R Control Chart

Here's is an example of creating a histogram with a density distribution line.

hist(dataset$Age, 
     main = "Customer Count by Age",
     ylab="Customer Count", 
     xlab="Customer Age",
     xlim = c(18, 100),
     border="black",
     breaks=20,
     col=c("lightyellow", "lightblue"), 
     las=1,
     probability = TRUE
)

lines(density(dataset$Age),lty="dotdash", lwd=4, col="red")

Here's an example of creating a barblot

barplot(dataset$'Sales Revenue',        
        names.arg = dataset$'Age Group', 
        main = "Sales Revenue by Customer Age Group",
        col = c("red","yellow","orange","blue", "green")
)

minValue <- 0
maxValue <- max(as.vector(dataset$'Sales Revenue'))
yTicks <- seq(from=minValue, to = maxValue, length.out = 10)
yTicks <- pretty(yTicks)
yTickLabels <- paste("$",format(yTicks/1000, , big.mark=","), "K",sep="")
axis(2, at=yTicks, labels = yTickLabels, lty = 1, las=1, cex.axis=0.7 )

Of course, these are simple examples using the built-in R graphics functionality. You can also use a richer graphics package such as lattice or ggplot2 to create some really detailed charts and graphs.

Is this what you are looking for?

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...