POLS/CSSS 503, University of Washington, Spring 2015

Learning Objectives

  1. Install R and RStudio
  2. Load data from a csv into R

Installing R

Install R, RStudio and devtools. Follow the instructions here.

Orientation with RStudio

R is the name of the programming language, and RStudio is a convenient and widely used interface to that language.

Since you will be using it for the remainder of the course, you should familiarize yourself with the RStudio GUI.

RStudio GUI

It consists of four windows,

  1. Bottom left: The console window. You type commands at the > prompt and R executes them.
  2. Top left: The editor window. Here you can edit and save R scripts which contain multiple R commands.
    • You can open a new R script using File -> New -> R script.
    • If you highlight an area, you can run those commands in the console with the “Run” button.
    • You can run all the commands in the editor window using the “Source” button.
  3. Top right
    • workspace lists all R objects (variables) that are defined
    • history lists all the commands that have been typed into the console.

  4. Bottom right

    • files allows you to browse directories and open files.
    • plots displays any plots created. In this window you can toggle back through previously created plots.
    • packages shows which packages are installed and loaded.
    • help displays R help.

RStudio documentation can be found at http://www.rstudio.com/ide/docs/. Of those, the most likely to be useful to you are:

Challenge:

  1. Go to Tools > Global Options. Change the font and color of the editor and console. Which one do you like the best?
  2. What happens when you type Alt+Shift+K?

Using R as a calculator

Although it is so much more, you can use R as a calculator. For example, to add, subtract, multiply or divide:

2 + 3
2 - 3
2 * 3
2 / 3

The power of a number is calculated with ^, e.g. \(4^2\) is,

4 ^ 2

R includes many functions for standard math functions. For example, the square root function is sqrt, e.g. \(\sqrt{2}\),

sqrt(2)

And you can combine many of them together

(2 * 4 + 3 ) / 10
sqrt(2 * 2)

Variables and Assignment

In R, you can save the results of calculations into objects that you can use later. This is done using the special symbol, <-. For example, this saves the results of 2 + 2 to an object named foo 1

foo <- 2 + 2

You can see that foo is equal to 4

foo

And you can reuse foo in other calculations,

foo + 3
foo / 2 * 8 + foo

You can use = instead of <- for assignment. You may see this in some other code. There are some technical reasons to use <- instead of =, but the primary reason we will use <- instead of = is that this is the convention used in modern R programs.

Challenge 1. Create a variable named whatever strikes your fancy and set it equal to the square root of 2. Then multiply it by 4. 2. Create a variable with a really long name and assign it a value. Start typing its name 3. Enter the following in the console sdgagasdgjasda.

Working Directory and R Projects

Working Directory

R Projects

Keeping all the files associated with a project organized together – input data, R scripts, analytical results, figures – is such a wise and common practice that RStudio has built-in support for this via its projects. Read this for more information about RStudio projects.

You will use RStudio projects for your labs and homeworks, and final paper. Create a RStudio project that you will use for all your labs.

  1. File -> New Project
  2. Select “New Directory”
  3. Select “Empty Project”
  4. Select a name for your project as Directory Name. “POLS_503_Labs” is as good as any, and better than most. Then choose where to put this directory with “Create project as sub-directory of”. Don’t worry about the other options.

Creating your first R Markdown Document

For this course, you will be we using R Markdown documents for homeworks. Create your firs

  1. File -> New File -> R Markdown
  2. Choose a title and author for your file. HTML output is fine.
  3. Hit OK. This will open a template for your Markdown file.
  4. Save this file with Ctrl-S.
  5. Click on the “Knit HTML” button. This will create a HTML document from this document.

Cheatsheets and additional resources about R Markdown are available at http://rmarkdown.rstudio.com/.

Loading Data into R

For the remainder of this lab you will be using a dataset of GDP per capita and fertility from Gapminder.2

Download the csv (“comma-separated values”)" https://github.com/POLS503/pols_503_sp15/blob/master/labs/gapminder.csv.

Then load the file

gapminder <- read.csv("gapminder.csv", stringsAsFactors = FALSE)

This creates a data frame. A data frame is a type of R object that corresponds to what you usually think of as a dataset or a spreadsheet — rows are observations and columns are variables.

Challenge: What happens when you do the following?

gapminder

This is a lot of information. How can we get a more useful picture of the dataset as a whole?

dim(gapminder)
names(gapminder)
head(gapminder)
summary(gapminder)

Challenge: Given the information previously:

  1. What are the variables in the dataset?
  2. How many observations are there?
  3. What is the unit of observation?
  4. What types of data are the different variables?
  5. What is the range of years in the data?
  6. What are the mean and median life expectancy?

Working with variables in Data Frames

You can extract single variables (or columns) and perform different operations on them. To extract a variable, we use the dollar sign ($) extraction operator.

gapminder$lifeExp

Again, perhaps a summary may be more interesting. We can do more specific operations on this variable alone:

mean(gapminder$lifeExp)
median(gapminder$lifeExp)
sd(gapminder$lifeExp)
min(gapminder$lifeExp)
max(gapminder$lifeExp)
quantile(gapminder$lifeExp)

Challenge 1. What are the mean and median of GDP per capita? 2. Find the 30th percentile of GDP per capita? 3. The function length() calculates the length of a vector. The function unique() returns the number of unique values in a vector. How many countries in the data are there? How many years?

Distributions

Summary statistics reduce the information of a distribution to single values. A distribution providess a richer understanding of the data. Look at the distribution of the variable lifeExp.

You will use the ggplot2 package for graphics for most of this course. In order to use it, you will need to load it using library()

library("ggplot2")

Create a histogram:

ggplot(gapminder, aes(x = lifeExp)) +
  geom_histogram()

You could also save the plot to a variable

lifexp_plot <- ggplot(gapminder, aes(x = lifeExp)) +
                      geom_histogram()

If you just enter the variable name in the console it will “print”" the object, which in this case, simply creates the plot:

lifexp_plot

Challenge Explore another variable of your choosing

  1. Look at some summary statistics for that variable.
  2. Visualize the distribution of that variable with a histogram.
  3. Describe this distribution in plain ordinary English to your partner.
  4. Write it as discussion in your R Markdown file.

Exploring relationships between variables

Use ggplot to create hisograms for each year

lifexp_plot + facet_wrap( ~ continent)

Challege: Describe how the distribution varies across years (Write it in your Markdown!)

You can also use ggplot2 to create a scatterplot

ggplot(gapminder, aes(y = lifeExp, x = log(gdpPercap))) +
  geom_point() +
  geom_smooth()

Challenge:

  1. Why is GDP per capita logged?
  2. Create a plot with a scatter plot of life expectancy vs. GDP per capita for each year.

Comments

Any R code following a hash (#) is not executed. These are called comments, and can and should be used to annotate and explain your code. For example, this doesn’t do anything.

#thisisacomment

And in this, nothing after the # is executed,

#this is still a comment
2 + 2 # this is also a comment

Challenge: What is this equal to?

5 * 4 # + 3 # - 8

R Scripts

You can save R commands in a file called an R script. To create a new R Script use File -> New File -> R Script. This will create a new tab in the upper left panel which will have a name like “Untitled1”. Save this to a file with the extension “.R” (RStudio will warn you if you do not)

To see how this works, write a few commands in the editor. For example,

2 + 2
3 + 8
mean(c(1, 2, 3))

You can run the current line or highlighted section with Ctl-Enter or the Run button.

Getting Help with R

Refer to Getting Help with R

  1. Refer to http://docs.ggplot2.org/current/ to find out how to create a density plot. Create a density plot of gdpPercap. Is is right skewed, left skewed, or symmetric?

  2. Go to stackoverlow and search for questions with tag [r].

    • What are featured questions today?
    • What is the most voted on question?
    • What is in the info tab?

  3. Find and download the cowsay package. You cannot use install.packages. What does the cowsay function do? Run it with something fun (it’ll make make sense once you know what it does).

Some text and the data set used in this are taken from Jenny Bryant, R basics, workspace and working directory, RStudio projects, licensed under CC BY-NC 3.0

  1. If you are curious as to why the variable was named foo, read this.↩

  2. Dataset from the gapminder R packager. The dataset in that package is an excerpt from the Gapminder data. Gapminder data is released under the Creative Commons Attribution 3.0 Unported license. See their terms of use.↩

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. R code is licensed under a BSD 2-clause license.