One of the many benefits of using R for data analysis is the
community behind it. Although our focus may be specific on language and
linguistics, R is used in a variety of different research and industry
areas, which means that different people use R to address different
needs. What this means is that there are a number of different
packages for R. Essentially, an R package is a set of
pre-created functions that someone else has made. By downloading and
installing an R package, you gain access to those functions.
A function in R is a command. It is a pre-made set of instructions
that are easily called upon by using the name of the function. Functions
in R will have a parentheses after their name. For example,
sum() is a function.
The parentheses contain the arguments for a function -
special instructions for the function, as well as the data you want the
function to operate on. Functions can have more than one argument,
depending on how the function was made.
print()Let’s look at the print() function. This function will
print the output of some operation to the R console. For example, if you
execute the command print('hello world'), the function will
print the string 'hello world' to the console.
## [1] "hello world"help()The print() function is a function that comes with R.
There are many other similar functions, such as the help()
function which will tell you about existing functions. Let’s try using
it to understand what print() does. Pay attention - here I
use print() and type just the name of the function I want
help for inside the help() function:
Print Values
Description
print prints its argument and returns it invisibly (via invisible(x)). It is a generic function which means that new printing methods can be easily added for new classes.
Usage
print(x, ...)
## S3 method for class 'factor'
print(x, quote = FALSE, max.levels = NULL,
width = getOption("width"), ...)
## S3 method for class 'table'
print(x, digits = getOption("digits"), quote = FALSE,
na.print = "", zero.print = "0",
right = is.numeric(x) || is.complex(x),
justify = "none", ...)
## S3 method for class 'function'
print(x, useSource = TRUE, ...)There are other ways of getting help for functions and commands in R,
such as using ?
sum()Let’s look at one more base function - sum(). This will
sum together all of the numbers that you provide to the function. For
example…
One number…
## [1] 1Two numbers…
## [1] 3Even more numbers…
## [1] 55seq()Functions usually aren’t as nice as sum(), and will
require a default number of arguments. Not including the correct number
will result in errors or other bad stuff. It’s always good to look at
the help documentation for a function and scroll down to check the
examples for use.
Let’s look at another function called seq()
Sequence Generation
Description
Generate regular sequences. seq is a standard generic with a default method. seq.int is a primitive which can be much faster but has a few restrictions. seq_along and seq_len are very fast primitives for two common cases.
Usage seq(…)
## Default S3 method:
seq(from = 1, to = 1, by = ((to - from)/(length.out - 1)),
length.out = NULL, along.with = NULL, ...)
seq.int(from, to, by, length.out, along.with, ...)
...The seq() function creates a sequence and has several
arguments used to create a sequence. The first arguments are
from and to. We can use these arguments inside
the function by calling their names. The from and
to arguments define the boundaries of the sequence.
A sequence from 1 to 8:
## [1] 1 2 3 4 5 6 7 8Notice that you can actually type the names of the arguments and use
= to specify their values. The seq() function
also has a by argument - it allows you to specify the size
of the sequence’s increments.
A sequence from 10 to 100, incremented by 5 each time:
## [1] 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100Arguments also have default positions in a function. Compare:
## [1] 1 2 3 4 5 6 7 8 9 10## [1] 1 2 3 4 5 6 7 8 9 10## [1] 1 2 3 4 5 6 7 8 9 10What is the default argument order for seq()?
It is a guarantee that you will want to install a new package to do
something else within R. There are many ways to get new packages, but
perhaps the most common way is to use the
install.packages() function in R. You use this function by
including the name of the package you want inside the function (make
sure to type the name of the package inside matching quote marks
'package' or "package").
Let’s practice this by installing a silly R package called
cowsay - here is how to do it:
install.packages('cowsay')You will see output that looks like this after you install it:
> install.packages('cowsay')
also installing the dependencies ‘fortunes’, ‘rmsfact’
trying URL 'https://cran.rstudio.com/bin/macosx/big-sur-arm64/contrib/4.4/fortunes_1.5-4.tgz'
Content type 'application/x-gzip' length 208887 bytes (203 KB)
==================================================
downloaded 203 KB
trying URL 'https://cran.rstudio.com/bin/macosx/big-sur-arm64/contrib/4.4/rmsfact_0.0.3.tgz'
Content type 'application/x-gzip' length 19378 bytes (18 KB)
==================================================
downloaded 18 KB
trying URL 'https://cran.rstudio.com/bin/macosx/big-sur-arm64/contrib/4.4/cowsay_0.9.0.tgz'
Content type 'application/x-gzip' length 400292 bytes (390 KB)
==================================================
downloaded 390 KB
The downloaded binary packages are in
/var/folders/4z/2cllrsm12cj_hhk_6cqygd_00000gn/T//RtmpuWey8q/downloaded_packagesOne you’ve installed a package, you need to load the package into R
so that you can use it. We do this with the library()
function. You type the name of the package in the function, like
this:
What is the cowsay package? Just like functions, we can also use
help() with packages. We just need to modify the function
to tell it to show the package index, which lists all the functions and
other parts of a package.
It seems that cowsay has three components:
animalsendless_horse()say()Let’s work with say(). Read the help page for it.
Sling messages and warnings with flair Description Sling messages and warnings with flair
Usage
say(
what = "Hello world!",
by = "cat",
type = NULL,
what_color = NULL,
by_color = NULL,
length = 18,
fortune = NULL,
...
)Let’s try it out:
##
## --------------
## Hello world!
## --------------
## \
## \
## \
## |\___/|
## ==) ^Y^ (==
## \ ^ /
## )=*=(
## / \
## | |
## /| | | |\
## \| | |_|/\
## jgs //_// ___/
## \_)
## What other values can we give? Running the function without valid
arguments gives us an error, but helpfully shows us the possible values
for the by argument, which controls the animal we see.
## Error in match.arg(by, c(choices = names(animals), "rms", "random")): 'arg' should be one of "cow", "chicken", "chuck", "clippy", "poop", "bigcat", "ant", "pumpkin", "ghost", "spider", "rabbit", "pig", "snowman", "frog", "hypnotoad", "shortcat", "longcat", "fish", "signbunny", "facecat", "behindcat", "stretchycat", "anxiouscat", "longtailcat", "cat", "trilobite", "shark", "buffalo", "grumpycat", "smallcat", "yoda", "mushroom", "endlesshorse", "bat", "bat2", "turkey", "monkey", "daemon", "egret", "duckling", "duck", "owl", "squirrel", "squirrel2", "goldfish", "alligator", "stegosaurus", "whale", "wolf", "rms", "random"##
## -----
## moo!
## ------
## \ ^__^
## \ (oo)\ ________
## (__)\ )\ /\
## ||------w|
## || ||You can use the :: command to access a function from an
installed package without loading it into your R session, using the
format package::function(). This is also a nice way to keep
track of which which function come from which libraries:
##
## --------------
## Hello world!
## --------------
## \
## \
## \
## |\___/|
## ==) ^Y^ (==
## \ ^ /
## )=*=(
## / \
## | |
## /| | | |\
## \| | |_|/\
## jgs //_// ___/
## \_)
## What doesendless_horse() functions do?
Try it out (press ESC to stop the horse…)
endless_horse()