|Introduction to R and RStudio||
|Project Management With RStudio||
|Exploring Data Frames||
|Creating Publication-Quality Graphics with ggplot2||
|Splitting and Combining Data Frames with plyr||
|Dataframe Manipulation with dplyr||
|Dataframe Manipulation with tidyr||
|Producing Reports With knitr||
|Writing Good Software||
- 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:
- Scientific notation is available, e.g:
- 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:
- Comparison operators:
all.equalto compare numbers!
<-is the assignment operator. Anything to the right is evaluate, then stored in a variable named to the left.
lslists all variables and functions you’ve created
rmcan be used to remove them
- When assigning values to function arguments, you must use
- To create a new project, go to File -> New Project
- Install the
packratpackage to create self-contained projects
install.packagesto install packages from CRAN
libraryto load a package into R
packrat::statusto check whether all packages referenced in your scripts have been installed.
- To access help for a function type
- 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.
?dputwill 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.
Individual values in R must be one of 5 data types, multiple values can be grouped in data structures.
typeof(object)gives information about an items data type.
- There are 5 main data types:
?numericreal (decimal) numbers
?integerwhole numbers only
?logicalTRUE or FALSE values
?NaN“not a number” for undefined values (e.g.
?NULLa data structure that doesn’t exist
NAcan occur in any atomic vector.
Infcan only occur in complex, integer or numeric type vectors. Atomic vectors are the building blocks for all other data structures. A
NULLvalue will occur in place of an entire data structure (but can occur as list elements).
Basic data structures in R:
?vector(can only contain one type)
?list(containers for other objects)
?data.frametwo dimensional objects whose columns can contain different types of data
?matrixtwo dimensional objects that can contain only one type of data.
?factorvectors that contain predefined categorical data.
?arraymulti-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).
?vector()All items in a vector must be the same type.
- Items can be converted from one type to another using coercion.
- The concatenate function ‘c()’ will append items to a vector.
seq(from=0, to=1, by=1)will create a sequence of numbers.
- Items in a vector can be named using the
?factor()Factors are a data structure designed to store categorical data.
levels()shows the valid values that can be stored in a vector of type factor.
?list()Lists are a data structure designed to store data of different types.
?matrix()Matrices are a data structure designed to store 2-dimensional data.
?data.frameis a key data structure. It is a
cbind()will add a column (vector) to a data.frame.
rbind()will add a row (list) to a data.frame.
Useful functions for querying data structures:
?strstructure, prints out a summary of the whole data structure
?typeoftells you the type inside an atomic vector
?classwhat is the data structure?
?headprint the first
nelements (rows for two-dimensional objects)
?tailprint the last
nelements (rows for two-dimensional objects)
?dimnamesretrieve or modify the row names and column names of an object.
?namesretrieve or modify the names of an atomic vector or list (or columns of a data.frame).
?lengthget the number of elements in an atomic vector
?dimget the dimensions of a n-dimensional object (Won’t work on atomic vectors or lists).
read.csvto read in data in a regular structure
separgument to specify the separator
- ”,” for comma separated
- “\t” for tab separated
- Other arguments:
header=TRUEif there is a header row
- Elements can be accessed by:
- Logical vectors
[single square brackets:
- extract single elements or subset vectors
xextracts the first item from vector x.
- extract single elements of a list. The returned value will be another
- extract columns from a data.frame
[with two arguments to:
- extract rows and/or columns of
x[1,2]will extract the value in row 1, column 2.
x[2,:]will extract the entire second column of values.
- extract rows and/or columns of
[[double square brackets to extract items from lists.
$to access columns or list elements by name
- negative indices skip elements
ifcondition to start a conditional statement,
else ifcondition to provide additional tests, and
elseto provide a default
- The bodies of the branches of conditional statements must be indented.
==to test for equality.
X && Yis only true if both X and Y are
X || Yis true if either X or Y, or both, are
- Zero is considered
FALSE; all other numbers are considered
- Nest loops to operate on multi-dimensional data.
- figures can be created with the grammar of graphics:
ggplotto create the base figure
aesthetics specify the data axes, shape, color, and data size
geometry functions specify the type of plot, e.g.
geometry functions also add statistical transforms, e.g.
scalefunctions change the mapping from data to aesthetics
facetfunctions stratify the figure into panels
aesthetics apply to individual layers, or can be set for the whole plot inside
themefunctions change the overall look of the plot
- order of layers matters!
ggsaveto save a figure.
- Most functions and operations apply to each element of a vector
*applies element-wise to matrices
%*%for true matrix multiplication
TRUEif any element of a vector is
TRUEif all elements of a vector are
- Put code whose parameters change frequently in a function, then call it with different parameter values to customize its behavior.
- The last line of a function is returned, or you can use
- Any code written in the body of the function will preferably look for variables defined inside the function.
- Document Why, then What, then lastly How (if the code isn’t self explanatory)
write.tableto write out objects in regular format
quote=FALSEso that text isn’t wrapped in
- Use the
xxplyfamily of functions to apply functions to groups within some data.
- the first letter,
list corresponds to the input data
- the second letter denotes the output data structure
- Anonymous functions (those not assigned a name) are used inside the
plyrfamily of functions on groups within data.
?selectto extract variables by name.
?filterreturn rows with matching conditions.
?group_bygroup data by one of more variables.
?summarizesummarize multiple values to a single value.
?mutateadd new variables to a data.frame.
- Combine operations using the
?pivot_longerconvert data from wide to long format.
?pivot_widerconvert data from long to wide format.
?separatesplit a single value into multiple values.
?unitemerge multiple values into a single value.
- Value of reproducible reports
- Basics of Markdown
- R code chunks
- Chunk options
- Inline R code
- Other output formats
- Program defensively, i.e., assume that errors are going to arise, and write code to detect them when they do.
- Write tests before writing code in order to help determine exactly what that code is supposed to do.
- Know what code is supposed to do before trying to debug it.
- Make it fail every time.
- Make it fail fast.
- Change one thing at a time, and for a reason.
- Keep track of what you’ve done.
- Be humble
- A value given to a function or program when it runs. The term is often used interchangeably (and inconsistently) with parameter.
- To give a value a name by associating a variable with it.
- (of a function): the statements that are executed when a function runs.
- 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.
- A character or characters used to separate individual values, such as the commas between columns in a CSV file.
- 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.
- A subscript that specifies the location of a single value in a collection, such as a single pixel in an image.
- A whole number, such as -12343. See also: floating-point number.
- In R, the directory(ies) where packages are stored.
- 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.
- 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.
- A collection of information that is presented in a specific order.
- An array’s dimensions, represented as a vector.
For example, a 5×3 array’s shape is
- 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.
- The classification of something in a program (for example, the contents of a variable) as a kind of number (e.g. floating-point, 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.