This document summarizes a brown-bag seminar on introducing R and data visualization. It covers loading and exploring data; basic data types and data frames; performing operations and asking questions of the data; subsetting, filtering, and handling duplicates and missing values; basic statistical analysis and graphs; and using the ggplot2 package to create bar plots, scatter plots, line graphs, box plots and more to visualize relationships in the data. Key points covered include using geom_bar with stat="bin", adding colors and facets, setting linetype and point shapes, and layering geoms to overlay points and lines on the same plot.

1. R Brown-bag seminarR Brown-bag seminar
Session 8Session 8

2. Summary

Introduction

Data Import (csv, txt ...)

Data

Types

Data-frames

Question

(sapply(tree,class) --ref(1) )

Basic Operations

Help

Summery

Subset and Filter

Duplicates and NA

Basic analysis/stats

Graphs

Default package

ggplot

How many have installed ggplot2 package
Ref.
1) http://www.statmethods.net/input/datatypes.html

3. Learn to Code
&
Code to Learn

5. Tree <- read.table("datavis.csv",sep=",",header=T)
?separator ?Yes file has a Header
library(ggplot2)
RStudio
File → New File → R Script

6. ggplot(data=tree, aes(x=PosTopoSeq)) + geom_bar(stat="bin")
? ? ?
Geometry = bar
statistical transformation = bin
bin = number of cases in group
Data frame Field on x

7. ggplot(data=tree, aes(x=VegStructure)) + geom_bar(stat="bin")
WOW!
Shrubland

8. Some colours please
ggplot(data=tree, aes(x=VegStructure,colour=Site)) + geom_bar(stat="bin")
?Different colours for each site

9. ggplot(data=tree, aes(x=VegStructure,fill=Site)) + geom_bar(stat="bin")
Fill geometry
Veg. Structure = Shrubland
is in all sites
&
Site 1 is richest
in terms of
Veg. Structure

10. Question: Confirm that Shrubland is present in every site
ggplot(data=tree) + geom_boxplot(aes(Site,avTreeDen,col=Site))+
coord_flip() + facet_wrap(~VegStructure,ncol=1)
Yes
Veg. Structure = Shrubland
is in all sites

11. ggplot(data=tree) + geom_point(aes(x=Carbon,y=Clay))

12. ggplot(data=tree,aes(x=Carbon,y=Clay))+geom_line() + geom_point()

13. ggplot(data=tree,aes(x=Carbon,y=Clay)) +
geom_line(colour="red", linetype="dashed", size=0.5) +
geom_point(colour="red", size=2, shape=22, fill="red")
? linetype
0 = blank, 1 = solid, 2 = dashed, 3 = dotted, 4 = dotdash, 5 = longdash, 6 =
twodash

14. what is shape = 25

15. ggplot(data=tree)+geom_point(aes(x=Carbon,y=Clay,col=Site))

16. ggplot(data=tree)+geom_line(aes(x=Carbon,y=Clay,col=Site))

17. gg <- ggplot() + geom_point(data=tree,aes(x=Carbon,y=Clay,col=Site)) +
geom_line(data=tree,aes(x=Carbon,y=Clay,col=Site))
plot(gg)

18. ggplot(data=tree) + geom_boxplot(aes(Site, pH))
ggplot(data=tree) + geom_boxplot(aes(Site, Clay))
ggplot(data=tree) + geom_boxplot(aes(Site, Carbon))

19. What we have done today?
Coding
landscape portal example

20. Assignment

Write a program
− Load data
− Show stats
− Make graphs
− Explain graphs

21. End