Visualizing data in R 4 : graphics using the base, graphics, stats, and ggplot2 packages
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Format
Language
English
ISBN
9781484268315, 1484268318
UPC
10.1007/978-1-4842-6831-5
Notes
General Note
Chapter 5: The Methods of plot().
General Note
Includes index.
Description
Master the syntax for working with R plotting functions in graphics and stats in this easy reference to formatting plots. The approach in Visualizing Data in R 4 toward the application of formatting in ggplot() will follow the structure of the formatting used by the plotting functions in graphics and stats. This book will take advantage of the new features added to R 4 where appropriate including a refreshed color palette for charts, Cairo graphics with more fonts/symbols, and improved performance from grid graphics including ggplot 2 rendering speed. Visualizing Data in R 4 starts with an introduction and then is split into two parts and six appendices. Part I covers the function plot() and the ancillary functions you can use with plot(). You'll also see the functions par() and layout(), providing for multiple plots on a page. Part II goes over the basics of using the functions qplot() and ggplot() in the package ggplot2. The default plots generated by the functions qplot() and ggplot() give more sophisticated-looking plots than the default plots done by plot() and are easier to use, but the function plot() is more flexible. Both plot() and ggplot() allow for many layers to a plot. The six appendices will cover plots for contingency tables, plots for continuous variables, plots for data with a limited number of values, functions that generate multiple plots, plots for time series analysis, and some miscellaneous plots. Some of the functions that will be in the appendices include functions that generate histograms, bar charts, pie charts, box plots, and heatmaps. You will: Use R to create informative graphics Master plot(), qplot(), and ggplot() Discover the canned graphics functions in stats and graphics Format plots generated by plot() and ggplot().
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O'Reilly,O'Reilly Online Learning: Academic/Public Library Edition
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Citations
APA Citation, 7th Edition (style guide)
Tollefson, M. (2021). Visualizing data in R 4: graphics using the base, graphics, stats, and ggplot2 packages . Apress.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Tollefson, Margot. 2021. Visualizing Data in R 4: Graphics Using the Base, Graphics, Stats, and Ggplot2 Packages. Apress.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Tollefson, Margot. Visualizing Data in R 4: Graphics Using the Base, Graphics, Stats, and Ggplot2 Packages Apress, 2021.
MLA Citation, 9th Edition (style guide)Tollefson, Margot. Visualizing Data in R 4: Graphics Using the Base, Graphics, Stats, and Ggplot2 Packages Apress, 2021.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
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Grouped Work ID
aeb82891-b36c-7627-d7b8-b25eaec3e9dc-eng
Grouping Information
| Grouped Work ID | aeb82891-b36c-7627-d7b8-b25eaec3e9dc-eng |
|---|---|
| Full title | visualizing data in r 4 graphics using the base graphics stats and ggplot2 packages |
| Author | tollefson margot |
| Grouping Category | book |
| Last Update | 2024-10-08 10:55:34AM |
| Last Indexed | 2024-12-03 03:26:15AM |
Book Cover Information
| Image Source | contentCafe |
|---|---|
| First Loaded | Jan 22, 2024 |
| Last Used | Nov 11, 2024 |
Marc Record
| First Detected | Mar 21, 2023 11:05:02 AM |
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| Last File Modification Time | Mar 21, 2023 11:05:02 AM |
| Suppressed | Record had no items |
MARC Record
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| 082 | 0 | 4 | |a 001.4/226|2 23 |
| 100 | 1 | |a Tollefson, Margot. | |
| 245 | 1 | 0 | |a Visualizing data in R 4 :|b graphics using the base, graphics, stats, and ggplot2 packages /|c Margot Tollefson. |
| 260 | |a Berkeley, CA :|b Apress,|c 2021. | ||
| 300 | |a 1 online resource (404 pages) | ||
| 336 | |a text|b txt|2 rdacontent | ||
| 337 | |a computer|b c|2 rdamedia | ||
| 338 | |a online resource|b cr|2 rdacarrier | ||
| 500 | |a Chapter 5: The Methods of plot(). | ||
| 500 | |a Includes index. | ||
| 505 | 0 | |a Intro -- Table of Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Part I: An Overview of plot() -- Chapter 1: Introduction: plot(), qplot(), and ggplot(), Plus Some -- 1.1 plot(), par(), layout(), and split.screen() -- 1.2 qplot() and ggplot() -- 1.3 The Appendixes -- 1.4 Software Versions and Hardware Used in This Book -- 1.5 Graphics Devices -- Chapter 2: The plot() Function -- 2.1 Arguments and Default Values -- 2.2 Ancillary Functions -- 2.3 Methods -- 2.4 The Graphics Devices and the Functions par(), layout(), and split.screen() | |
| 505 | 8 | |a 2.5 An Example -- Chapter 3: The Arguments of plot() -- 3.1 The Dataset -- 3.2 Changing the Overall Appearance in plot() -- 3.2.1 Labels and Axis Limits -- 3.2.2 Box Type, Aspect Ratio, Annotation, and Expanded Plotting -- 3.3 Points and Lines -- 3.3.1 Types of Plots -- 3.3.2 The Arguments pch and lty -- 3.4 Details -- 3.4.1 Colors -- 3.4.1.1 Assigning Colors with Character Strings -- 3.4.1.2 Assigning Colors with Integers -- 3.4.1.3 Assigning Colors with Functions -- 3.4.2 Fonts and Font Families -- 3.4.2.1 Font Families and Assigning the Font Family in plot() | |
| 505 | 8 | |a 3.4.2.2 Font Weights in plot() -- 3.4.3 Character Size in plot() -- 3.4.4 Line Details: lwd, lend, ljoin, and lmitre -- 3.4.5 Making Changes to the Axes -- 3.4.6 Working with Log Scales -- Chapter 4: Ancillary Functions for plot() -- 4.1 Functions That Affect Overall Appearance -- 4.1.1 The title() Function -- 4.1.2 The axis() and axTicks() Functions -- 4.1.2.1 The axis() Function -- 4.1.2.2 The axTicks() Function -- 4.1.3 The box(), grid(), clip(), and rug() Functions -- 4.1.3.1 The box() Function -- 4.1.3.2 The grid() Function -- 4.1.3.3 The clip() Function -- 4.1.3.4 The rug() Function | |
| 505 | 8 | |a 4.2 Functions Defined at Points -- 4.2.1 The points() Function -- 4.2.2 The text() Function -- 4.2.3 The symbols() Function -- 4.2.4 The image() and rasterImage() Functions -- 4.2.4.1 The image() Function -- 4.2.4.2 The rasterImage() Function -- 4.3 Functions That Use Lines -- 4.3.1 The lines() and abline() Functions -- 4.3.2 The curve() Function -- 4.3.3 The segments() and arrows() Functions -- 4.3.3.1 The segments() Function -- 4.3.3.2 The arrows() Function -- 4.3.3.3 An Example of Using segments() and arrows() | |
| 505 | 8 | |a 4.3.4 Functions That Plot Lines That Close on Themselves: rect(), polygon(), and polypath() -- 4.3.4.1 The rect() Function -- 4.3.4.2 The polygon() Function -- 4.3.4.3 The polypath() Function -- 4.3.4.4 An Example of rect(), polygon(), and polypath() -- 4.3.5 The contour() Function -- 4.4 Functions to Provide Information About or to Interact with a Plot -- 4.4.1 The legend() and mtext() Functions -- 4.4.1.1 The legend() Function -- 4.4.1.2 The mtext() Function -- 4.4.2 The Interactive Functions: identify() and locator() -- 4.4.2.1 The identify() Function -- 4.4.2.2 The locator() Function | |
| 520 | |a Master the syntax for working with R plotting functions in graphics and stats in this easy reference to formatting plots. The approach in Visualizing Data in R 4 toward the application of formatting in ggplot() will follow the structure of the formatting used by the plotting functions in graphics and stats. This book will take advantage of the new features added to R 4 where appropriate including a refreshed color palette for charts, Cairo graphics with more fonts/symbols, and improved performance from grid graphics including ggplot 2 rendering speed. Visualizing Data in R 4 starts with an introduction and then is split into two parts and six appendices. Part I covers the function plot() and the ancillary functions you can use with plot(). You'll also see the functions par() and layout(), providing for multiple plots on a page. Part II goes over the basics of using the functions qplot() and ggplot() in the package ggplot2. The default plots generated by the functions qplot() and ggplot() give more sophisticated-looking plots than the default plots done by plot() and are easier to use, but the function plot() is more flexible. Both plot() and ggplot() allow for many layers to a plot. The six appendices will cover plots for contingency tables, plots for continuous variables, plots for data with a limited number of values, functions that generate multiple plots, plots for time series analysis, and some miscellaneous plots. Some of the functions that will be in the appendices include functions that generate histograms, bar charts, pie charts, box plots, and heatmaps. You will: Use R to create informative graphics Master plot(), qplot(), and ggplot() Discover the canned graphics functions in stats and graphics Format plots generated by plot() and ggplot(). | ||
| 588 | 0 | |a Print version record. | |
| 590 | |a O'Reilly|b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Information visualization.|9 311813 | |
| 650 | 0 | |a Visual analytics.|9 399406 | |
| 776 | 0 | 8 | |i Print version:|a Tollefson, Margot.|t Visualizing Data in R 4.|d Berkeley, CA : Apress L.P., ©2021|z 9781484268308 |
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