R for Reproducible Scientific Analysis: [Introduction to R and RStudio]({{ page.root }}/01-rstudio-intro/)

Key Points

Introduction to R and RStudio
  • Use RStudio to write and run R programs.

  • R has the usual arithmetic operators and mathematical functions.

  • Use <- to assign values to variables.

  • Use ls() to list the variables in a program.

  • Use rm() to delete objects in a program.

  • Use install.packages() to install packages (libraries).

Project Management With RStudio
  • Use RStudio to create and manage projects with consistent layout.

  • Treat raw data as read-only.

  • Treat generated output as disposable.

  • Separate function definition and application.

  • Use version control.

Seeking Help
  • Use help() to get online help in R.

Data Structures
  • Use read.csv to read tabular data in R.

  • The basic data types in R are double, integer, complex, logical, and character.

  • Use factors to represent categories in R.

Exploring Data Frames
  • Use cbind() to add a new column to a data frame.

  • Use rbind() to add a new row to a data frame.

  • Remove rows from a data frame.

  • Use na.omit() to remove rows from a data frame with NA values.

  • Use levels() and as.character() to explore and manipulate factors

  • Use str(), nrow(), ncol(), dim(), colnames(), rownames(), head() and typeof() to understand structure of the data frame

  • Read in a csv file using read.csv()

  • Understand length() of a data frame

Subsetting Data
  • Indexing in R starts at 1, not 0.

  • Access individual values by location using [].

  • Access slices of data using [low:high].

  • Access arbitrary sets of data using [c(...)].

  • Use which to select subsets of data based on value.

Control Flow
  • Use if and else to make choices.

  • Use for to repeat operations.

Creating Publication-Quality Graphics
  • Use ggplot2 to create plots.

  • Think about graphics in layers: aesthetics, geometry, statistics, scale transformation, and grouping.

  • Use vectorized operations instead of loops.

Functions Explained
  • Use function to define a new function in R.

  • Use parameters to pass values into functions.

  • Load functions into programs using source.

Writing Data
  • Save plots from RStudio using the ‘Export’ button.

  • Use write.table to save tabular data.

  • Use the plyr package to split data, apply functions to subsets, and combine the results.

Dataframe Manipulation with dplyr
  • Use the dplyr package to manipulate dataframes.

  • Use select() to choose variables from a dataframe.

  • Use filter() to choose data based on values.

  • Use group_by() and summarize() to work with subsets of data.

  • Use mutate() to create new variables.

Dataframe Manipulation with tidyr
  • Use the tidyr package to change the layout of dataframes.

  • Use gather() to go from wide to long format.

  • Use scatter() to go from long to wide format.

Producing Reports With knitr
  • Mix reporting written in R Markdown with software written in R.

  • Specify chunk options to control formatting.

  • Use knitr to convert these documents into PDF and other formats.

Writing Good Software
  • Document what and why, not how.

  • Break programs into short single-purpose functions.

  • Write re-runnable tests.

  • Don’t repeat yourself.

  • Don’t repeat yourself.

  • Be consistent in naming, indentation, and other aspects of style.

Introduction to R and RStudio

Project management with RStudio

Seeking help

Data structures

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

Data types

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).

Vectors - ?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 names() function.

Factors - ?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.

Lists - ?list() Lists are a data structure designed to store data of different types.

Matrices - ?matrix() Matrices are a data structure designed to store 2-dimensional data.

Data Frames - ?data.frame is a key data structure. It is a list of vectors. - 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: - ?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

Subsetting data

Control flow

Creating publication quality graphics


Functions explained

Writing data


Dataframe manipulation with dplyr

Dataframe manipulation with tidyr

Producing reports with knitr

Best practices for writing good code


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 (5,3).
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.