R Dataset / Package DAAG / jobs

On this R-data statistics page, you will find information about the jobs data set which pertains to Canadian Labour Force Summary Data (1995-96). The jobs data set is found in the DAAG R package. You can load the jobs data set in R by issuing the following command at the console data("jobs"). This will load the data into a variable called jobs. If R says the jobs data set is not found, you can try installing the package by issuing this command install.packages("DAAG") and then attempt to reload the data with the library() command. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the jobs R data set. The size of this file is about 136,796 bytes.

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.

Source

Statistics Canada

Examples

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)

Dataset imported from https://www.r-project.org.

Attachments: csv, json

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