CODEWITHSUNDEEP
rgraphggplot2
JD Long
JD Long

Reputation: 60756

Creating a Pareto Chart with ggplot2 and R

I have been struggling with how to make a Pareto Chart in R using the ggplot2 package. In many cases when making a bar chart or histogram we want items sorted by the X axis. In a Pareto Chart we want the items ordered descending by the value in the Y axis. Is there a way to get ggplot to plot items ordered by the value in the Y axis? I tried sorting the data frame first but it seems ggplot reorders them.

Example:

val <- read.csv("http://www.cerebralmastication.com/wp-content/uploads/2009/11/val.txt")
val<-with(val, val[order(-Value), ])
p <- ggplot(val)
p + geom_bar(aes(State, Value, fill=variable), stat = "identity", position="dodge") + scale_fill_brewer(palette = "Set1")

the data frame val is sorted but the output looks like this:

alt text
(source: cerebralmastication.com)

Hadley correctly pointed out that this produces a much better graphic for showing actuals vs. predicted:

ggplot(val, aes(State, Value)) + geom_bar(stat = "identity", subset = .(variable == "estimate"), fill = "grey70") + geom_crossbar(aes(ymin = Value, ymax = Value), subset = .(variable == "actual"))

which returns:

alt text
(source: cerebralmastication.com)

But it's still not a Pareto Chart. Any tips?

Upvotes: 20

Views: 27134

Answers (8)

bbiasi
bbiasi

Reputation: 1599

We can use the ggQC package.

library(ggplot2)
library(ggQC)
Data4Pareto <- data.frame(
  KPI = c("Customer Service Time", "Order Fulfillment", "Order Processing Time",
          "Order Production Time", "Order Quality Control Time", "Rework Time",
          "Shipping"),
  Time = c(1.50, 38.50, 3.75, 23.08, 1.92, 3.58, 73.17)) 


ggplot2::ggplot(Data4Pareto, aes(x = KPI, y = Time)) +
 ggQC::stat_pareto(point.color = "red",
                   point.size = 3,
                   line.color = "black",
                   bars.fill = c("blue", "orange")) +
  theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust=0.5))

enter image description here

Source

Upvotes: 5

Dirk is no longer here
Dirk is no longer here

Reputation: 368439

Subsetting and sorting your data;

valact <- subset(val, variable=='actual')
valsort <- valact[ order(-valact[,"Value"]),]

From there it's just a standard boxplot() with a very manual cumulative function on top:

op <- par(mar=c(3,3,3,3)) 
bp <- barplot(valsort [ , "Value"], ylab="", xlab="", ylim=c(0,1),    
              names.arg=as.character(valsort[,"State"]), main="How's that?") 
lines(bp, cumsum(valsort[,"Value"])/sum(valsort[,"Value"]), 
      ylim=c(0,1.05), col='red') 
axis(4)
box() 
par(op)

which should look like this

alt text
(source: eddelbuettel.com)

and it doesn't even need the overplotting trick as lines() happily annotates the initial plot.

Upvotes: 23

Fernando
Fernando

Reputation: 7905

freqplot = function(x, by = NULL, right = FALSE)
{
if(is.null(by)) stop('Valor de "by" precisa ser especificado.')
breaks = seq(min(x), max(x), by = by )
ecd = ecdf(x)
den = ecd(breaks)
table = table(cut(x, breaks = breaks, right = right))
table = table/sum(table)

intervs = factor(names(table), levels = names(table))
freq = as.numeric(table/sum(table))
acum = as.numeric(cumsum(table))

normalize.vec = function(x){
  (x - min(x))/(max(x) - min(x))
}

dados = data.frame(classe = intervs, freq = freq, acum = acum, acum_norm = normalize.vec(acum))
p = ggplot(dados) + 
  geom_bar(aes(classe, freq, fill = classe), stat = 'identity') +
  geom_point(aes(classe, acum_norm, group = '1'), shape = I(1), size = I(3), colour = 'gray20') +
  geom_line(aes(classe, acum_norm, group = '1'), colour = I('gray20'))

p
}

Upvotes: 0

Isaiah
Isaiah

Reputation: 2155

A traditional Pareto chart in ggplot2.......

Developed after reading Cano, E. L., Moguerza, J. M., & Redchuk, A. (2012). Six Sigma with R. (G. Robert, K. Hornik, & G. Parmigiani, Eds.) Springer. 

library(ggplot2);library(grid)

counts  <- c(80, 27, 66, 94, 33)
defects <- c("price code", "schedule date", "supplier code", "contact num.", "part num.")
dat <- data.frame(count = counts, defect = defects, stringsAsFactors=FALSE )
dat <- dat[order(dat$count, decreasing=TRUE),]
dat$defect <- factor(dat$defect, levels=dat$defect)
dat$cum <- cumsum(dat$count)
count.sum<-sum(dat$count)
dat$cum_perc<-100*dat$cum/count.sum

p1<-ggplot(dat, aes(x=defect, y=cum_perc, group=1))
p1<-p1 + geom_point(aes(colour=defect), size=4) + geom_path()

p1<-p1+ ggtitle('Pareto Chart')+ theme(axis.ticks.x = element_blank(), axis.title.x = element_blank(),axis.text.x = element_blank())
p1<-p1+theme(legend.position="none")

p2<-ggplot(dat, aes(x=defect, y=count,colour=defect, fill=defect))
p2<- p2 + geom_bar()

p2<-p2+theme(legend.position="none")

plot.new()
grid.newpage()
pushViewport(viewport(layout = grid.layout(2, 1)))
print(p1, vp = viewport(layout.pos.row = 1,layout.pos.col = 1))
print(p2, vp = viewport(layout.pos.row = 2,layout.pos.col = 1))

Upvotes: 7

Richie Cotton
Richie Cotton

Reputation: 121127

To simplify things, let's just consider only the estimates.

estimates <- subset(val, variable == "estimate")

First we reorder the factor levels, so that States are plotted in decreasing order of Value.

estimates$State <- with(estimates, reorder(State, -Value))

Similarly, we reorder the dataset and calculate a cumulative value.

estimates <- estimates[order(estimates$Value, decreasing = TRUE),]
estimates$cumulative <- cumsum(estimates$Value)

Now we are ready to draw the plot. The trick to get a line and bar on the same axes is to convert the State variable (a factor) to be numeric. 

p <- ggplot(estimates, aes(State, Value)) + 
  geom_bar() +
  geom_line(aes(as.numeric(State), cumulative))
p

As mentioned in the question, trying to draw two Pareto plots of two variable groups right next to each other isn't very easy. You'd probably be better off using facetting if you want multiple Pareto plots.

Upvotes: 1

Yannick Wurm
Yannick Wurm

Reputation: 3708

With a simple example:

 > data
    PC1     PC2     PC3     PC4     PC5     PC6     PC7     PC8     PC9    PC10 
0.29056 0.23833 0.11003 0.05549 0.04678 0.03788 0.02770 0.02323 0.02211 0.01925

barplot(data) does things correctly

the ggplot equivalent "should be": qplot(x=names(data), y=data, geom='bar')

But that incorrectly reorders/sorts the bars alphabetically... because that's how levels(factor(names(data))) would be ordered.

Solution: qplot(x=factor(names(data), levels=names(data)), y=data, geom='bar')

Phew!

Upvotes: 4

Jonathan Chang
Jonathan Chang

Reputation: 25367

The bars in ggplot2 are ordered by the ordering of the levels in the factor.

val$State <- with(val, factor(val$State, levels=val[order(-Value), ]$State))

Upvotes: 16

Dirk is no longer here
Dirk is no longer here

Reputation: 368439

Also, see the package qcc which has a function pareto.chart(). Looks like it uses base graphics too, so start your bounty for a ggplot2-solution :-)

Upvotes: 3

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