R Graphics Cookbook PDF Download

Author: Winston Chang
Publisher: "O'Reilly Media, Inc."
ISBN: 1449316956
Category : Computers
Languages : en
Pages : 414

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Book Description
"Practical recipes for visualizing data"--Cover.

Author: Winston Chang
Publisher: "O'Reilly Media, Inc."
ISBN: 1491978554
Category : Computers
Languages : en
Pages : 444

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Book Description
This O’Reilly cookbook provides more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly—without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project and includes a discussion of how and why the recipe works. Most of the recipes in this second edition use the updated version of the ggplot2 package, a powerful and flexible way to make graphs in R. You’ll also find expanded content about the visual design of graphics. If you have at least a basic understanding of the R language, you’re ready to get started with this easy-to-use reference. Use R’s default graphics for quick exploration of data Create a variety of bar graphs, line graphs, and scatter plots Summarize data distributions with histograms, density curves, box plots, and more Provide annotations to help viewers interpret data Control the overall appearance of graphics Explore options for using colors in plots Create network graphs, heat maps, and 3D scatter plots Get your data into shape using packages from the tidyverse

Author: Jaynal Abedin
Publisher: Packt Publishing Ltd
ISBN: 1783988797
Category : Computers
Languages : en
Pages : 368

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Book Description
Targeted at those with an existing familiarity with R programming, this practical guide will appeal directly to programmers interested in learning effective data visualization techniques with R and a wide-range of its associated libraries.

Author: Hrishi V. Mittal
Publisher: Packt Publishing Ltd
ISBN: 9781849513067
Category : Computers
Languages : en
Pages : 255

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Book Description
This hands-on guide cuts short the preamble and gets straight to the point – actually creating graphs, instead of just theoretical learning. Each recipe is specifically tailored to fulfill your appetite for visually representing you data in the best way possible. This book is for readers already familiar with the basics of R who want to learn the best techniques and code to create graphics in R in the best way possible. It will also serve as an invaluable reference book for expert R users.

Author: Paul Teetor
Publisher: "O'Reilly Media, Inc."
ISBN: 1449307264
Category : Computers
Languages : en
Pages : 438

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Book Description
With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author

Author: JD Long
Publisher: "O'Reilly Media, Inc."
ISBN: 1492040630
Category : Computers
Languages : en
Pages : 600

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Book Description
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data

Author: Winston Chang
Publisher: O'Reilly Media, Incorporated
ISBN: 9781449316952
Category : Computers
Languages : en
Pages : 411

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Book Description
This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works. Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you’re ready to get started. Use R’s default graphics for quick exploration of data Create a variety of bar graphs, line graphs, and scatter plots Summarize data distributions with histograms, density curves, box plots, and other examples Provide annotations to help viewers interpret data Control the overall appearance of graphics Render data groups alongside each other for easy comparison Use colors in plots Create network graphs, heat maps, and 3D scatter plots Structure data for graphing

Author: Mike Ohlson de Fine
Publisher: Packt Publishing Ltd
ISBN: 1849513856
Category : Computers
Languages : en
Pages : 260

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Book Description
Annotation Python is a great object-oriented and interactive programming language that lets you develop graphics, both static and animated, using built-in vector graphics functions that are provided with Python. Python 2.6 Graphics Cookbook is a collection of straightforward recipes and illustrative screenshots for creating and animating graphic objects using the Python language. This book makes the process of developing graphics interesting and entertaining by working in a graphic workspace without the burden of mastering complicated language definitions and opaque examples. If you choose to work through all the recipes from the beginning, you will learn to install Python and create basic programs for making lines and shapes using the built-in Tkinter module. The confusing topic of color manipulation is explored in detail using existing Python tools as well as some new tools in the recipes. Next you will learn to manipulate font size, color, and placement of text as placing text exactly where you want on a screen can be tricky because font height, inter-character spacing, and text window dimensions all interfere with each other. Then you will learn how to animate graphics, for example having more than one independent graphic object co-exist and interact using various Python methods. You will also learn how you can work with raster images, such as converting their formats using the Python Imaging Library. Next you will learn how you can combine vector images with raster images so that you can animate the raster images with ease. You will also walk through a set of recipes with the help of which you can handle and manipulate blocks of raw data that may be hundreds of megabytes in size using datastreams, files, and hard drives. You will also learn how you can use Inkscape to dismantle existing images and use parts of them for your own graphics and Python programs. At the end of the book you will learn how you can create GUIs for different purposes. A quick reference for creating interesting graphic animations using Python programming.

Author: J. D. Long
Publisher:
ISBN: 9781492040675
Category : Mathematical statistics
Languages : en
Pages : 601

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Book Description
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an intermediate user, this book will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data.

Author: AshishSingh Bhatia
Publisher: Packt Publishing Ltd
ISBN: 1787287807
Category : Computers
Languages : en
Pages : 564

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Book Description
Explore over 110 recipes to analyze data and build predictive models with simple and easy-to-use R code About This Book Apply R to simplify predictive modeling with short and simple code Use machine learning to solve problems ranging from small to big data Build a training and testing dataset, applying different classification methods. Who This Book Is For This book is for data science professionals, data analysts, or people who have used R for data analysis and machine learning who now wish to become the go-to person for machine learning with R. Those who wish to improve the efficiency of their machine learning models and need to work with different kinds of data set will find this book very insightful. What You Will Learn Create and inspect transaction datasets and perform association analysis with the Apriori algorithm Visualize patterns and associations using a range of graphs and find frequent item-sets using the Eclat algorithm Compare differences between each regression method to discover how they solve problems Detect and impute missing values in air quality data Predict possible churn users with the classification approach Plot the autocorrelation function with time series analysis Use the Cox proportional hazards model for survival analysis Implement the clustering method to segment customer data Compress images with the dimension reduction method Incorporate R and Hadoop to solve machine learning problems on big data In Detail Big data has become a popular buzzword across many industries. An increasing number of people have been exposed to the term and are looking at how to leverage big data in their own businesses, to improve sales and profitability. However, collecting, aggregating, and visualizing data is just one part of the equation. Being able to extract useful information from data is another task, and a much more challenging one. Machine Learning with R Cookbook, Second Edition uses a practical approach to teach you how to perform machine learning with R. Each chapter is divided into several simple recipes. Through the step-by-step instructions provided in each recipe, you will be able to construct a predictive model by using a variety of machine learning packages. In this book, you will first learn to set up the R environment and use simple R commands to explore data. The next topic covers how to perform statistical analysis with machine learning analysis and assess created models, covered in detail later on in the book. You'll also learn how to integrate R and Hadoop to create a big data analysis platform. The detailed illustrations provide all the information required to start applying machine learning to individual projects. With Machine Learning with R Cookbook, machine learning has never been easier. Style and approach This is an easy-to-follow guide packed with hands-on examples of machine learning tasks. Each topic includes step-by-step instructions on tackling difficulties faced when applying R to machine learning.