我想在数据框中添加一个计算列，在每个STEP_NAME系列（R1，R2 ...）上找到CpK，并将DATA列作为度量
Cpk的Calcul是：
m <- mean(table1$Data)
s <- sd(table1$Data)
Ts <- max(table1$HIGH_LIMIT)
Ti <- min(table1$LOW_LIMIT)
CpK <- min((m-Ti)/(3*s), (Ts-m)/(3*s))
我试过
library(dplyr)
table2 <- table1 %>%
group_by(STEP_NAME) %>%
summarise(m = mean(DATA), s = sd(DATA), Ts = max(High_Limit),
Ts = max(High_Limit), Ti = min(LOW_LIMIT)) %>%
mutate(CpK = min((m-Ti)/(3*s), (Ts-m)/(3*s)))
CpK值总是一个常数，我猜min函数不能用这种格式，任何想法？我也尝试用Cp =（Ts-Ti）/ 6s添加Cp列，效果很好
这里是我的数据框样本的dput（）导出：
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"68937", "68938", "68939"))
答案 0 :(得分：0)
我必须承认，这有点奇怪。 我认为发生了什么last grouping variable is dropped。这对于很多不同的情况实际上是有意义的，但不是你的。不过，我们可以破解它的方式：min和group_by之间存在一些意料之外的互动，但我并不完全确定。 几乎似乎有些错误。
table1 %>%
group_by(STEP_NAME) %>%
summarise(m = mean(DATA), s = sd(DATA), Ts = max(HIGH_LIMIT),
Ts = max(HIGH_LIMIT), Ti = min(LOW_LIMIT)) %>%
mutate(CpK1 = (m-Ti)/(3*s),
CpK2 = (Ts-m)/(3*s)) %>%
mutate(CpK = ifelse(CpK1 < CpK2, CpK1, CpK2)) %>%
select(-CpK1, -CpK2)
# A tibble: 5 x 6
STEP_NAME m s Ts Ti CpK
<fctr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 C10 104.522294 1.282699532 112.00 88.00 1.943221
2 R1 90.335988 0.327022906 93.90 87.90 2.482994
3 R2 2.140924 0.004407826 2.22 2.08 4.607264
4 R3 30.058242 0.061715734 31.10 29.10 5.175568
5 R4 30.050151 0.065536919 31.10 29.10 4.832650
另一种方法是在group_by电话后添加另一个summarise来电：
table1 %>%
group_by(STEP_NAME) %>%
summarise(m = mean(DATA), s = sd(DATA), Ts = max(HIGH_LIMIT),
Ts = max(HIGH_LIMIT), Ti = min(LOW_LIMIT)) %>%
group_by(STEP_NAME) %>%
mutate(CpK = min((m-Ti)/(3*s), (Ts-m)/(3*s)))
# A tibble: 5 x 6
# Groups: STEP_NAME [5]
STEP_NAME m s Ts Ti CpK
<fctr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 C10 104.522294 1.282699532 112.00 88.00 1.943221
2 R1 90.335988 0.327022906 93.90 87.90 2.482994
3 R2 2.140924 0.004407826 2.22 2.08 4.607264
4 R3 30.058242 0.061715734 31.10 29.10 5.175568
5 R4 30.050151 0.065536919 31.10 29.10 4.832650