Forum Discussion

tglah's avatar
tglah
Frequent Visitor
9 years ago

R Control Chart

HelloPBI Community,   I havent found too much info on R Control Charts in this forum and am wondering if there is anyone out there that could copy&paste one?     Cheers
MawashiKid's avatar
MawashiKid
Resolver II
9 years ago

RE : xBarChart

In true life scenario, I'd say the following data would probably be obtained as a result
of fancy mathemathic algorithm formula... though I'll leave that to Math PhDs...:smileyhappy:
So for for simplicity I just added a list of subgroup manually...

So here we go...

#declare qcc library:

library(qcc)

# Load a mock list of 10 subgroup data manually:

sg1 <- c(1.397742,1.399917,1.278918,1.279828) # Fill in subgroup 1 data!
sg2 <- c(1.283877,1.307215,1.341566,1.396107) # Fill in subgroup 2 data!
sg3 <- c(1.313634,1.278839,1.242498,1.331201) # Fill in subgroup 3 data!
sg4 <- c(1.245943,1.303432,1.390168,1.298949) # Fill in subgroup 4 data!
sg5 <- c(1.188624,1.226905,1.217450,1.284127) # Fill in subgroup 5 data!
sg6 <- c(1.287875,1.283185,1.234186,1.314055) # Fill in subgroup 6 data!
sg7 <- c(1.276711,1.284376,1.305309,1.249184) # Fill in subgroup 7 data!
sg8 <- c(1.312219,1.297509,1.272367,1.371223) # Fill in subgroup 8 data!
sg9 <- c(1.378350,1.312981,1.381944,1.268875) # Fill in subgroup 9 data!
sg10 <- c(1.332196,1.268824,1.299608,1.329053) # Fill in subgroup 10 data!

# Include those subgroups into a my.data mock list through rbind

my.data <- rbind(sg1,sg2,sg3,sg4,sg5,sg6,sg7,sg8,sg9,sg10)

# Draw the R Chart and calculate relevant metrics

q1 <- qcc(my.data, type="R", nsigmas=3)

which should generate similar R chart:



then add following to ldraw the X-BAR chart...

# Draw the X-Bar Chart and calculate relevant metrics
q2 <- qcc(my.data, type="xbar", nsigmas=3)

which should generate following X-Bar Chart:


Finally:

# Establish the LSL and USL as set by customer specs, then
# draw the process capability chart and calculate metrics:

lsl <- 1.31 # Fill in a mock LSL here!
usl <- 1.32 # Fill in a mock USL here!

process.capability(q2, spec.limits=c(lsl,usl))

which should end up with following:


Hope this helps...

  • tglah's avatar
    tglah
    Frequent Visitor
    9 years ago

    Thank you for all of this information! I am going to try and take some time this weekend to put into play your examples.

     

    Much appreciated! Ill reply back with any progress I can make.

     

    Cheers.

    • tglah's avatar
      tglah
      Frequent Visitor
      9 years ago

      I have been able to create the R and XBar charts in PowerBI R Visuals, but still need some adjustments as it doesnt look right to me (data not displaying as expected).

       

      library(qcc)

      months<- c("Jan", "Feb", "Mar", "Apr","May", "Jun","Jul","Aug","Sep","Oct","Nov","Dec")

      qcc(dataset, type="R", nsigmas=1, labels=months, xlab= "Month", ylab = "Service Level %", title = "Phone Call SVL", digits=3)

       

       

      Any idea how to get the Y axis to show as percentages? My data is in percentages as you can see when selecting a simple Line Chart from the PowerBI Visuals.

       

       

      Thanks for all your assistance!

       

       

       

      • MawashiKid's avatar
        MawashiKid
        Resolver II
        9 years ago

        Sorry for late response. For the sake of simplicity, I mainly used mock data which I entered
        manually. The idea was basically to create a series of 4 weeks subsets over a 12 months period sort if thing...
        We both agree that a real life scenario would have gone through a much fancier scenario such as querying data
        from a server and even adding conversion at some stage. I used numeric for simplicity.

        Also I noticed that even if qcc library offers a wide variety of statisitic chart [R, xBar,...], it doesn't seem to have
        any qcc - y axis formatting options parameter as you would probably find using scaling_y_continuous in ggplot2 library.
        So in this case I don't believe y axis percentage formatting could be done in one shot.

         

        My best bet would be to define the qcc : q1 R Chart and q2 xBar  in respectice class with a plot=False attribute

         library(qcc)
 Jan <- c(0.837742,0.839917,0.728918,0.729828) # Fill in subgroup January data!
 Feb <- c(0.783877,0.807215,0.841566,0.836107) # Fill in subgroup February data!
 Mar <- c(0.813634,0.728839,0.742498,0.831201) # Fill in subgroup March data!
 Apr <- c(0.745943,0.803432,0.830168,0.798949) # Fill in subgroup April data!
 May <- c(0.688624,0.726905,0.717450,0.784127) # Fill in subgroup May data!
 Jun <- c(0.787875,0.783185,0.714186,0.814055) # Fill in subgroup June data!
 Jul <- c(0.726711,0.784376,0.805309,0.749184) # Fill in subgroup July data!
 Aug <- c(0.812219,0.797509,0.722367,0.871223) # Fill in subgroup August data!
 Sep <- c(0.878350,0.812981,0.881944,0.768875) # Fill in subgroup September data!
 Oct <- c(0.832196,0.768824,0.799608,0.729053) # Fill in subgroup October data!
 Nov <- c(0.813634,0.728839,0.742498,0.831201) # Fill in subgroup November data!
 Dec <- c(0.726711,0.784376,0.805309,0.749184) # Fill in subgroup December data!
 
 # Include those subgroups into a my.data mock list through rbind
 
 dataset <- rbind(Jan,Feb,Mar,Apr,May,Jun,Jul,Aug,Sep,Oct,Nov,Dec)
 months<- c("Jan", "Feb", "Mar", "Apr","May", "Jun","Jul","Aug","Sep","Oct","Nov","Dec") 

         # assign q1
 q1 <- qcc(dataset, type="R", nsigmas=1, labels=months, xlab= "Month", ylab = "Service Level %", title = "Phone Call SVL", digits=3, label.limits = c("5%", "14%"),plot=FALSE)
 # assign q2
         q2 <- qcc(dataset, type="xbar", nsigmas=1, labels=months, xlab= "Month", ylab = "Service Level %", title = "Phone Call SVL", digits=3, label.limits = c("76%", "80%"), plot=FALSE)

        and then use each q1 & q2 with a plot method allowing to erase the y axis and redifine a new one with somekind of thicks. 

        plot(q1, yaxt="n", ... , xlab="Months", ylab="Service Levels %", title="Phone Call SVL", label.limits= c("5%", "13%"))

        plot(q2, yaxt="n", ...,  xlab="Months", ylab="Service Levels %", title="Phone Call SVL", label.limits= c("76%", "80%"))

        Tom Hopper has written a blog on rewriting qcc plot using ggplot2 and grid,
          https://tomhopper.me/2014/03/03/rewriting-plot-qcc-using-ggplot2-and-grid/

        though I haven't got a chance to dive deep into it. I wish I could bring you an easiy solution on y axis percentage formatting
        though I haven't found one with qcc. Sorry.