2 R

2.1 R

Created in 1992 by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand

• Free, open-source implementation of S
  • statistical programming language
  • Bell Labs

• Functional programming language
• Supports (and commonly used as) procedural (i.e., imperative) programming
• Object-oriented
• Interpreted (not compiled)

2.2 Interpreting values

When values and operations are inputted in the Console, the interpreter returns the results of its interpretation of the expression

2

## [1] 2

"String value"

## [1] "String value"

# comments are ignored

2.3 Basic types

R provides three core data types

• numeric
  • both integer and real numbers
• character
  • i.e., text, also called strings
• logical
  • TRUE or FALSE

2.4 Numeric operators

R provides a series of basic numeric operators

Operator	Meaning	Example	Output
+	Plus	5 + 2	7
-	Minus	5 - 2	3
*	Product	5 * 2	10
/	Division	5 / 2	2.5
%/%	Integer division	5 %/% 2	2
%%	Module	5 %% 2	1
^	Power	5^2	25

5 + 2

## [1] 7

2.5 Logical operators

R provides a series of basic logical operators to test

Operator	Meaning	Example	Output
==	Equal	5 == 2	FALSE
!=	Not equal	5 != 2	TRUE
> (>=)	Greater (or equal)	5 > 2	TRUE
< (<=)	Less (or equal)	5 <= 2	FALSE
!	Not	!TRUE	FALSE
&	And	TRUE & FALSE	FALSE
|	Or	TRUE | FALSE	TRUE

5 >= 2

## [1] TRUE

2.6 Variables

Variables store data and can be defined

• using an identifier (e.g., a_variable)
• on the left of an assignment operator <-
• followed by the object to be linked to the identifier
• such as a value (e.g., 1)

a_variable <- 1

The value of the variable can be invoked by simply specifying the identifier.

a_variable

## [1] 1

2.7 Algorithms and functions

An algorithm or effective procedure is a mechanical rule, or automatic method, or programme for performing some mathematical operation (Cutland, 1980).

A program is a specific set of instructions that implement an abstract algorithm.

The definition of an algorithm (and thus a program) can consist of one or more functions

• set of instructions that preform a task
• possibly using an input, possibly returning an output value

Programming languages usually provide pre-defined functions that implement common algorithms (e.g., to find the square root of a number or to calculate a linear regression)

2.8 Functions

Functions execute complex operations and can be invoked

• specifying the function name
• the arguments (input values) between simple brackets
  • each argument corresponds to a parameter
  • sometimes the parameter name must be specified

sqrt(2)

## [1] 1.414214

round(1.414214, digits = 2)

## [1] 1.41

2.9 Functions and variables

• functions can be used on the right side of <-
• variables and functions can be used as arguments

sqrt_of_two <- sqrt(2)
sqrt_of_two

## [1] 1.414214

round(sqrt_of_two, digits = 2)

## [1] 1.41

round(sqrt(2), digits = 2)

## [1] 1.41

2.10 Naming

When creating an identifier for a variable or function

• R is a case sensitive language
  • UPPER and lower case are not the same
  • a_variable is different from a_VARIABLE
• names can include
  • alphanumeric symbols
  • . and _
• names must start with
  • a letter

2.11 Coding style

A coding style is a way of writing the code, including

• how variable and functions are named
  • lower case and _
• how spaces are used in the code
• which libraries are used

# Bad
X<-round(sqrt(2),2)

#Good
sqrt_of_two <- sqrt(2) %>%
 round(digits = 2)

Study the Tidyverse Style Guid and use it consistently!

2.12 R libraries

Libraries are collections of functions and/or datasets.

• installed in R using the function install.packages
• loaded using the function library
• every script needs to load all the library that it uses

install.packages("tidyverse")

library(tidyverse)

The meta-library Tidyverse contains many libraries, including stringr.

2.13 stringr

R provides some basic functions to manipulate strings, but the stringr library provides a more consistent and well-defined set

str_length("Leicester")

## [1] 9

str_detect("Leicester", "e")

## [1] TRUE

str_replace_all("Leicester", "e", "x")

## [1] "Lxicxstxr"

2.14 The pipe operator

The Tidyverse also provide a clean and effective way of combining multiple manipulation steps

The pipe operator %>%

• takes the result from one function
• and passes it to the next function
• as the first argument
• that doesn’t need to be included in the code anymore

2.15 Pipe example

2.16 Pipe example

The two codes below are equivalent

• the first simply invokes the functions
• the second uses the pipe operator %>%

round(sqrt(2), digits = 2)

## [1] 1.41

sqrt(2) %>%
 round(digits = 2)

## [1] 1.41