使用R将qicharts图转换为ggplot [英] Convert a qicharts plot to ggplot using R

问题描述

我的数据框看起来像这样

 日期时间<  -  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函数并获取此图。

  library（qicharts）
 qic（FailRate_M1，
x = Datetime，
 data = df1 ，
 chart ='c'，
 runvals = TRUE，
 cex = 1.2，
 main ='测量失败率（M1）'，
 ylab ='MFR （％）'，
 xlab ='Datetime'）
  

这张图可以使用ggplot绘图吗？或者可以将它转换为ggplot格式？请提供你的意见，并帮助我解决这个问题。

有很多功能都有自己定制的绘图方式，但我最好想看看我们是否可以将这些图转换为ggplot。

我试图做以下事情：

  p1 < -  qic FailRate_M1，
x = Datetime，
 data = df1，
 chart ='c'，
 runvals = TRUE，
 cex = 1.2，
 main ='测量失败率（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 
  

并获得以下错误错误：ggplot2不知道如何处理类qic的数据

解决方案

我并不熟悉 qicharts :: qic 在做什么，但以下模仿了核心图形的元素与 ggplot2 ：

  library（ggplot2）
 
 my_value < -  min（df1 $ FailRate_M1）+ 6 
 
 ggplot（df1，aes（x = Datetime，y = FailRate_M1，group = 1））+ 
 geom_line（color = （colorblue，size = 1）+ 
 geom_point（color =lightgreen，size = 3）+ 
 geom_point（data = subset（df1，FailRate_M1> = 10），color =red ，size = 4）+ 
 geom_hline（aes（yintercept = c（1.3,4.8）））+ 
 geom_hline（aes（yintercept = my_value），linetype = 2）+ 
 labs =测量失败率（M1），
y =MFR（％））
  

一些注释可以帮助您理解：

• 当 x 是一个因子时，您需要使用 aes（group = 1） code> ggplot（）知道数据属于一个，应该是连接的。在这种情况下，使用一行代码。


• 注意对 geom_point 的多次调用。第一个将绘制所有点。第二种方法会将 df1 $ FailRate_M1> = 10 中的子集数据以红色颜色。可能不太明显的是，在红色点下方有一个 lightgreen 点。


• 在调用 geom_hline 时，我将 yintercepts 与 c（ ）函数。或者，您可以拨打 geom_hline 两次。

My dataframe looks like this

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)

Now i use the qic function from the "qichart" package and obtain this plot.

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')

Can this plot be plotted using ggplot? or can it be converted to a ggplot format?. Kindly please provide your inputs and help me in solving this problem.

There are many functions that have thier own customized way of plotting but I would ideally like to see if we could convert those plots to ggplot.

I tried to do the following

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

and then I try to use ggplot

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

and get the following error "Error: ggplot2 doesn't know how to deal with data of class qic"

解决方案

I am not familiar with what what qicharts::qic is doing, but the following mimics the core elements of the graphic with ggplot2:

library(ggplot2)

my_value <- min(df1$FailRate_M1) + 6

ggplot(df1, aes(x = Datetime, y = FailRate_M1, group = 1)) +
  geom_line(color = "steelblue", size = 1) +
  geom_point(color = "lightgreen", size = 3) +
  geom_point(data = subset(df1, FailRate_M1 >= 10), color = "red", size = 4) +
  geom_hline(aes(yintercept = c(1.3, 4.8))) +
  geom_hline(aes(yintercept = my_value), linetype = 2) +
  labs(title = "Measurement Fail Rate (M1)",
       y = "MFR (%)")

A couple notes to aid your understanding:

• When x is a factor, you need to use aes(group = 1) so that ggplot() knows the data "belong together" and should be "connected". In this case, with a line.
• Notice the multiple calls to geom_point. The first will plot all of the points. The second will blot just the subset of data where df1$FailRate_M1 >= 10 with a red color. What may not be obvious is that there is a lightgreen point underneath this red point.
• On the call to geom_hline I am plotting multiple yintercepts with the c() function. Alternatively, you could call geom_hline twice.

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