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Home > Data > Data Visualization > R Graph Essentials
R Graph Essentials
R Graph Essentials

R Graph Essentials:

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R Graph Essentials

Chapter 2. Advanced Functions in Base Graphics

The goal of this chapter is to enable you to create different types of graphs in R. In Chapter 1, Base Graphics in R – One Step at a Time, you created scatterplots and line plots. Now in this chapter, you will learn how to create other types of graphs, including bar charts, histograms, boxplots, pie charts, and dotcharts. Topics covered in this chapter include the following:

  • Including a regression line and residuals in your graph
  • Creating complex multiple axes
  • Including grid lines and point labels
  • Shading and coloring your graph
  • Creating bar charts, histograms, boxplots, pie charts, and dotcharts
  • Adding LOWESS smoothers to your graph
  • Creating scatterplot matrices
  • Adding error bars

After working through this chapter, you should understand the principles behind certain advanced plotting functions and should be able to create a wide range of graphs for research and analysis.

Reading datasets into R

Several datasets have been created for this book and can be downloaded from the website for this book as text files. These text files also provide the R code for each chapter. Alternatively, copy the relevant CSV file into a convenient folder, make sure that the R working directory matches your folder, and use the read.csv() command. For example, to read a CSV file called Patients as the object T, enter the following syntax:

T <- read.csv("Patients.csv", h=T)

Further explanations on reading datasets will be given in this chapter.

Including a regression line and residuals

In the Creating scatterplots and line plots section in Chapter 1, Base Graphics in R – One Step at a Time, we saw how to use the abline() command and the lm() command to include a regression line in your graph. Now, we will take this idea a little further. The following regression uses a datafile in which a sample of 10 people rated a film by awarding scores out of 100. These people then viewed the film a second time 1 month later and again awarded scores. We wish to use a regression model to see how well the first rating scores predicted the second rating.

In an OLS regression with one predictor, we fit a model of the following form:

Yi  =  β0  +  β1 Xi  + ei

In this form, β0 is the intercept, β1 is the slope, and e i are the errors (or residuals).

Let's perform the regression on the data and plot the results. Along the way, we will learn some useful R syntax. Go to the code file of this chapter, and copy and paste...

A medical dataset to create graphs

For many of the examples in this book, we will use the following dataset. It gives medical data on 45 people: their names; their gender (a two-level categorical variable); their ethnicity (a four-level categorical variable, labeled 1, 2, and 3); the medical treatment they received (a three-level categorical variable with levels A, B, or C); their age band (a three-level categorical variable with levels Y, M, and E, standing for young, middle-aged, and elderly); their weight (body mass) before treatment (in kg) and weight (body mass) after treatment (in kg), their heights (in cm); whether they smoke (a two-level categorical variable with levels Y and N); whether they perform regular exercise (a two-level categorical variable with levels TRUE and FALSE); and finally, whether or not they recovered after treatment (a two-level categorical variable with levels 1 and 0). We read this dataset as an object called T. The syntax to read this dataset is given in...

Creating complex multiple axes

Now we will create a graph with two curves and three axes. First, let's read the following vectors of data:

x <- c(-25:25)

y <- 1.5*x + 2

z <- 0.3*(x**2) - 20

In the preceding code, we have a linear function and a quadratic function. As you will see, we will need some extra room for text on the right-hand margin. This is because we wish to add some explanatory text there. By default, graphs in R have margins that are as follows:

  • 5-lines wide on the bottom axis
  • 4-lines wide on the left-hand axis
  • 4-lines wide on the top axis
  • 2-lines wide on the right-hand axis

We want to create a right-hand margin 8.1-lines wide on the right axis using the mar argument, which controls margin widths:

par(mar=c(5, 4, 4, 8) + 0.1)

Note the syntax for changing the default margin width for any axis. You simply insert the desired line width value in the appropriate position within the mar argument. Now, we disable the default axes and plot as follows:

plot(x, y,type=&quot...

Including a grid on your graph

You can add a grid to your plot using the grid() command. Let's set up a simple graph and add a grid:

x <- seq(1:5)
y <- x
plot(x, y, pch = 16)

Let's add a default grid with horizontal and vertical grid lines at major units in both the horizontal and vertical directions:

grid()

You get the following graph:

Including a grid on your graph

Now, we omit the horizontal grid lines using ny = NA. Of course, you could do the same for the vertical grid lines.

plot(x, y, pch = 16)
grid(ny=NA)

We get the following graph:

Including a grid on your graph

Setting the numbers of grid lines to NULL produces the default option of grid lines at every unit, for example:

plot(x, y, pch = 16)
grid(nx = NULL, ny = NULL)

Reading datasets into R

Several datasets have been created for this book and can be downloaded from the website for this book as text files. These text files also provide the R code for each chapter. Alternatively, copy the relevant CSV file into a convenient folder, make sure that the R working directory matches your folder, and use the read.csv() command. For example, to read a CSV file called Patients as the object T, enter the following syntax:

T <- read.csv("Patients.csv", h=T)

Further explanations on reading datasets will be given in this chapter.

Including a regression line and residuals

In the Creating scatterplots and line plots section in Chapter 1, Base Graphics in R – One Step at a Time, we saw how to use the abline() command and the lm() command to include a regression line in your graph. Now, we will take this idea a little further. The following regression uses a datafile in which a sample of 10 people rated a film by awarding scores out of 100. These people then viewed the film a second time 1 month later and again awarded scores. We wish to use a regression model to see how well the first rating scores predicted the second rating.

In an OLS regression with one predictor, we fit a model of the following form:

Yi  =  β0  +  β1 Xi  + ei

In this form, β0 is the intercept, β1 is the slope, and e i are the errors (or residuals).

Let's perform the regression on the data and plot the results. Along the way, we will learn some useful R syntax. Go to the code file of this chapter, and copy and paste the following syntax into R. It contains...

A medical dataset to create graphs

For many of the examples in this book, we will use the following dataset. It gives medical data on 45 people: their names; their gender (a two-level categorical variable); their ethnicity (a four-level categorical variable, labeled 1, 2, and 3); the medical treatment they received (a three-level categorical variable with levels A, B, or C); their age band (a three-level categorical variable with levels Y, M, and E, standing for young, middle-aged, and elderly); their weight (body mass) before treatment (in kg) and weight (body mass) after treatment (in kg), their heights (in cm); whether they smoke (a two-level categorical variable with levels Y and N); whether they perform regular exercise (a two-level categorical variable with levels TRUE and FALSE); and finally, whether or not they recovered after treatment (a two-level categorical variable with levels 1 and 0). We read this dataset as an object called T. The syntax to read this dataset is given in the...

Creating complex multiple axes

Now we will create a graph with two curves and three axes. First, let's read the following vectors of data:

x <- c(-25:25)

y <- 1.5*x + 2

z <- 0.3*(x**2) - 20

In the preceding code, we have a linear function and a quadratic function. As you will see, we will need some extra room for text on the right-hand margin. This is because we wish to add some explanatory text there. By default, graphs in R have margins that are as follows:

  • 5-lines wide on the bottom axis

  • 4-lines wide on the left-hand axis

  • 4-lines wide on the top axis

  • 2-lines wide on the right-hand axis

We want to create a right-hand margin 8.1-lines wide on the right axis using the mar argument, which controls margin widths:

par(mar=c(5, 4, 4, 8) + 0.1)

Note the syntax for changing the default margin width for any axis. You simply insert the desired line width value in the appropriate position within the mar argument. Now, we disable the default axes and plot as follows:

plot(x, y,type="o", pch...

Including a grid on your graph

You can add a grid to your plot using the grid() command. Let's set up a simple graph and add a grid:

x <- seq(1:5)
y <- x
plot(x, y, pch = 16)

Let's add a default grid with horizontal and vertical grid lines at major units in both the horizontal and vertical directions:

grid()

You get the following graph:

Now, we omit the horizontal grid lines using ny = NA. Of course, you could do the same for the vertical grid lines.

plot(x, y, pch = 16)
grid(ny=NA)

We get the following graph:

Setting the numbers of grid lines to NULL produces the default option of grid lines at every unit, for example:

plot(x, y, pch = 16)
grid(nx = NULL, ny = NULL)

Shading and coloring your graph

You can shade and color your graphs using the polygon() command. To use the polygon() command, you must specify the horizontal and vertical axis limits, but you must also include the x and y variables as the middle arguments.

Let's create a quadratic curve and shade under it with a light green selected from the Hexadecimal Color Chart:

x <- 1:100
y <- 3*x^2 + 2*x + 7
plot(x, y)
lines(x, y)

polygon(cbind(c(min(x), x, max(x)), c(min(y), y, min(y))), col="#00CC66")

Here is the graph:

Using this approach, the polygon() command shades under the curve, between the minimum and maximum values of the x variable and below the y variable. The syntax involving cbind() is an elegant way of including the relevant limits.

The following example is more complex. It uses the rnorm() command to simulate values from a normal distribution, with a given mean and standard deviation. By default, random values with a mean of 0 and a standard deviation of 1 are produced. For...

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Description

This book is targeted at R programmers who want to learn the graphing capabilities of R. This book will presume that you have working knowledge of R.

What you will learn

  • Understand and implement the basic graphics syntax and techniques
  • Create scatterplots and line plots, and include mathematical expressions in them
  • Include more advanced graphics and color palettes in your graph
  • Create and customize graphs using the qplot function
  • Customize the graphics, backgrounds, sizes, and colors of your graph using ggplot
  • Add layers to your graph using ggplot
  • Make publicationquality graphs using ggplot
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Publication date : Sep 22, 2014
Length: 190 pages
Edition : 1st
Language : English
ISBN-13 : 9781783554553
Category :
Data
Languages :
R
Concepts :
Data Visualization

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Publication date : Sep 22, 2014
Length: 190 pages
Edition : 1st
Language : English
ISBN-13 : 9781783554553
Category :
Data
Languages :
R
Concepts :
Data Visualization

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Table of Contents

5 Chapters
1. Base Graphics in R – One Step at a Time Chevron down icon Chevron up icon
1. Base Graphics in R – One Step at a Time
Learning basic graphics techniques
Creating and joining points
Creating scatterplots and line plots
Colors in R
Passing parameter values to titles and labels
Including a regression line
Graphing mathematical functions
R provides many options
Creating graphs with several curves
Customizing your axes
Creating axis labels
Creating multiple graphs on the same page
Saving your graphs
Including mathematical expressions on your plots
Summary
2. Advanced Functions in Base Graphics Chevron down icon Chevron up icon
2. Advanced Functions in Base Graphics
Reading datasets into R
Including a regression line and residuals
A medical dataset to create graphs
Creating complex multiple axes
Including a grid on your graph
Shading and coloring your graph
Creating bar charts
R's color palettes
Using smoothers on your graph
Creating scatterplot matrices
Summary
3. Mastering the qplot Function Chevron down icon Chevron up icon
3. Mastering the qplot Function
About qplot
The qplot syntax
Producing scatterplots using qplot
Subsetting your data before graphing
Mapping aesthetics to categorical variables
Controlling colors on your graph
Setting up graphs as objects
Creating facet plots
Creating line graphs using qplot
Creating multiple curves simultaneously
Including smoothed curves
Creating histograms with qplot
Creating facet plots for histograms
Creating kernel density plots
Creating bar charts
Creating boxplots
Creating graphs with dates
Summary
4. Creating Graphs with ggplot Chevron down icon Chevron up icon
4. Creating Graphs with ggplot
Getting started with ggplot
Mapping color, shape, and size to a variable
Creating attractive color schemes
Creating curves for each factor level
Creating histograms
Creating bar charts
Creating boxplots
Labeling points with text
Including regression lines
Summary
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5
(4 Ratings)
5 star 50%
4 star 50%
3 star 0%
2 star 0%
1 star 0%
A. Zubarev Oct 19, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
R as a language has experienced an explosion in adoption in the last several years, and this is despite the proliferation of the spreadheet applications, most notably the Microsoft’s Excel. Besides, R Bloggers came up with a 14 bullet points list explaining why. While I do not agree with all the 14 points I admit that R has many unique capabilities, and one of them is its graphing (or charting, if you wish). R Graph Essentials is the book that aims straight at this strength making you very proficient in producing useful, awesomely looking and most importantly professional grade plots, charts or graphs.I must say Having David Alexander (the author) on board with you means you are bound to success, I liked his style of writing a lot. David possesses all the necessary skills to cover such a wide topic efficiently, accurately and comprehensively. I admit I had little issues producing most of the plots from the book. On one occasion only I got stuck with qplot not working, but Packt and the awesome R community on G+ replied quickly putting me back on tracks to charting by explaining that I need to install ggplot2. A big thank you!I advocate the book is best read with your R Studio humming alongside as you will have a ton of fun producing interesting graphs. And it is not important if you run a Linux or Windows.It was very convenient to have the datasets used for examples saved for later use (I recommend R Studio as one of the reasons as saving the state between sessions in it is trivial). The topics I wish the author could cover is how to put the graphics on the web and make the data obtained from a database, but the book explains how to get your data from files.In terms of closing, I have to say I benefited a lot from this book. As I work with data most of my time I was able to produce super nice histograms of table data (off flat files) which helped me get better insight into the selectivity of my data and this resulted in better and mew indexes yet some indexes even were removed in our SQL Server databases.My next to do as pet project is to visualize data movements. I trust it will be a lot of fun and this is all thanks to this book.Five out of five!
Amazon Verified review Amazon
Mariano Rico Dec 02, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
At last a nice explanation of the whole R graph system. It is especially interesting qplot, the basic framework to create packages like ggplot2. Also you have a good review of the classical plot() functions. Although plot() provides simpler graphs (compared, for instance, to ggplot2) you can achieve functionality that ggplot2 does not have, for instance, two y-axis graphs or nice fillings for black&white figures. With this book you can learn how to create your own data visualizations (graphs).A good recommendation despite its short length (180 pages).
Amazon Verified review Amazon
W Boudville Oct 10, 2014
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Congratulations on making it this far! Yes, I kid you not. If you are reading my review, then you already know R or know about it. R is now the de facto statistical package favoured by many maths departments throughout the world. What this means is that the researchers in those departments often write and debug the subroutines in R. All for free, as far as you are concerned. So looking at R is a good choice. But given that you are dealing with possibly large data, graphics routines are essential. The book focuses on what comes with R. The base set of graphics.We see that simple plotting of curves is available. Along with scatter plots and various histograms. The R code to generate those figures is short. Yes, it is programming, but you do not need prior knowledge of a fully fledged computer language like C or java. The R language is quicker to learn.The graphics examples in the book are nothing different or new from what any statistics text might show. Instead, it shows how R Graph can be equivalent to other packages like Mathematica, Maple, SAS, Splus etc. Those have been around much longer, but typically are not free.The book is not meant to teach stats graphics per se. So if you are also learning that, consider getting a pure text on it and then also use this Lillis book to aid in actually drawing some graphs.
Amazon Verified review Amazon
Daniel Strassburger Dec 10, 2014
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I highly recommend this text. This book will take you from analyzing to visualizing data in no time. Truly. Lillis does a superb job of breaking down the, all too often unnecessarily complex, syntax so the reader can fully understand how each component of code affects the output. As a PhD student in Social Psychology and earning a minor in Statistics, I can deeply appreciate the practical applications of each of the graphing tutorials Lillis has chosen to include in this text. For those readers who are eager to extend their skill set beyond base R graphics, Lillis introduces the reader to the grammar of ggplot - a highly customizable system of producing graphs. Because of its concise, accurate, practical examples and explanations, this text will proudly sit atop my list of resources as I continue to develop my skills when visualizing statistical analyses. More information about this text (including supplemental files) can be found at the publisher's website here: http://bit.ly/ZvZQDS
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FAQs

What is the digital copy I get with my Print order? Chevron down icon Chevron up icon

When you buy any Print edition of our Books, you can redeem (for free) the eBook edition of the Print Book you’ve purchased. This gives you instant access to your book when you make an order via PDF, EPUB or our online Reader experience.

What is the delivery time and cost of print book? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela
What is custom duty/charge? Chevron down icon Chevron up icon

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order? Chevron down icon Chevron up icon

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges? Chevron down icon Chevron up icon

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

  • If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
  • Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.
How can I cancel my order? Chevron down icon Chevron up icon

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy? Chevron down icon Chevron up icon

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

  1. If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
  2. Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
  3. You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
  4. Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
  5. If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
  6. Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged? Chevron down icon Chevron up icon

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use? Chevron down icon Chevron up icon

You can pay with the following card types:

  1. Visa Debit
  2. Visa Credit
  3. MasterCard
  4. PayPal
What is the delivery time and cost of print books? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela