Description
1) Introduction: plot(), qplot(), and ggplot(), Plus Somea) plot() - arguments, ancillary functions, and methods; par() and layout()b) qplot() and ggplot() - aesthetics, geometries, and other useful functionsc) other plotting functions in graphics and stats
Part I. An Overview of plot()
2) The plot() Function a) what the function is and how the function worksb) will use method .xy for example
3) The Arguments to plot()a) Type of plot, axis labels, plot titles, display formatb) Plotting characters, character size, fonts, colors, line styles and widths
4) Ancillary Functions to use with plot()a) axis(), box(), clip(), grid(), legend(), mtext(), rug()b) abline(), contour(), curve(), lines(), polypath()c) arrows(), image(), points(), polygon(), rect(), segments(), symbols(), text()d) axTicks(), identify(), locator(), pch(), strwidth(),
5) The Methods for plot()a) What are methods?b) Methods in the graphics packagec) Methods in the stats package
6) How to Use the Functions par() and layout()a) What par() doesb) Arguments specific to par()c) Multiple plots
Part II. A look at the ggplot2 Package
7) The Functions qplot(), ggplot(), and the Specialized Notation in ggplot2a) Working with qplot()b) The ggplot() functionc) Specialized notation
8) Themesa) The theme() functionb) The element_*() functions
9) Aesthetics and Geometriesa) The aes() functionb) The geom_*() functions
10) Controlling the Appearancea) The annotate_*() functionsb) The coord_*() functionsc) The facet_*() functionsd) The guide_*() functionse) The position_*() functionsf) The scale_*() functionsg) The stat_*() functions
Appendix I. Plots for Contingency TablesAppendix II. Plots for Continuous VariablesAppendix III. Plots for Data with a Limited Number of ValuesAppendix IV. Functions that Generate Multiple PlotsAppendix V. Plots for Time SeriesAppendix VI. Miscellaneous Plots
Author: Margot Tollefson
Publisher: Apress
Published: 04/30/2021
Pages: 401
Binding Type: Paperback
Weight: 1.60lbs
Size: 10.00h x 7.00w x 0.86d
ISBN13: 9781484268308
ISBN10: 148426830X
BISAC Categories:
- Computers | Artificial Intelligence | Computer Vision & Pattern Recognit
- Computers | Information Theory
Part I. An Overview of plot()
2) The plot() Function a) what the function is and how the function worksb) will use method .xy for example
3) The Arguments to plot()a) Type of plot, axis labels, plot titles, display formatb) Plotting characters, character size, fonts, colors, line styles and widths
4) Ancillary Functions to use with plot()a) axis(), box(), clip(), grid(), legend(), mtext(), rug()b) abline(), contour(), curve(), lines(), polypath()c) arrows(), image(), points(), polygon(), rect(), segments(), symbols(), text()d) axTicks(), identify(), locator(), pch(), strwidth(),
5) The Methods for plot()a) What are methods?b) Methods in the graphics packagec) Methods in the stats package
6) How to Use the Functions par() and layout()a) What par() doesb) Arguments specific to par()c) Multiple plots
Part II. A look at the ggplot2 Package
7) The Functions qplot(), ggplot(), and the Specialized Notation in ggplot2a) Working with qplot()b) The ggplot() functionc) Specialized notation
8) Themesa) The theme() functionb) The element_*() functions
9) Aesthetics and Geometriesa) The aes() functionb) The geom_*() functions
10) Controlling the Appearancea) The annotate_*() functionsb) The coord_*() functionsc) The facet_*() functionsd) The guide_*() functionse) The position_*() functionsf) The scale_*() functionsg) The stat_*() functions
Appendix I. Plots for Contingency TablesAppendix II. Plots for Continuous VariablesAppendix III. Plots for Data with a Limited Number of ValuesAppendix IV. Functions that Generate Multiple PlotsAppendix V. Plots for Time SeriesAppendix VI. Miscellaneous Plots
Author: Margot Tollefson
Publisher: Apress
Published: 04/30/2021
Pages: 401
Binding Type: Paperback
Weight: 1.60lbs
Size: 10.00h x 7.00w x 0.86d
ISBN13: 9781484268308
ISBN10: 148426830X
BISAC Categories:
- Computers | Artificial Intelligence | Computer Vision & Pattern Recognit
- Computers | Information Theory
About the Author
Margot Tollefson, PhD is a semi-retired freelance statistician, with her own consulting business, Vanward Statistics. She received her PhD in statistics from Iowa State University and has many years of experience applying R to statistical research problems. Dr. Tollefson has chosen to write this book because she often creates graphics using R and would like to share her knowledge and experience. Her professional blog is on WordPress at vanwardstat. Social media: @vanstat