國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Visualizing data in R 4graphics usin...

SpringerLink (Online service)

Visualizing data in R 4graphics using the base, graphics, stats, and ggplot2 packages /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Visualizing data in R 4by Margot Tollefson.
其他題名:	graphics using the base, graphics, stats, and ggplot2 packages /
作者:	Tollefson, Margot.
出版者:	Berkeley, CA :Apress :2021.
面頁冊數:	xv, 401 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Information visualization.
電子資源:	https://doi.org/10.1007/978-1-4842-6831-5
ISBN:	9781484268315$q(electronic bk.)

Visualizing data in R 4graphics using the base, graphics, stats, and ggplot2 packages /
Tollefson, Margot.

Visualizing data in R 4graphics using the base, graphics, stats, and ggplot2 packages /[electronic resource] :by Margot Tollefson. - Berkeley, CA :Apress :2021. - xv, 401 p. :ill., digital ;24 cm.

Part I. An Overview of plot() -- 1. Introduction: plot(),qplot(), and ggplot(), Plus Some -- 2. The plot() Function -- 3. The Arguments to plot() -- 4. Ancillary Functions for plot() -- 5. The Methods for plot() -- 6, Graphics Devices and Laying Out Plots -- Part II. A look at the ggplot2 Package -- 7. Graphics with the ggplot2 Package: An Introduction -- 8. Working with the ggplot() Function: The Theme and the Aesthetics -- 9. The Geometry, Statistic, Annotate, and Border Functions -- 10. Formatting and Plot Management Tools -- Part III. Appendices -- A. Plots for Contingency Tables and Discrete Data -- B. Plots for Continuous Variables -- C. Functions That Plot Multiple Plots -- D. Smoothers -- E. Plots for Time Series -- F. Miscellaneous Plotting Functions.

Master the syntax for working with R's 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()

ISBN: 9781484268315$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-6831-5doiSubjects--Topical Terms:

248886
Information visualization.

LC Class. No.: QA76.9.I52

Dewey Class. No.: 001.4226

Visualizing data in R 4graphics using the base, graphics, stats, and ggplot2 packages /
LDR:03579nmm a2200325 a 4500 001 599891
003 DE-He213
005 20210719133305.0
006 m d
007 cr nn 008maaau
008 211027s2021 cau s 0 eng d
020 $a 9781484268315$q(electronic bk.)
020 $a 9781484268308$q(paper)
024 7 $a 10.1007/978-1-4842-6831-5 $2 doi
035 $a 978-1-4842-6831-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.I52
072 7 $a U $2 bicssc
072 7 $a COM000000 $2 bisacsh
072 7 $a UX $2 thema
082 0 4 $a 001.4226 $2 23
090 $a QA76.9.I52 $b T651 2021
100 1 $a Tollefson, Margot. $3 680806
245 1 0 $a Visualizing data in R 4 $h [electronic resource] : $b graphics using the base, graphics, stats, and ggplot2 packages / $c by Margot Tollefson.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2021.
300 $a xv, 401 p. : $b ill., digital ; $c 24 cm.
505 0 $a Part I. An Overview of plot() -- 1. Introduction: plot(),qplot(), and ggplot(), Plus Some -- 2. The plot() Function -- 3. The Arguments to plot() -- 4. Ancillary Functions for plot() -- 5. The Methods for plot() -- 6, Graphics Devices and Laying Out Plots -- Part II. A look at the ggplot2 Package -- 7. Graphics with the ggplot2 Package: An Introduction -- 8. Working with the ggplot() Function: The Theme and the Aesthetics -- 9. The Geometry, Statistic, Annotate, and Border Functions -- 10. Formatting and Plot Management Tools -- Part III. Appendices -- A. Plots for Contingency Tables and Discrete Data -- B. Plots for Continuous Variables -- C. Functions That Plot Multiple Plots -- D. Smoothers -- E. Plots for Time Series -- F. Miscellaneous Plotting Functions.
520 $a Master the syntax for working with R's 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()
650 0 $a Information visualization. $3 248886
650 0 $a Visual analytics. $3 285731
650 1 4 $a Professional Computing. $3 763344
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 274492
650 2 4 $a Data Structures and Information Theory. $3 825714
650 2 4 $a Artificial Intelligence. $3 212515
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-6831-5
950 $a Professional and Applied Computing (SpringerNature-12059)