The Grammar Of Graphics
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| Author | : Leland Wilkinson |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 415 |
| Release | : 2013-03-09 |
| Genre | : Computers |
| ISBN | : 1475731000 |
Written for statisticians, computer scientists, geographers, research and applied scientists, and others interested in visualizing data, this book presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. It was designed for a distributed computing environment, with special attention given to conserving computer code and system resources. While the tangible result of this work is a Java production graphics library, the text focuses on the deep structures involved in producing quantitative graphics from data. It investigates the rules that underlie pie charts, bar charts, scatterplots, function plots, maps, mosaics, and radar charts. These rules are abstracted from the work of Bertin, Cleveland, Kosslyn, MacEachren, Pinker, Tufte, Tukey, Tobler, and other theorists of quantitative graphics.
| Author | : Hadley Wickham |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 211 |
| Release | : 2009-10-03 |
| Genre | : Computers |
| ISBN | : 0387981411 |
Provides both rich theory and powerful applications Figures are accompanied by code required to produce them Full color figures
| Author | : Paul Murrell |
| Publisher | : CRC Press |
| Total Pages | : 442 |
| Release | : 2018-11-15 |
| Genre | : Computers |
| ISBN | : 0429749953 |
This third edition of Paul Murrell’s classic book on using R for graphics represents a major update, with a complete overhaul in focus and scope. It focuses primarily on the two core graphics packages in R - graphics and grid - and has a new section on integrating graphics. This section includes three new chapters: importing external images in to R; integrating the graphics and grid systems; and advanced SVG graphics. The emphasis in this third edition is on having the ability to produce detailed and customised graphics in a wide variety of formats, on being able to share and reuse those graphics, and on being able to integrate graphics from multiple systems. This book is aimed at all levels of R users. For people who are new to R, this book provides an overview of the graphics facilities, which is useful for understanding what to expect from R's graphics functions and how to modify or add to the output they produce. For intermediate-level R users, this book provides all of the information necessary to perform sophisticated customizations of plots produced in R. For advanced R users, this book contains vital information for producing coherent, reusable, and extensible graphics functions.
| Author | : Hadley Wickham |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 521 |
| Release | : 2016-12-12 |
| Genre | : Computers |
| ISBN | : 1491910364 |
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
| Author | : Michael Friendly |
| Publisher | : Harvard University Press |
| Total Pages | : 337 |
| Release | : 2021-06-08 |
| Genre | : Science |
| ISBN | : 0674259041 |
A comprehensive history of data visualization—its origins, rise, and effects on the ways we think about and solve problems. With complex information everywhere, graphics have become indispensable to our daily lives. Navigation apps show real-time, interactive traffic data. A color-coded map of exit polls details election balloting down to the county level. Charts communicate stock market trends, government spending, and the dangers of epidemics. A History of Data Visualization and Graphic Communication tells the story of how graphics left the exclusive confines of scientific research and became ubiquitous. As data visualization spread, it changed the way we think. Michael Friendly and Howard Wainer take us back to the beginnings of graphic communication in the mid-seventeenth century, when the Dutch cartographer Michael Florent van Langren created the first chart of statistical data, which showed estimates of the distance from Rome to Toledo. By 1786 William Playfair had invented the line graph and bar chart to explain trade imports and exports. In the nineteenth century, the “golden age” of data display, graphics found new uses in tracking disease outbreaks and understanding social issues. Friendly and Wainer make the case that the explosion in graphical communication both reinforced and was advanced by a cognitive revolution: visual thinking. Across disciplines, people realized that information could be conveyed more effectively by visual displays than by words or tables of numbers. Through stories and illustrations, A History of Data Visualization and Graphic Communication details the 400-year evolution of an intellectual framework that has become essential to both science and society at large.
| Author | : Winston Chang |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 414 |
| Release | : 2013 |
| Genre | : Computers |
| ISBN | : 1449316956 |
"Practical recipes for visualizing data"--Cover.
| Author | : Kieran Healy |
| Publisher | : Princeton University Press |
| Total Pages | : 292 |
| Release | : 2018-12-18 |
| Genre | : Social Science |
| ISBN | : 0691181624 |
An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions
| Author | : Leland Wilkinson |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 1996 |
| Genre | : Mathematical statistics |
| ISBN | : 9780135693100 |
This book offers a thorough introduction to using good statistical tools, both exploratory and confirmatory, to solve real statistical problems using SYSTAT statistical software.
| Author | : Stephen Michael Kosslyn |
| Publisher | : Oxford University Press |
| Total Pages | : 303 |
| Release | : 2006 |
| Genre | : Psychology |
| ISBN | : 0195306627 |
Addresses the problems that arise when we attempt to convey information with visual displays such as graphs by presenting psychological principles for constructing effective graphs. This work is useful for those who use visual displays to convey information in the sciences, humanities, and business such as finance, marketing, and advertising.
| Author | : Chester Ismay |
| Publisher | : CRC Press |
| Total Pages | : 461 |
| Release | : 2019-12-23 |
| Genre | : Mathematics |
| ISBN | : 1000763463 |
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.
