使用 R 将 qicharts 图转换为 ggplot

我的数据框看起来像这样

Datetime <- c("2015-09-29AM", "2015-09-29PM" ,"2015-09-30AM", "2015-09-30PM", "2015-10-01AM" ,"2015-10-01PM" 
              ,"2015-10-02AM", "2015-10-02PM" ,"2015-10-03AM" ,"2015-10-03PM", "2015-10-04AM" ,"2015-10-04PM" 
              ,"2015-10-05AM", "2015-10-05PM", "2015-10-06AM" ,"2015-10-06PM")
FailRate_M1 <- c(0.0000000,0.0000000,0.9615385,0.9009009,0.0000000,1.4492754,1.5151515,0.0000000,0.8849558,0.0000000,4.4444444,0.7142857
                  ,0.0000000,10.3448276,0.0000000,0.0000000)

df1 <- data.frame(Datetime,FailRate_M1)

现在我使用“qichart”包中的 qic 函数并获得此图。

library(qicharts)
   qic(FailRate_M1,               
        x        = Datetime,              
        data     = df1,                  
        chart    = 'c',
        runvals  = TRUE,               
        cex      = 1.2,
        main     = 'Measurement Fail Rate (M1)', 
        ylab     = 'MFR (%)',          
        xlab     = 'Datetime')

可以使用 ggplot 绘制该图吗？或者可以将其转换为ggplot格式吗？请提供您的意见并帮助我解决这个问题。

有许多函数都有自己定制的绘图方式，但我理想地想看看我们是否可以将这些绘图转换为 ggplot。

我尝试执行以下操作

p1<-  qic(FailRate_M1,               
        x        = Datetime,              
        data     = df1,                  
        chart    = 'c',
        runvals  = TRUE,               
        cex      = 1.2,
        main     = 'Measurement Fail Rate (M1)', 
        ylab     = 'MFR (%)',          
        xlab     = 'Datetime')

然后我尝试使用 ggplot

library(ggplot2)
sp <- ggplot(p1, aes(x = Datetime, y = FailRate_M1))+ 
  geom_point(size=2.5)
sp

并得到以下错误“错误：ggplot2 不知道如何处理 qic 类的数据"

基于 Jason 的答案和 p1 数据框。

您可以访问 qic 函数返回的值，并在函数调用中使用 print.out =TRUE 在控制台中查看它们。

使用 dplyr 更新了答案：

library(dplyr)
library(ggplot2)
library(ggExtra)# optional for plot tidying
df2 <- data.frame(p1$labels,p1$y,p1$cl,p1$ucl) %>%
  dplyr::rename(y = p1.y,
         Datetime = p1.labels,
         cl = p1.cl,
         ucl= p1.ucl)

p <- ggplot(df2, aes(x = Datetime, y = y, group = 1)) +
  theme_minimal() + 
  geom_line(color = "steelblue", size = 1) +
  geom_point(color = "steelblue", size = 3) +
  geom_point(data = subset(df2, FailRate_M1 >= 10), color = "red", size = 4) +
  geom_hline(aes(yintercept = cl)) +
  geom_hline(aes(yintercept = ucl)) +
  labs(title = "Measurement Fail Rate (M1)",
       y = "MFR (%)")
p <- p + removeGrid() + rotateTextX() #from ggExtra,personal preference
p

最终情节 https://i.stack.imgur.com/ocJb7.png

截距线不再是硬编码的。 我从所有运行/控制图中删除了无关的水平线，ggExtra的removeGrid和rotateTextX()比等效的ggplot2语法更容易记住（至少对我来说）