See also my other programming languages links.
Starting with this
data.csv file, start R and:
coursedata <- read.csv(file="data.csv", head=TRUE, sep=",") coursedata summary(coursedata) summary(coursedata$Final) hist(coursedata$Final, xlim=c(0,50)) fit <- lm(coursedata$Final ~ coursedata$Assign) summary(fit) plot(coursedata$Assign, coursedata$Final) abline(fit)
Again, working with my
example.tex file. The old way to turn this into a PDF:
latex example dvips -Ppdf example ps2pdf example.ps example.pdf
The newer way:
When I process that input file, I get this PDF output.
For exercise 9, I included this graph:
It was produced by Graphviz from this DOT source file with the commands:
dot 9-graph-src.dot -Tpng -o 9-graph.png dot 9-graph-src.dot -Tgif -o 9-graph.gif dot 9-graph-src.dot -Tsvg -o 9-graph.svg
(which produce PNG, GIF, and SVG output, respectively). You can also look at the source for the exercise 10 graph.
The script uses
find to get all regular files (not directories, etc.) in the directory that are named like
*.py. Then each of those filenames is given to a sub-script that uses
grep to check if there are leading tabs. If there are, the filename is printed.