The page size can be set by using the following line: pdf(“plot.pdf”, width=8,height=11) The code above set the page size to 8 multiply 11, which is the letter size. The following is a complete example. # create a simple data frame a
You may want to add a title for a plot page that contains multiple diagrams. The following R code plot 3 diagrams on one page, and add a title to the page. # create a simple data frame a
You can plot multiple diagrams on one page by using par() to set up the page layout. The following R code plot multiple diagrams on one page. # create a simple data frame a
If you want to replace a string in multiple files in a folder, you can use the following command: cd /path/to/folder sed -i ‘s/foo/bar/g’ * In the command line above, all occurrences of “foo” will be replaced with “bar”.
Required background knowledge: activation record, static scoping & dynamic scoping.
Below is not standard C code. (case1)
foo (double a, double b){ double square (double z) { return z * z; } return square (a) + square (b); } |
If you want to declare an empty vector in R, you can do the following: vec
In R, we can easily write a date frame object to a csv file. By using the method write.csv, the csv file can be generated under the same directory of your R script. write.csv(dataFrame, file=”median.csv”)
Installing R on Mac is very easy. Just download the installation file here: http://cran.r-project.org/bin/macosx/. The bin files will be automatically added to the PATH.
Installing R on Windows is pretty straightforward. Just go to the page and download the installation file here. Remember you need to add the bin directory to your “Path” environment variable.
Sometimes, you may want to run R Script by using command line. In this way, you can write a bash script and schedule a task everyday. In addition you can also pass different arguments to the R program. Create a R script “GetARgument.R”: args
The R code below reads a file line by line. path <- "/path/to/the/file" print(path) conn <- file(path,open="r") lines <- readLines(conn) for (i in 1:length(lines)){ print(lines[i]) } close(conn)path <- "/path/to/the/file" print(path) conn <- file(path,open="r") lines <- readLines(conn) for (i in 1:length(lines)){ print(lines[i]) } close(conn)
This post summarizes the top questions asked about Java regular expressions. As they are most frequently asked, you may find that they are also very useful.
This article summarizes top questions asked about C/C++ pointers on stackoverflow.com. Pointers are the most confusing part of C/C++, those questions use simple examples to explain key pointer concepts.
To store or transfer an image, we often need to convert an image to a string in such a way that the string represents the image. Like other programming languages (e.g. Java), we can also convert an image to a string representation in Python.
Backreferences in Java Regular Expressions is another important feature provided by Java.
To understand backreferences, we need to understand group first. Group in regular expression means treating multiple characters as a single unit. They are created by placing the characters to be grouped inside a set of parentheses – â€()â€. Each set of parentheses corresponds to a group.