Reference

Last updated on 2024-12-10 | Edit this page

Reference

Introduction to R and RStudio

  • Use the escape key to cancel incomplete commands or running code (Ctrl+C) if you’re using R from the shell.
  • Basic arithmetic operations follow standard order of precedence:
    • Brackets: (, )
    • Exponents: ^ or **
    • Divide: /
    • Multiply: *
    • Add: +
    • Subtract: -
  • Scientific notation is available, e.g: 2e-3
  • Anything to the right of a # is a comment, R will ignore this!
  • Functions are denoted by function_name(). Expressions inside the brackets are evaluated before being passed to the function, and functions can be nested.
  • Mathematical functions: exp, sin, log, log10, log2 etc.
  • Comparison operators: <, <=, >, >=, ==, !=
  • Use all.equal to compare numbers!
  • <- is the assignment operator. Anything to the right is evaluate, then stored in a variable named to the left.
  • ls lists all variables and functions you’ve created
  • rm can be used to remove them
  • When assigning values to function arguments, you must use =.

Data structures

Individual values in R must be one of 5 data types, multiple values can be grouped in data structures.

Data types

  • typeof(object) gives information about an items data type.

  • There are 5 main data types:

    • ?numeric real (decimal) numbers
    • ?integer whole numbers only
    • ?character text
    • ?complex complex numbers
    • ?logical TRUE or FALSE values

    Special types:

    • ?NA missing values
    • ?NaN “not a number” for undefined values (e.g. 0/0).
    • ?Inf, -Inf infinity.
    • ?NULL a data structure that doesn’t exist

    NA can occur in any atomic vector. NaN, and Inf can only occur in complex, integer or numeric type vectors. Atomic vectors are the building blocks for all other data structures. A NULL value will occur in place of an entire data structure (but can occur as list elements).

Basic data structures in R:

  • atomic ?vector (can only contain one type)
  • ?list (containers for other objects)
  • ?data.frame two dimensional objects whose columns can contain different types of data
  • ?matrix two dimensional objects that can contain only one type of data.
  • ?factor vectors that contain predefined categorical data.
  • ?array multi-dimensional objects that can only contain one type of data

Remember that matrices are really atomic vectors underneath the hood, and that data.frames are really lists underneath the hood (this explains some of the weirder behaviour of R).

Useful functions for querying data structures:

  • ?str structure, prints out a summary of the whole data structure
  • ?typeof tells you the type inside an atomic vector
  • ?class what is the data structure?
  • ?head print the first n elements (rows for two-dimensional objects)
  • ?tail print the last n elements (rows for two-dimensional objects)
  • ?rownames, ?colnames, ?dimnames retrieve or modify the row names and column names of an object.
  • ?names retrieve or modify the names of an atomic vector or list (or columns of a data.frame).
  • ?length get the number of elements in an atomic vector
  • ?nrow, ?ncol, ?dim get the dimensions of a n-dimensional object (Won’t work on atomic vectors or lists).

Exploring Data Frames

  • read.csv to read in data in a regular structure
    • sep argument to specify the separator
      • “,” for comma separated
      • “\t” for tab separated
    • Other arguments:
      • header=TRUE if there is a header row

Seeking help

  • To access help for a function type ?function_name or help(function_name)
  • Use quotes for special operators e.g. ?"+"
  • Use fuzzy search if you can’t remember a name ‘??search_term’
  • CRAN task views are a good starting point.
  • Stack Overflow is a good place to get help with your code.
    • ?dput will dump data you are working from so others can load it easily.
    • sessionInfo() will give details of your setup that others may need for debugging.

Dataframe manipulation with dplyr

  • library(dplyr)
  • ?select to extract variables by name.
  • ?filter return rows with matching conditions.
  • ?group_by group data by one of more variables.
  • ?summarize summarize multiple values to a single value.
  • ?mutate add new variables to a data.frame.
  • Combine operations using the ?"|>" pipe operator.

Creating publication quality graphics

  • figures can be created with the grammar of graphics:
    • library(ggplot2)
    • ggplot to create the base figure
    • aesthetics specify the data axes, shape, color, and data size
    • geometry functions specify the type of plot, e.g. point, line, density, box
    • geometry functions also add statistical transforms, e.g. geom_smooth
    • scale functions change the mapping from data to aesthetics
    • facet functions stratify the figure into panels
    • aesthetics apply to individual layers, or can be set for the whole plot inside ggplot.
    • theme functions change the overall look of the plot
    • order of layers matters!
    • ggsave to save a figure.

Glossary

argument
A value given to a function or program when it runs. The term is often used interchangeably (and inconsistently) with parameter.
assign
To give a value a name by associating a variable with it.
body
(of a function): the statements that are executed when a function runs.
comment
A remark in a program that is intended to help human readers understand what is going on, but is ignored by the computer. Comments in Python, R, and the Unix shell start with a # character and run to the end of the line; comments in SQL start with --, and other languages have other conventions.
comma-separated values
(CSV) A common textual representation for tables in which the values in each row are separated by commas.
delimiter
A character or characters used to separate individual values, such as the commas between columns in a CSV file.
documentation
Human-language text written to explain what software does, how it works, or how to use it.
floating-point number
A number containing a fractional part and an exponent. See also: integer.
for loop
A loop that is executed once for each value in some kind of set, list, or range. See also: while loop.
index
A subscript that specifies the location of a single value in a collection, such as a single pixel in an image.
integer
A whole number, such as -12343. See also: floating-point number.
library
In R, the directory(ies) where packages are stored.
package
A collection of R functions, data and compiled code in a well-defined format. Packages are stored in a library and loaded using the library() function.
parameter
A variable named in the function’s declaration that is used to hold a value passed into the call. The term is often used interchangeably (and inconsistently) with argument.
return statement
A statement that causes a function to stop executing and return a value to its caller immediately.
sequence
A collection of information that is presented in a specific order.
shape
An array’s dimensions, represented as a vector. For example, a 5×3 array’s shape is (5,3).
string
Short for “character string”, a sequence of zero or more characters.
syntax error
A programming error that occurs when statements are in an order or contain characters not expected by the programming language.
type
The classification of something in a program (for example, the contents of a variable) as a kind of number (e.g. floating-point number, integer), string, or something else. In R the command typeof() is used to query a variables type.
while loop
A loop that keeps executing as long as some condition is true. See also: for loop.