Graphical data analysis with R. (2018)
- Record Type:
- Book
- Title:
- Graphical data analysis with R. (2018)
- Main Title:
- Graphical data analysis with R
- Further Information:
- Note: Antony Unwin.
- Authors:
- Unwin, Antony
- Contents:
- Setting the Scene; Graphics in action; Introduction; What is graphical data analysis (GDA)?; Using this book, the R code in it, and the book’s webpage Brief Review of the Literature and Background Materials ; Literature review; Interactive graphics; Other graphics software; Websites; Datasets; Statistical texts Examining Continuous Variables ; Introduction; What features might continuous variables have?; Looking for features; Comparing distributions by subgroups; What plots are there for individual continuous variables?; Plot options; Modelling and testing for continuous variables Displaying Categorical Data ; Introduction; What features might categorical variables have?; Nominal data—no fixed category order; Ordinal data—fixed category order; Discrete data—counts and integers; Formats, factors, estimates, and barcharts; Modelling and testing for categorical variables Looking for Structure: Dependency Relationships and Associations ; Introduction; What features might be visible in scatterplots?; Looking at pairs of continuous variables; Adding models: lines and smooths; Comparing groups within scatterplots; Scatterplot matrices for looking at many pairs of variables; Scatterplot options; Modelling and testing for relationships between variables Investigating Multivariate Continuous Data; Introduction; What is a parallel coordinate plot (pcp)?; Features you can see with parallel coordinate plots; Interpreting clustering results; Parallel coordinate plots and time series;Setting the Scene; Graphics in action; Introduction; What is graphical data analysis (GDA)?; Using this book, the R code in it, and the book’s webpage Brief Review of the Literature and Background Materials ; Literature review; Interactive graphics; Other graphics software; Websites; Datasets; Statistical texts Examining Continuous Variables ; Introduction; What features might continuous variables have?; Looking for features; Comparing distributions by subgroups; What plots are there for individual continuous variables?; Plot options; Modelling and testing for continuous variables Displaying Categorical Data ; Introduction; What features might categorical variables have?; Nominal data—no fixed category order; Ordinal data—fixed category order; Discrete data—counts and integers; Formats, factors, estimates, and barcharts; Modelling and testing for categorical variables Looking for Structure: Dependency Relationships and Associations ; Introduction; What features might be visible in scatterplots?; Looking at pairs of continuous variables; Adding models: lines and smooths; Comparing groups within scatterplots; Scatterplot matrices for looking at many pairs of variables; Scatterplot options; Modelling and testing for relationships between variables Investigating Multivariate Continuous Data; Introduction; What is a parallel coordinate plot (pcp)?; Features you can see with parallel coordinate plots; Interpreting clustering results; Parallel coordinate plots and time series; Parallel coordinate plots for indices; Options for parallel coordinate plots; Modelling and testing for multivariate continuous data; Parallel coordinate plots and comparing model results Studying Multivariate Categorical Data ; Introduction; Data on the sinking of the Titanic; What is a mosaicplot?; Different mosaicplots for different questions of interest; Which mosaicplot is the right one?; Additional options; Modelling and testing for multivariate categorical data Getting an Overview ; Introduction; Many individual displays; Multivariate overviews; Multivariate overviews for categorical variables; Graphics by group; Modelling and testing for overviews Graphics and Data Quality: How Good Are the Data? ; Introduction; Missing values; Outliers; Modelling and testing for data quality Comparisons, Comparisons, Comparisons ; Introduction; Making comparisons; Making visual comparisons; Comparing group effects graphically; Comparing rates visually; Graphics for comparing many subsets; Graphics principles for comparisons; Modelling and testing for comparisons Graphics for Time Series; Introduction; Graphics for a single time series; Multiple series; Special features of time series; Alternative graphics for time series; R classes and packages for time series; Modelling and testing time series Ensemble Graphics and Case Studies ; Introduction; What is an ensemble of graphics?; Combining different views—a case study example; Case studies Some Notes on Graphics with R ; Graphics systems in R; Loading datasets and packages for graphical analysis; Graphics conventions in statistics; What is a graphic anyway?; Options for all graphics; Some R graphics advice and coding tips; Other graphics; Large datasets; Perfecting graphics Summary; Data analysis and graphics; Key features of GDA; Strengths and weaknesses of GDA; Recommendations for GDA References General Index Datasets Index … (more)
- Publisher Details:
- Place of publication not identified : Chapman and Hall/CRC
- Publication Date:
- 2018
- Extent:
- 1 online resource (310 pages), (135 illustrations)
- Subjects:
- 001.4226
Information visualization
Visual analytics
Data mining -- Graphic methods
R (Computer program language) - Languages:
- English
- ISBNs:
- 9781315360041
1315360047 - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.372408
- Ingest File:
- 01_358.xml