Rstudio interaction

Our analysis should be located in a findable and accessible location. Getting used to a reusable project structure is good practice for our project data management.

Please create a folder called RProjects under the Documents folder

Exercise 1 - New Rstudio Project (4 min)

⁵

RStudio menu (top left corner): click File menu button,
Then New Project
Click New Directory
Click New Project
In Directory name type the name of your project, e.g. Rfoundation (Browse and select a folder where to locate your project, e.i. the RProjects folder)
Lastly, click the Create Project button

Panes or panels

There are four main panels on RStudio. We will soon work on these panels, but first be shortly introduced.

The upper-left panel is the editor where we interact with code and scripts.
The panel in the upper-right, where it says Environment is empty will show you the objects that you are currently working with.
The lower-left panel is called the console, which runs the R code. It only saves the code temporarily so it is mostly used as testing ground.
The panel in the bottom-right will display files, plots, packages, help and more.

Exercise 2 - Folder structure (3 min)

Create two folders in your project

scripts
data

In RStudio, you can use the fourth panel, click Files then New Folder.

When in doubt of naming conventions check⁶.

Exercise 3 - New R script (2 min)

RStudio menu (top left corner): click File, then New File, then R script. Did you see the shortcut? You can also create a new script with Ctrl+Shift+N, for mac users replace Ctrl for command. There is another button close by, maybe you already found it
Save your script. You can click on the save icon or Ctrl+S. Select the scripts folder and type a name like learning.R. ⁷
Now, check with your neighbour if they have finished too, maybe they need more time, or maybe you can help out

Exercise 4 - Add comments to your new R script file (3 min)

Comments start with a hash # and follows with a single space

# Description:
# Author:
# Date:

To add a section

# Starting with calculations --------------------------

From now on, I will recommend you to add a new section for each exercise, and comments on every line.

R syntax

Tip: To have a readable code, use spaces around all symbols and after commas.

To get the hang of R, we start using it as a calculator. Type 2 + 2 directly into the console panel and press enter. You should see this:

2 + 2

## [1] 4

Exercise 5 - Try any other calculation (2 min)

In your new script try a new calculation, and add comments
To run code from a script you need to click Ctrl+Enter or click the button Run (green right direction arrow)

R objects

R can calculate, but we would also like to save these results. We can store one or multiple values in objects to access them later.

Syntax: objectName <- value
Notice the symbol <- its called assignment operator
Values can be fixed, calculated or a result of a transformation

When in doubt of naming conventions and style check⁸.

Let’s create a few objects together

# Creating a few objects --------------------------

# text should be inside double quotes
today <- "Monday"
# numbers can be small, long or with decimals
howManyPeople <- 21
# Sometimes we need to save yes or no answers, 
# write TRUE or FALSE in upper case
myAnswer <- TRUE

Exercise 6 - Naming and syntax (4 min)

Now, stop for a sec and have a look at the style guide⁹ again and discuss with your neighbour. If you are keen and there is time, feel free to change the values of the objects we just created.

Functions

How to get help

To use functions we first need to learn how they work.

There are three ways to find help using RStudio¹⁰

?functionName
help(functionName)
Press F1 or command F1 on the functionName

From now on, I will encourage you to use the help for any new function you encounter.

Exercise 7 - Using the help on RStudio to find your objects (1 min)

What does ls stand for?
test ls() on your script
How many objects do you have in your environment?

R data types

We had created these three objects with specific R data types

numeric
logical
character

Exercise 8 - Check the R data type of your objects using `class` (2 min)

Articulate a description of each R data type

Data structures

vector
matrix
data.frame

Example of a numeric vector

We use the function c() to combine values and create vectors

track <- c(10, 2, 5.3, 6, -25, 14) # numeric vector
track

## [1]  10.0   2.0   5.3   6.0 -25.0  14.0

Exercise 9 - Create a vector (3 min)

You can create either a vector of characters or a vector of logicals

If you create a vector of characters use quotes "" for each value
If you create a vector of logicals use TRUE and FALSE as values

These is how the results should look

## [1] "one"   "two"   "three"

## [1]  TRUE  TRUE FALSE

Exercise 10 - Discuss with your neighbour (2 min )

Did an error come up? Could you fix it?
Did you use the help?
Did you google up for hints?

Exercise 11 - Other structures (4 min )

Use the help to find out more about

factor
list
Can you find an example of your own data where you can use one of these structures?

Import files

Let’s introduce some data to R.

First, make sure you have a data folder!

Remember R is case sensitive

download.file(url = "http://tiny.cc/csvexample", 
              destfile = "data/example.csv")

mydata <- read.csv(file = "data/example.csv")

Exercise 12 - Importing data into R (4 min)

Use the code above to import data into R.¹¹
It is recommended that you always use the help to find out more about the new functions before using them.¹²
checkout the function str with your new object

Exercise 13 - Let’s discuss

what have you learned from the new functions?
what kind of data did you read into R?
is str useful?

# let's now create a plot
plot(x = mydata$M_At1, y = mydata$M_At2)

Install packages

Most R packages can be installed like this: install.packages("packageName")

After installing, you need to load it using library(packageName). You will need to load a package for each new R session.

Then, go to the fourth panel and select the packages tab, after loading a package it should be checked.

You can also check sessionInfo()

Exercise 14 - Install the ggplot2 package for graphics (3 min)

Use what you have learned to install the ggplot2 package. After that, if you are keen you can install the tidyverse package.

library(ggplot2)

ggplot(data = mydata, 
       mapping = aes(x = M_At1, y = M_At2)) +
  geom_point()

Exercise 15 - how to find help on the web (7 min)

Your task is now to create a new ggplot with colours. It can be any kind of ggplot and you can use any colour
You need to google is out, you can work in pairs

This is the start of your own R self-learning path

Now look at your script, look how good you are doing, and you can keep going.

Resources

There are plenty of R resources, these are only a few.

Feedback

To finish up please send your anonymous feedback through this link before leaving http://tiny.cc/elixir_feedback

Close project

File close project (save your data if you want), then you can close RStudio.

Open source

This handout was written in Rmarkdown and uses the open-source style Tufte. It has been published in Github pages and also as a PDF handout.

All of the information of my courses can be found on my Github repo R for Data Analysis. These resources are freely available under the Creative Commons - Attribution Licence CC BY 4.0. You may re-use and adapt the material in any way you wish, without asking permission, provided you cite the original source. That is a link back to the website R for Data Analysis and my ORCID 0000-0002-8990-1985.

I acknowledge this publication is resulting from support of Elixir-Belgium for my role as data science and bioinformatics trainer.

Last update: 2018-02-14

See installation instructions installation.md ↩
“Learning to code is a never ending journey with a set of challenges and delights unique to each person”↩
Key levels of learning ↩
resources ↩
FYI: Projects make managing multiple directories straightforward↩
a style guide ↩
[The .R extension is important for R to recognise your script]↩
a style guide ↩
style guide ↩
The help panel will show you the Documentation with examples at the end↩
You can either read the example.csv file or copy another csv file to your data folder↩
You can also read other kinds of files using read.table or use functions from packages like readr↩

R foundations Handout

Paula Andrea Martinez

2018-02-19

Getting started

Remember

Hands-on Training

Starting with programming

This workshop aim

What is R and Rstudio

What are we going to learn?