I’ve recently been scouring the internet for a public opinion data set pertaining to job satisfaction. I was particularly interested in examining how gender, age, and socio-economic status influence how satisfied an individual is with their current employment situation. For example, existing research suggests that women and private-sector employees tend to have higher levels of job satisfaction. While I did not find an satisfactory data set on job satisfaction, I did find some intriguing information on regional variation in job satisfaction in England. I will admit that I know very little about England and can not propose any plausible explanations for this variation. In any case, I’ve generated a Cleveland Dotplot using GGPlot2 and have included the image and my R code below. It would be intriguing to map this data onto a spatial map of England and I plan to work on that soon.

df = data.frame(Region=c("Southwest","West Midlands","Southeast",
"Yorkshire","East Midlands","East England","London",
"Northwest","Northeast"), Satisfaction=c(49,45,41,40,39,37,33,30,22),
Num=c(1:9))
Region = df[,1]
Satisfaction = df[,2]
Num = df[,3]
ggplot(df, aes(x=Satisfaction, y=reorder(Region,Num))) +
geom_point(colour="red", size=2.5) + opts(title="Job Satisfaction in England") +
ylab("Region") + xlim(10,70) +
opts(plot.title = theme_text(face = "bold", size=12)) +
xlab("") + ylab("") +
opts(axis.text.y = theme_text(family = "sans",
face = "bold", size = 8))+
opts(axis.text.x = theme_text(family = "sans",
face = "bold", size = 8))
R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).