1. ggplot2 II EPID 799C Wed Sep 19 2017 New Packages (install now!)
RColorBrewer ggrepel plotly

2. Today’s Overview More ggplot: Homework 1: due today!
Scales
Colors
ggplot extension packages
Themes
Homework 1: due today!
Homework 2: out by tomorrow morning!

3. ggplot2
stats, scales, colors, themes

4. Ggplot components
data aesthetic mapping geometric object statistical transformations scales coordinate system position adjustments faceting

5. Ggplot components

6. Let’s Try
Review: make a scatterplot ggplot of the mpg dataset where displ and hwy are x and y. Overlay a linear relationship line by group using geom_smooth(). Color all of it by the class variable.
Add and tweak some geoms
add a layer with a black line modeling the overall relationship of the data. Hint: override… something!
We have overplotting going on (how you can tell?). Lower the points alpha and jitter to see the problem.
Add a geom_rug, just cuz. Jitter it as well.

7. Answers
# start with ggplot(mpg, aes(displ, hwy, color=class))+ geom_smooth()+ geom_point(alpha=0.2)+ # add geoms geom_jitter()+ geom_smooth(color="black")+ geom_rug(position = "jitter")

9. scales: position
Some form of: scale_x_continuous(limits=c(a,b), breaks=a:b) …is pretty common A note on clipping:

10. Let’s Try: Playing with scales

11. Answers
ggplot(mpg, aes(displ, hwy, color=class))+ geom_jitter()+ geom_smooth()+ geom_smooth(color="black")+ #scale_x_continuous(limits=c(0,NA))+ #scale_y_continuous(limits=c(0,NA)) #scale_x_continuous(limits=c(0,5)) coord_cartesian(xlim = c(0,5)) #change the "window" (needs all limits)

12. scales: color
Typically using brewer or manual

13. scales: color brewer RColorBrewer::display.brewer.all()
RColorBrewer::display.brewer.all()
Also, not covered, if you’re making maps, see tmaptools::palette_explorer()

14. Let’s Try

15. Answers
ggplot(mpg, aes(displ, hwy, color=class))+ geom_point()+ #scale_color_discrete() #scale_color_manual(values = c("red", "yellow", "green", "purple", "orange", "blue", "black")) #scale_color_brewer("Blues") #scale_color_brewer(type="seq", palette="OrRd", guide="colorbar") #scale_color_brewer(type="div", palette="Spectral", guide="legend") #scale_color_brewer(type="div", palette="OrRd") #scale_color_manual(values = RColorBrewer::brewer.pal(7, "Blues"))

16. positions

17. positions
dodge
fill
jitter
nudge
stack
ggplot(mpg, aes(fl, fill=drv))+ geom_bar(position=“<POSITION>”)
Where <POSITION> is one of: dodge fill jitter nudge stack
Can be tweaked further with the function equivalents position = position_dodge(width=1)
Or a few more detailed versions
…+geom_label(aes(label=mylabs), nudge_y=1)

18. Let’s Try

19. Answers
# Positions ggplot(mpg, aes(fl, fill=drv))+geom_bar() ggplot(mpg, aes(fl, fill=drv))+geom_bar(position="stack") ggplot(mpg, aes(fl, fill=drv))+geom_bar(position="dodge") ggplot(mpg, aes(fl, fill=drv))+geom_bar(position="fill") ggplot(mpg, aes(fl, fill=drv))+geom_bar(position="jitter") #ugh. ggplot(mpg, aes(cty, hwy, color=drv))+geom_point(position="jitter") ggplot(mpg, aes(cty, hwy, color=drv, label=drv))+geom_point()+geom_text(nudge_y = 2)

20. coordinate systems
Rarely used, except for coord_flip() Another solution in helper packages

21. labels
labs(), like last time, covers almost every label: x y title subtitle caption And can also do legend titles… …or do in the scale_*() function Use g+annotate() to just stick something (anything!) right where you want it.

22. Let’s Try

23. Answers
# Labels ggplot(mpg, aes(displ, hwy, color=class))+ geom_point()+ annotate(geom="text", x=1, y=4, label="Note: nothing in \n this corner")+ annotate(geom="point", x=1, y=4, color="red")+ scale_y_continuous(limits = c(0,NA))+ scale_x_continuous(limits = c(0,NA)) # Add labs #coord_flip()

24. Slightly More Advanced: stats
Put on your thinking caps

25. Layer=data+stats+geoms
Hadley’s (package author) underlying theory from grammar of graphics: layer=data+stats+geoms. Often stat or geom imply the other, so each has a default parameter of the other.
Excellent Stack Overflow Review
is-the-difference-between-geoms-and-stats-in-ggplot2

26. Let’s Try

27. Let’s dig in…
Default stats for geoms: reference/ggplot2/geom

28. stat variables
geoms, behind the scenes, often calculate a new dataframe to actually plot on screen.
stat_<thing> calculates a new dataframe explicitly
That dataframe has some “secret” (documented) variable names, accessible by special inline variables
..count.. ..ncount.. ..density.. ..ndensity..
..count.. ..prop.. Etc.
What if I want to refer to those new variables elsewhere in the ggplot call? (kinda guts / rare use)

29. Let’s Try

30. Answers
# Stats and geoms ggplot(mpg, aes(displ))+geom_bar(stat="count") ggplot(mpg, aes(displ))+stat_count(geom) ggplot(mpg, aes(displ))+geom_bar(stat="density", aes(fill=..density..), color=NA) ggplot(mpg, aes(displ))+geom_bar(stat="density", aes(color=..scaled..)) ggplot(mpg, aes(displ))+geom_bar(stat="density", aes(color=..count..)) ggplot(mpg, aes(displ))+geom_bar(stat="bin") ggplot(mpg, aes(displ, hwy))+geom_tile(stat="bin_2d") ggplot(mpg, aes(displ, hwy))+geom_hex(stat="") ggplot(mpg, aes(displ, hwy))+geom_bar(stat="bin_2d") ggplot(mpg, aes(cty, hwy, z=displ))+ geom_point(alpha=0.2)+geom_jitter(stat="unique")+ stat_ellipse() ggplot(mpg, aes(cty))+geom_bar(stat="density", aes(fill=..count..)) # stat = count or bin ggplot(mpg, aes(y=cty, x=manufacturer))+geom_boxplot(aes(color=..lower..)) #ggsave()

31. And: Saving a ggplot The usual GUI / Rstudio way
Simplest version is super easy. Save my last ggplot:
ggsave(“filename.png”)
ggsave(“filename.pdf”)
etc.
Can fool with size (width, height in inches, pixels, etc.)

32. ggplot2 Extensions
Extending the language

33. Overview
Extensions to ggplot2 add geometries, statistics, themes… all within the language you now know.
Dedicated website for them:
And many in development elsewhere.
Let’s look at some greatest hits

34. plotly
Minimal use? ggplotly() Can also send plots to your account online, integrate with shiny (renderPlotly and outputPlotly), etc.

35. ggrepel
Already have geom_text() and geom_label (label draws a text box, text is just text)
Now have geom_text_repel() and geom_label_repel() to use a “force” to spread out data and labels.

36. Let’s Try

37. Answers
library(plotly) ggplot(mpg, aes(y=cty, x=manufacturer))+geom_boxplot(aes(color=..middle..)) ggplotly() ggplot(mpg, aes(cty, hwy))+geom_label(aes(label=manufacturer)) library(ggrepel) ggplot(mpg, aes(cty, hwy))+geom_jitter()+geom_text(aes(label=manufacturer)) ggplot(mpg, aes(cty, hwy, color=manufacturer))+geom_jitter()+geom_text(aes(label=manufacturer), nudge_y=1) ggplot(mpg, aes(displ, cyl, color=drv))+geom_point(stat="unique")+geom_text_repel(aes(label=manufacturer), stat="unique",force=0.01)

38. ggforce https://github.com/thomasp85/ggforce
project.org/web/packages/ggforce/vignettes/Visual _Guide.html

39. ggstance
coord_flip() alternative

40. ggmosaic
master/vignettes/ggmosaic.Rmd

41. Survminer (also GGAlly::ggsurv())

42. ggridges
project.org/web/packages/ggridges/vignettes/intro duction.html

43. GGally

44. So,so many themes
ggthemes, etc.

45. ggsci
: ggsci offers a collection of ggplot2 color palettes inspired by scientific journals, data visualization libraries, science fiction movies, and TV shows

46. Special mention: broom
Broom… tidies data! Available Tidiers Currently broom provides tidying methods for many S3 objects from the built-in stats package, including lm glm htest anova nls kmeans manova TukeyHSD arima It also provides methods for S3 objects in popular third-party packages, including Lme4 glmnet boot gam survival Lfe zoo multcomp sp maps

47. Thinking big: other packages
For example, treemapify
How to install dev versions of things…

48. Thinking big: Sankey diagrams
How many ways to cut it:
key-diagrams-in-r
Good example

49. Next week: dplyr!
Highly recommend doing something this weekend about dplyr.