DAAG (version 1.24)

jobs: Canadian Labour Force Summary Data (1995-96)

Description

The number of workers in the Canadian labour force broken down by region (BC, Alberta, Prairies, Ontario, Quebec, Atlantic) for the 24-month period from January, 1995 to December, 1996 (a time when Canada was emerging from a deep economic recession).

Usage

jobs

Format

This data frame contains the following columns:

BC

monthly labour force counts in British Columbia

Alberta

monthly labour force counts in Alberta

Prairies

monthly labour force counts in Saskatchewan and Manitoba

Ontario

monthly labour force counts in Ontario

Quebec

monthly labour force counts in Quebec

Atlantic

monthly labour force counts in Newfoundland, Nova Scotia, Prince Edward Island and New Brunswick

Date

year (in decimal form)

Details

These data have been seasonally adjusted.

Examples

# NOT RUN {
print("Multiple Variables and Times - Example 2.1.4")
sapply(jobs, range)
pause()

matplot(jobs[,7], jobs[,-7], type="l", xlim=c(95,97.1))
 # Notice that we have been able to use a data frame as the second argument to matplot().
 # For more information on matplot(), type help(matplot)
text(rep(jobs[24,7], 6), jobs[24,1:6], names(jobs)[1:6], adj=0)
pause()

sapply(log(jobs[,-7]), range)
apply(sapply(log(jobs[,-7]), range), 2, diff)
pause()

oldpar <- par(mfrow=c(2,3))
range.log <- sapply(log(jobs[,-7], 2), range)
maxdiff <- max(apply(range.log, 2, diff))
range.log[2,] <- range.log[1,] + maxdiff
titles <- c("BC Jobs","Alberta Jobs","Prairie Jobs",
   "Ontario Jobs", "Quebec Jobs", "Atlantic Jobs")
for (i in 1:6){
plot(jobs$Date, log(jobs[,i], 2), type = "l", ylim = range.log[,i],
    xlab = "Time", ylab = "Number of jobs", main = titles[i])
}
par(oldpar)
# }