1. ggplot2 Merrill Rudd TAs: Brooke Davis and Megsie Siple
FISH 512: Super-Advanced R

2. Goals for the lecture If you have used ggplot2 before:
learn some new tricks
obtain a useful handout
Share your tricks with others
If you have not used ggplot2 before:
Learn the basics
Start using for easy data exploration

3. Figure Credit: Sean Anderson

4. Sources http://docs.ggplot2.org/current/
Elegant Graphics for Data Analysis:
Sean Anderson – notes for ggplot2, FSH 554
Cookbook for R:

5. Fundamentals to ggplot2
Data massaging
Layering
Themes

6. Data massaging
AGRRA database

7. Data format requirements
“long” format data, “tidy data”
Each aesthetic or facet variable in its own column
Useful packages: reshape2, plyr, dplyr (Lecture 6)

8. Merging multiple data sets with shared columns
base R
merge()
Joins 2 data frames by matching ID variables
plyr
Join functions
Merge data frames by ID variables, more flexible than merge()
join_all() – list of data frames
Can specify rows to use (1st data frame only, rows from all data frames, etc.)
reshape2
melt()
Reshapes data into long form
Option to specify ID and measurement variables
Cast functions
Reshapes data into wide form
dcast() or acast() depending on if you want data frame or array output

9. Atlantic and Gulf Rapid Reef Assessment (AGRRA)

10. Variables in Data 3 data files Simplified variables for this example
Average and standard deviation for most variables
Shared ID Variables
Coral Mortality
Algae Abundance
Fish Biomass
Country
Number of Corals
Crustose
Total Fish Biomass
Year
Total Standing Dead
Turf
Herbivore Biomass
Site
Macro
Invertivore Biomass
Date
Piscivore Biomass
Depth
Zone
Number of Transects

11. DataMassageAGRRA.R

12. DataMassageAGRRA.R
Wide form to long form

13. DataMassageAGRRA.R Wide form to long form
Specify variables that should have separate value columns

14. DataMassageAGRRA.R Wide form to long form
Specify variables that should have separate value columns
Get 2 separate value columns for each factor

15. DataMassageAGRRA.R Wide form to long form
Specify variables that should have separate value columns
Get 2 separate value columns for each factor
+ a couple other boring steps in code…. And repeat for algae and fish biomass data

16. DataMassageAGRRA.R
Join multiple data frames from a list

17. DataMassageAGRRA.R Join multiple data frames from a list
Include rows from all data frames, will result in NAs for ID variable combinations that don’t have data for some measurement variables

18. Take a look at the data structure “SelectAGRRA_long
Take a look at the data structure “SelectAGRRA_long.csv” read into “Explore_ggplot2.R” “DataMassageAGRRA.R” and original csv files for reference

19. Layering
ggplot2 functions

20. Difference between plot and ggplot2 functions
qplot = ggplot wrapper: less syntax for common tasks
ggplot will work in all cases

21. ggplot function
Layered grammar data + geometric representation + aesthetics + layout
See file: ggplot2_explore.R
Hadley Wickham – Elegant Graphics for Data Analysis

22. Data and aesthetic mapping
Data frame
Columns in data frame

23. Data and aesthetic mapping
Data frame
Columns in data frame
Can add data aesthetics to initial aes function,
or add as another layer later to base plot

24. Slide courtesy of Sean Anderson
Geoms
Slide courtesy of Sean Anderson

29. Position adjustment

31. Scales
Controls the mapping from data to aesthetic attributes scale_xxx_yyy()

34. Faceting Investigating whether patterns hold across all conditions
Discrete variables in data frame

38. Subsetting data
So far – all examples used data that was available for every ID variable
Country, Depth, Zone, Number of Transects (all data points)
Number of Corals, Total Fish Biomass (not all data points, but for all of the above categorical variables)
Need to subset data to adjust which data to plot when you’re only interested in 1 factor from a list of possible factors

41. Specifying data in geomOR
This example – just used a different subset from the same dataset
Useful if working with multiple datasets or would like to refer to any other object

42. Specifying data in geomOR
This example – just used a different subset from the same dataset
Useful if working with multiple datasets or would like to refer to any other object

43. Adding lines and rectangles to plots
See also: geom_abline()
geom_vline()
geom_hline()
geom_rect()

44. Statistics stat_smooth < 1000 points – default “loess”
> 1000 points – default “gam”
This would take a lot more time to create in base R!

48. Publication quality figures
Adjusting the theme

50. See example code for creating custom theme in“ggplot2_explore.R”
Courtesy of:

52. ggthemes package

53. Exercises in code
ending with…
Recreating this plot!

54. Coordinate System
Maps position of objects onto plane of the plot (x,y) coordinates – potential for more dimensions but not yet capable
Cartesian
Semi-log
Polar