Part IV: ggplot2 Introduction

part4.r

## Title: ggplot2 Introduction: Part IV
## Description: This line by line analysis, provides an introduction to ggplot2. Time series.
## Created by: Brandon Bertelsen: Research Manager, Credo Consulting Inc.

# Review the economics data set from the ggplot2 intro
e <- economics
str(e)

# Let's look at geom_line
ggplot(e, aes(date, uempmed)) + geom_line() 

# Let's look at changes in savings rate and unemployment over time. 
ggplot(e, aes(date, uempmed)) + geom_line() + geom_line(aes(date,psavert))

# We should probably add some color
ggplot(e, aes(date, uempmed)) + geom_line(color="Red") + geom_line(color="Blue", aes(date,psavert))

# We can fake a legend, but it's not the best option. To create it properly, we must reformat the data
ggplot(e, aes(date, uempmed, color="Rate")) + geom_line(aes(color="Unemployment")) + geom_line(data=e, aes(date, psavert, color="Savings"))

# Melting
e.melt <- melt(e, id.vars="date")
head(e.melt)
e.melt <- subset(e.melt, variable == c("uempmed","psavert"))
str(e.melt)
# Are we missing anything? Don't forget droplevels()
e.melt <- droplevels(e.melt)

ggplot(e.melt, aes(date, value, color=variable)) + geom_line()

# Smoothing
ggplot(e, aes(date, uempmed)) + geom_line() + geom_smooth()