
16970, 16971, 16972, 16973, 16974, 16975, 16976, 16977, 16978, 
16979, 16980, 16981, 16982, 16970, 16971, 16972, 16973, 16974, 
16975, 16976, 16977, 16978, 16979, 16980, 16981, 16982), class = "Date"), 
Name = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("A", 
"B", "C"), class = "factor"), Revenue = c(0.08, 0.03, 0.09, 
2, 0.09, 0.29, 0.56, 0.23, 0.12, 0.76, 0.23, 0.45, 0.32, 
0.1, 0.14, 0.8, 0.3, 0.12, 0.75, 0.2, 0.09, 0.22, 0.11, 4, 
0.3, 0.45, 0.19, 0.23, 0.56, 0.77, 0.9, 9, 0.38, 0.11, 0.98, 
0.87, 0.09, 0.2, 0.65)), .Names = c("DATE", "Name", "Revenue"), 
row.names = c(NA, -39L), class = "data.frame")

df

> df
         DATE Name Revenue
1  2016-06-18    A    0.08
2  2016-06-19    A    0.03
3  2016-06-20    A    0.09
4  2016-06-21    A    2.00
5  2016-06-22    A    0.09
6  2016-06-23    A    0.29
7  2016-06-24    A    0.56
8  2016-06-25    A    0.23
9  2016-06-26    A    0.12
10 2016-06-27    A    0.76
11 2016-06-28    A    0.23
12 2016-06-29    A    0.45
13 2016-06-30    A    0.32
14 2016-06-18    B    0.10
15 2016-06-19    B    0.14
16 2016-06-20    B    0.80
17 2016-06-21    B    0.30
18 2016-06-22    B    0.12
19 2016-06-23    B    0.75
20 2016-06-24    B    0.20
21 2016-06-25    B    0.09
22 2016-06-26    B    0.22
23 2016-06-27    B    0.11
24 2016-06-28    B    4.00
25 2016-06-29    B    0.30
26 2016-06-30    B    0.45
27 2016-06-18    C    0.19
28 2016-06-19    C    0.23
29 2016-06-20    C    0.56
30 2016-06-21    C    0.77
31 2016-06-22    C    0.90
32 2016-06-23    C    9.00
33 2016-06-24    C    0.38
34 2016-06-25    C    0.11
35 2016-06-26    C    0.98
36 2016-06-27    C    0.87
37 2016-06-28    C    0.09
38 2016-06-29    C    0.20
39 2016-06-30    C    0.65

我想要编写一个脚本，它将使用每个名称的qcc包创建一个控制图，然后为每个名称的控制图表指定超出限制的行。

所以我知道如何为每个名字分别制作一个正常的个人控制图，就是这样。名称："A“，例如：

library(dplyr)
library(qcc)
target <- c("A")
testing<-filter(df, Name %in% target)
library(qcc)
my.xmr.x <- qcc(testing$Revenue, type = "xbar.one", plot=TRUE)
beyond.limits(my.xmr.x)

结果：

​

​

结果是一个数据点超出了名称A的限制：

6

我的目标是编写一个脚本，它将提取所有名称的行(而不仅仅是像6这样的行号)。

下面是我想要的输出结果，最后是这样的：

Out_of_Control_Rows_By_Name
         DATE     Name Revenue 
   6  2016-06-21    A    2.00
   11 2016-06-28    B    4.00
   6  2016-06-23    C    9.00

任何帮助都会很好，谢谢！

Answer 1

require(pacman) # you don't have to use this; it's my package manager
p_load(dplyr,qcc)

tmp <- df[0,]
for(i in unique(df$Name)){
  testing<-filter(df, Name == i)
  my.xmr.x <- qcc(testing$Revenue, type = "xbar.one", plot=TRUE)
  beyond.limits(my.xmr.x)
  df2 <- df[df$Name == i,]
  tmp <- rbind(tmp,df2[beyond.limits(my.xmr.x),])
}

DATE Name Revenue 4 2016-06-21 A 2 24 2016-06-28 B 4 32 2016-06-23 C 9