Graphical data analysis with R:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boca Raton [u.a.]
CRC Pr.
2015
|
| Series: | Chapman & Hall/CRC the R series
|
| Subjects: | |
| Online Access: | Klappentext Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | XIII, 296 S. graph. Darst. |
| ISBN: | 9781498715232 |
Staff View
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Record in the Search Index
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| adam_text | Graphical Data Analysis with R shows you what information you
can gain from graphical displays. The book focuses on why you draw
graphics to display data and which graphics to draw (and uses R to
do so). All the datasets are available in R or one of its packages and
the R code is available at rosuda.org/GDA.
Graphical data analysis is useful for data cleaning, exploring data
structure, detecting outliers and unusual groups, identifying trends
and clusters, spotting local patterns, evaluating modelling output,
and presenting results. This book guides you in choosing graphics
and understanding what information you can glean from them. It
can be used as a primary text in a graphical data analysis course
or as a supplement in a statistics course. Colour graphics are used
throughout.
Features
• Concentrates on why graphics are drawn and what they reveal
• Emphasises the value of drawing a variety of different graphics
• Uses real datasets in R to show how graphical data analysis
works in practice
• Supplies R code for all the graphics on the author’s website
• Includes a set of exercises in each chapter to facilitate hands-on
learning
Contents
Preface xi
1 Setting the Scene . 1
1.1 Graphics in action .................................................. 1
1.2 Introduction......................................................... 3
1.3 What is Graphical Data Analysis (GDA)?............................... 5
1.4 Using this book, the R code in it, and the book’s webpage .......... 14
2 Brief Review of the Literature and Background Materials 19
2.1 Literature review................................................... 19
2.2 Interactive graphics................................................ 21
2.3 Other graphics software ............................................ 21
2.4 Websites ........................................................... 22
2.5 Datasets............................................................ 23
2.6 Statistical texts .................................................. 25
3 Examining Continuous Variables 22
3.1 Introduction........................................................ 27
3.2 What features might continuous variables have?...................... 29
3.3 Looking for features ............................................... 30
3.4 Comparing distributions by subgroups................................ 44
3.5 What plots are there for individual continuous variables?........... 46
3.6 Plot options........................................................ 47
3.7 Modelling and testing for continuous variables ..................... 48
4 Displaying Categorical Data 53
4.1 Introduction........................................................ 53
4.2 What features might categorical variables have?..................... 56
4.3 Nominal data—no fixed category order ............................... 57
4.4 Ordinal data—fixed category order .................................. 62
4.5 Discrete data—counts and integers .................................. 66
4.6 Formats, factors, estimates, and barcharts ......................... 70
4.7 Modelling and testing for categorical variables .................... 71
vii
viii
5 Looking for Structure: Dependency Relationships and Associations 75
5.1 Introduction......................................................... 75
5.2 What features might be visible in scatterplots? ..................... 77
5.3 Looking at pairs of continuous variables............................. 78
5.4 Adding models: lines and smooths..................................... 83
5.5 Comparing groups within scatterplots ................................ 86
5.6 Scatterplot matrices for looking at many pairs of variables ......... 88
5.7 Scatterplot options ................................................. 92
5.8 Modelling and testing for relationships between variables ........... 94
6 Investigating Multivariate Continuous Data 99
6.1 Introduction......................................................... 99
6.2 What is a parallel coordinate plot (pep)?........................... 100
6.3 Features you can see with parallel coordinate plots ................ 102
6.4 Interpreting clustering results .................................... 106
6.5 Parallel coordinate plots and time series........................... 108
6.6 Parallel coordinate plots for indices .............................. 112
6.7 Options for parallel coordinate plots............................... 115
6.8 Modelling and testing for multivariate continuous data............. 127
6.9 Parallel coordinate plots and comparing model results .............. 127
7 Studying Multivariate Categorical Data 131
7.1 Introduction........................................................ 131
7.2 Data on the sinking of the Titanic ................................. 132
7.3 What is a mosaicplot? .............................................. 133
7.4 Different mosaicplots for different questions of interest........... 140
7.5 Which mosaicplot is the right one? ................................. 148
7.6 Additional options ................................................. 149
7.7 Modelling and testing for multivariate categorical data ............ 151
8 Getting an Overview 155
8.1 Introduction........................................................ 155
8.2 Many individual displays............................................ 159
8.3 Multivariate overviews.............................................. 162
8.4 Multivariate overviews for categorical variables.................... 168
8.5 Graphics by group .................................................. 170
8.6 Modelling and testing for overviews................................. 174
ix
9 Graphics and Data Quality: How Good Are the Data? 177
9.1 Introduction.................................................... 177
9.2 Missing values ................................................. 178
9.3 Outliers........................................................ 183
9.4 Modelling and testing for data quality.......................... 193
10 Comparisons, Comparisons, Comparisons 197
10.1 Introduction................................................... 197
10.2 Making comparisons............................................. 199
10.3 Making visual comparisons ..................................... 202
10.4 Comparing group effects graphically ........................... 208
10.5 Comparing rates visually....................................... 212
10.6 Graphics for comparing many subsets............................ 214
10.7 Graphics principles for comparisons............................ 216
10.8 Modelling and testing for comparisons ......................... 218
11 Graphics for Time Series 223
11.1 Introduction................................................... 223
11.2 Graphics for a single time series.............................. 224
11.3 Multiple series ............................................... 226
11.4 Special features of time series ............................... 233
11.5 Alternative graphics for time series .......................... 237
11.6 R classes and packages for time series......................... 238
11.7 Modelling and testing time series ............................. 238
12 Ensemble Graphics and Case Studies 243
12.1 Introduction................................................... 243
12.2 What is an ensemble of graphics? .............................. 246
12.3 Combining different views—a case study example ................ 248
12.4 Casestudies ................................................... 252
13 Some Notes on Graphics with R 257
13.1 Graphics systems in R ......................................... 257
13.2 Loading datasets and packages for graphical analysis........... 258
13.3 Graphics conventions in statistics ............................ 258
13.4 What is a graphic anyway?...................................... 259
13.5 Options for all graphics ...................................... 261
13.6 Some R graphics advice and coding tips......................... 264
13.7 Other graphics ................................................. 2R
13.8 Large datasets ................................................ 272
13.9 Perfecting graphics............................................ 273
X
14 Summary 27 5
14.1 Data analysis and graphics................................... 275
14.2 Key features of GDA.......................................... 276
14.3 Strengths and weaknesses of GDA.............................. 276
14.4 Recommendations for GDA ..................................... 277
References 279
General index..................................................... 291
Datasets index ................................................... 295
|
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| language | English |
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| spelling | Unwin, Antony Verfasser aut Graphical data analysis with R Antony Unwin Boca Raton [u.a.] CRC Pr. 2015 XIII, 296 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Chapman & Hall/CRC the R series Includes bibliographical references and index Information visualization Visual analytics Data mining Graphic methods R (Computer program language) R Programm (DE-588)4705956-4 gnd rswk-swf Visualisierung (DE-588)4188417-6 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Grafische Darstellung (DE-588)4129552-3 gnd rswk-swf Datenanalyse (DE-588)4123037-1 s Grafische Darstellung (DE-588)4129552-3 s Visualisierung (DE-588)4188417-6 s R Programm (DE-588)4705956-4 s DE-604 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028046588&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Klappentext Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028046588&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Unwin, Antony Graphical data analysis with R Information visualization Visual analytics Data mining Graphic methods R (Computer program language) R Programm (DE-588)4705956-4 gnd Visualisierung (DE-588)4188417-6 gnd Datenanalyse (DE-588)4123037-1 gnd Grafische Darstellung (DE-588)4129552-3 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4188417-6 (DE-588)4123037-1 (DE-588)4129552-3 |
| title | Graphical data analysis with R |
| title_auth | Graphical data analysis with R |
| title_exact_search | Graphical data analysis with R |
| title_full | Graphical data analysis with R Antony Unwin |
| title_fullStr | Graphical data analysis with R Antony Unwin |
| title_full_unstemmed | Graphical data analysis with R Antony Unwin |
| title_short | Graphical data analysis with R |
| title_sort | graphical data analysis with r |
| topic | Information visualization Visual analytics Data mining Graphic methods R (Computer program language) R Programm (DE-588)4705956-4 gnd Visualisierung (DE-588)4188417-6 gnd Datenanalyse (DE-588)4123037-1 gnd Grafische Darstellung (DE-588)4129552-3 gnd |
| topic_facet | Information visualization Visual analytics Data mining Graphic methods R (Computer program language) R Programm Visualisierung Datenanalyse Grafische Darstellung |
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