PDF Download R Graphics Cookbook: Practical Recipes for Visualizing Data
When you're a newbie reader or the one that attempt to begin love reading, you can select R Graphics Cookbook: Practical Recipes For Visualizing Data as the best alternative. This book is preferred amongst the viewers. This is one of the factors we suggest you to attempt analysis this book. Even this is not kind of book that will offer large possibility; you can get it detailed. As just what we constantly became aware of discovering can be done by steps. You cannot reach the knowledge at the same time by doing everything, it will certainly require some processes.
R Graphics Cookbook: Practical Recipes for Visualizing Data
PDF Download R Graphics Cookbook: Practical Recipes for Visualizing Data
R Graphics Cookbook: Practical Recipes For Visualizing Data. Provide us 5 minutes as well as we will certainly reveal you the very best book to check out today. This is it, the R Graphics Cookbook: Practical Recipes For Visualizing Data that will be your finest choice for far better reading book. Your five times will not spend lost by reading this site. You can take the book as a resource making far better principle. Referring the books R Graphics Cookbook: Practical Recipes For Visualizing Data that can be situated with your needs is at some point difficult. Yet below, this is so very easy. You could discover the most effective thing of book R Graphics Cookbook: Practical Recipes For Visualizing Data that you can review.
Obtaining the books R Graphics Cookbook: Practical Recipes For Visualizing Data now is not kind of hard means. You can not only going for publication shop or collection or borrowing from your pals to review them. This is an extremely straightforward way to exactly obtain guide by online. This on-line e-book R Graphics Cookbook: Practical Recipes For Visualizing Data could be one of the options to accompany you when having downtime. It will not lose your time. Believe me, guide will show you brand-new point to review. Just spend little time to open this on-line e-book R Graphics Cookbook: Practical Recipes For Visualizing Data and review them anywhere you are now.
The R Graphics Cookbook: Practical Recipes For Visualizing Data will additionally sow you great way to reach your suitable. When it comes true for you, you can read it in your leisure. Why don't you try it? In fact, you will certainly not know how precisely this publication will be, unless you review. Although you do not have much time to complete this publication rapidly, it actually does not need to complete fast. Choose your priceless free time to make use of to read this book.
The writer is really clever to select the words to use in making this publication. The options of words are crucial to produce a publication. It will certainly be proper to check out by such specific societies. Yet among the advances of this book is that this book is really appropriate for every culture. You may not hesitate to know nothing after reading this publication. R Graphics Cookbook: Practical Recipes For Visualizing Data could assist you to locate numerous things after reading.
Amazon.com Review
Q&A with Winston Chang, author of "R Graphics Cookbook: Practical Recipes for Visualizing Data" Q. Why is your book timely? A. Interest in R for data analysis and visualization has exploded in recent years. In the computer-tech world, computers and networks have made it much easier to gather and organize data, and more and more people have recognized that there's useful information to be found. To illustrate, consider the job "data scientist": this is a job title that didn't even exist five years ago, and now it's one of the hottest tickets on the market. At the same time, there's been a swell of interest in R in its more traditional setting, in science and engineering. I think there are many reasons for this. One, is that there's a growing recognition outside of the computer-programmer world that learning a little programming can save you a lot of time and reduce errors. Another reason is that the last few years have seen an improvement in the user-friendliness of tools for using R. So there's a lot of interest in using R for finding information in data, and visualization an essential tool for doing this. Data visualizations can help you understand your data and find patterns when you're in the exploratory phase of data analysis, and they are essential for communicating your findings to others. Q. What information do you hope that readers of your book will walk away with? A. As my book is a Cookbook, the primary goal is to efficiently present solutions for visualizing data, without demanding a large investment of time from the reader. For many readers, the goal is to just figure out how to make a particular type of graph and be done with it. There are others who will want to gain a deeper understanding of how graphing works in R. For these readers, I've written an appendix on the graphing package ggplot2, which is used extensively in the recipes in the book. This appendix explains some of the concepts in the grammar of graphics, and how they relate to structures common to data visualizations in general. Finally, I hope that readers will find ideas and inspiration for visualizing their data by browsing the pages and looking at the pictures. Q. What's the most exciting/important thing happening in your space? A. I'm excited that R is becoming more and more accessible to users who don't primarily identify as programmers. Many scientists, engineers, and data analysts have outgrown programs that provide canned data analysis routines, and they're turning increasingly to R. The growing popularity of R is part of a virtuous circle: as R gains a larger user base, it encourages people to create better educational materials and programming tools for R, which in turn helps to grow the number of R users. Technology-wise, I'm excited by Shiny, which is a framework for bringing R analyses to the web. (I should mention that this it's part of my job to work on the development of Shiny.) This makes it possible to build interactive applications for data analysis and visualization for users who don't need to know R, or even that the application is backed by R.
Read more
About the Author
Winston Chang is a software engineer at RStudio, where he works on data visualization and software development tools for R. He holds a Ph.D. in Psychology from Northwestern University. During his time as a graduate student, he created a website called "Cookbook for R", which contains recipes for handling common tasks in R. In previous lives, he was a philosophy graduate student and a computer programmer.
Read more
Product details
Paperback: 416 pages
Publisher: O'Reilly Media; 1 edition (January 6, 2013)
Language: English
ISBN-10: 1449316956
ISBN-13: 978-1449316952
Product Dimensions:
7 x 0.9 x 9.2 inches
Shipping Weight: 1.6 pounds (View shipping rates and policies)
Average Customer Review:
4.5 out of 5 stars
89 customer reviews
Amazon Best Sellers Rank:
#146,424 in Books (See Top 100 in Books)
This book is a must for anyone who works with ggplot2. There are so many excellent graph images, that I often flip through the book when I'm trying to figure out how to create a specific plot, but may not know what it is called.
If you're ever fumbling around with data in R, you're probably familiar with the built-in, unattractive graphics. ggplot2's been increasingly recognized as a necessity for getting the most out of your imagery. It offers nearly complete control over your graphics output, building them layer by layer.I spent a solid year learning and exploring R as a graduate student before I cracked open Winston Chang's R Graphics Cookbook and started learning ggplot2's little oddities. ggplot2 is itself almost like another language within R, but it's thankfully a very simple language -- far more simple and far more flexible, I feel, than the built-in graphics options.Since you'll be printing your graphics step by step -- your boundaries before your lines; your lines separately from points; etc. -- it's easy to keep track of where every impact on the output image is occurring, allowing you to easily tweak the code and get immediate results. E.g., if annotations are not lining up where you want, or font size needs to be reduced.Chang's cookbook is separated by what feature you need to either edit or create, making it easy to jump to what the reader needs. Full sections are devoted to bar graphs, line graphs, scatter plots, data distribution graphics, customizing annotations, axes, legends, color options, and cetera. Nearly 400 pages of text and images showing different ways of customizing and displaying every piece of your graphics. It's not a book you read cover to cover -- just the resource that 'cookbook' implies, meeting the reader's specific needs.If you want to just jump into the code and see what you can do with your own data, there's no better place to start. Almost no time is devoted to unnecessary exercises or teaching you the fundamentals of the R programming language. Exploring the far reaches of the Internet is a free alternative that's likely just as helpful, but Chang's book serves as a great reference, and contains almost everything you need all in one.
This book is the third that I have recently used to get up to speed on the R language and environment. The other two texts include "R in a Nutshell" and "R in Action" (see my review). The main catalysts behind my decision to purchase another book on R was my need to get up to speed with using the language to create graphs, and that not only are plotting functions that come with base R not unified behind a common interface and set of options, there exist limitations with base R plotting functions. Of course, there are other plotting functions across the over 2500 packages that have become available to the community, but the ggplot2 package that is the focus of this book is well regarded and grown in use to become one of the most popular R packages since its release in 2005.What Chang presents in this book is extremely practical. My recent pro bono work to move a client away from Microsoft Excel to this powerful open source platform and industry standard used for both small and big data analytics is partially testament to the usefulness of this book. While I have needed to peruse R package documentation as part of this work, it is not a stretch to say that a majority of what I needed was contained in this book, either as starting points or complete examples. The explanations are very well written and organized, and the fact that all of the pertinent graphs are in color was very helpful when it came time to understanding how ggplot2 can be used for tasks such as plotting multiple lines in one plot, and the data setup that is necessary to perform these tasks, which is a bit different than base R plotting functions, but worth the effort to use since ggplot2 employs universal usage patterns.While "R in Action" might be better at easing the reader into the R language and environment, this book starts with enough R basics in its first two chapters, such as installing packages and loading data, that most will find it sufficient for getting their feet wet, and the author's introduction to ggplot2 in the appendix combined with Chapter 15 (Getting Your Data into Shape) are not only well done, but very succinct for busy professionals. After discussing bar graphs, line graphs, scatter plots, and summarized data distributions, the author presents annotations, axes, legends, and controlling the overall appearance of graphs, followed by discussions on facets, miscellaneous graphs, and outputting for presentation. If you are new to ggplot2, you will probably need to touch a majority of these chapters to some degree in order to get up to speed, but information is easy to find. Very well recommended.
Great book! The book is very well organized, which enables fast learning.The reason for missing a star:After 3 chapters, I notice that there are a lot of similarities among of the plots. It would be immensely helpful if the author added a brief introductions on ggplot: the philosophy of the developers and the common features of different geoms. To me, it works like a photoshop, things work in layers and the order of layers affect the output. An overview of ggplot is helpful is because before you plot anything, it is a good idea to have a holistic picture in mind what layers I would be needing and which is the best way to organize the layers. Recipes are easy for instant hands-on, but to figure out the principles based on discrete recipes is a demanding job for average users.Updated: in the end of the book, there is appendix A, which explains the philosophy of ggplot. -This is exactly what I wanted. I realized this after finishing the first 6 chapter. It really helps.
I have Hadley Wickham's book on ggplot2 ggplot2: Elegant Graphics for Data Analysis (Use R!), which is a great introduction to advanced R graphics. However, since that book was published in 2009, a few updates in R and ggplot2 have made some of the tricks I used for plots obsolete and I've had to refer to the online ggplot2 documentation to update my code. The R Graphics Cookbook makes this task of finding best practices for ggplot2 much easier, and provides some really concrete examples. This R Graphics Cookbook and the ggplot2 book make for a powerful combination.
R Graphics Cookbook: Practical Recipes for Visualizing Data PDF
R Graphics Cookbook: Practical Recipes for Visualizing Data EPub
R Graphics Cookbook: Practical Recipes for Visualizing Data Doc
R Graphics Cookbook: Practical Recipes for Visualizing Data iBooks
R Graphics Cookbook: Practical Recipes for Visualizing Data rtf
R Graphics Cookbook: Practical Recipes for Visualizing Data Mobipocket
R Graphics Cookbook: Practical Recipes for Visualizing Data Kindle
