SLIDE 1
Making Pretty Pictures with ggplot2 Drew Conway December 3, 2009 - - PowerPoint PPT Presentation
Making Pretty Pictures with ggplot2 Drew Conway December 3, 2009 - - PowerPoint PPT Presentation
Making Pretty Pictures with ggplot2 Drew Conway December 3, 2009 Types of Plots Well Cover Scatter Plots Identifying key actors in #rstats network Tipping: Women vs. Men Time-Series Closing Price of Four Major European Stock
SLIDE 2
SLIDE 3
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources Key Actor Analysis Tipping by Sex
Identifying key actors in #rstats network
Last month I presented the SNA in R talk to the Bay Area R Meetup
◮ As part of this presentation I generated the online social network of people
- n Twitter discussing R by mining the #rstats hash-tag
◮ As before, I used ggplot2 to generate a plot that highlights key actors in
the network
> # Load ggplot2 library > library(ggplot2) > # Load in centrality data > rstats.cent<-read.csv("rstats_centrality.csv") > # Calculate residuals for simple OLS of eig~bet > rstats.res<-as.vector(lm(eig~bet,data=rstats.cent)$residuals) > rstats.cent<-transform(rstats.cent,res=rstats.res) > # Create plot > cent.plot<-ggplot(rstats.cent,aes(x=bet,y=eig,label=name,colour=res, + size=abs(res)))+xlab("Betweenness Centrality")+ylab("Eigenvector + Centrality") > cent.plot<-cent.plot+geom_text()+opts(title="Key Actor Analysis for #rstats")
Drew Conway Making Pretty Pictures with ggplot2
SLIDE 4 google
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources Key Actor Analysis Tipping by Sex
Key Actor Plot of #rstats Social Network
This plot will look familiar to those that attended my SNA in R talk in August!
Key Actor Analysis for #rstats
Betweenness Centrality Eigenvector Centrality
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tweetblockerapp marissamayer PageInNYC lizstrauss MarkHornick NYTimesDowd nytimesbits eldon tonyrobbins nytimesscience stevenbjohnson itconversations longreads markoff rushkoff jennyholzer waltmossberg leolaporte briansolis arrington pomeranian99 Richard_Dawkins dannysullivan louisgray chasemurdock
5000 10000 15000 20000 res
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0.6 Drew Conway Making Pretty Pictures with ggplot2
SLIDE 5
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources Key Actor Analysis Tipping by Sex
Tipping: Women vs. Men
Using the pre-loaded data tips we will create a simple comparative scatter plot
- f total bill amount vs. the subsequent tip paid by both women and men.
> # Create plot > tip.bysex<-ggplot(tips,aes(total_bill))+ + geom_point(aes(y=tip,colour=tip/total_bill))+xlab("Total Bill Amount")+ + ylab("Tip")+facet_wrap(~sex,ncol=2) > tip.bysex<-tip.bysex+opts(title="Tipping: Women vs. Men")
◮ By using the facet_wrap() we will have two plots in a single chart; each
corresponding to the tipping data for women and men respectively
◮ By setting colour=tip/total_bill the plot will highlight which sex contains
more “outlier tippers”
Drew Conway Making Pretty Pictures with ggplot2
SLIDE 6
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources Key Actor Analysis Tipping by Sex
Plot of Tipping Trends by Sex
Tipping: Women vs. Men
Total Bill Amount Tip
2 4 6 8 10 Female
- 10
20 30 40 50 Male
- ●
- ●
- 10
20 30 40 50 tip/total_bill
- 0.1
- 0.2
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- 0.4
- 0.5
- 0.6
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Drew Conway Making Pretty Pictures with ggplot2
SLIDE 7
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources Major EU Stock Indices Driver Fatalities in the U.K. and Seatbelt Law
Plotting the Daily Closing Price of Four Major EU Stock Indices
Using the base datasets package we will plot the daily closing price of the DAX, SMI, CAC and FTSE from 1991 through 1998
◮ This data set is a ts object, so we must first convert it to a data frame
with a time vector
> # Create data frame and add time vector > eu<-data.frame(EuStockMarkets) > eu<-transform(eu,time=time(EuStockMarkets)) > # Create base plot object > eu.plot<-ggplot(eu,aes(time))
◮ Now add the stock price data and appropriate legend
> # Add stock price data > eu.plot<-eu.plot+geom_line(aes(y=DAX,colour="DAX"))+ + geom_line(aes(y=SMI,colour="SMI")) > eu.plot<-eu.plot+geom_line(aes(y=CAC,color="CAC"))+ + geom_line(aes(y=FTSE,colour="FTSE")) > # Create title and legend > eu.plot<-eu.plot+opts(title="Daily closing stock prices of + Major EU Stock Indices")+xlab("Year")+ylab("Closing Price") > eu.plot<-eu.plot+scale_colour_manual(name="Indices", + values=c("DAX"="black","SMI"="blue","CAC"="red","FTSE"="green"))
Drew Conway Making Pretty Pictures with ggplot2
SLIDE 8
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources Major EU Stock Indices Driver Fatalities in the U.K. and Seatbelt Law
Plot of Closing Price for Major EU Stock Indices
Daily closing stock prices of Major EU Stock Indices
Year Closing Price
2000 3000 4000 5000 6000 7000 8000 1992 1993 1994 1995 1996 1997 1998 Indices DAX SMI CAC FTSE Drew Conway Making Pretty Pictures with ggplot2
SLIDE 9
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources Major EU Stock Indices Driver Fatalities in the U.K. and Seatbelt Law
What Impact did Seatbelt Laws have on Driver Fatalities in the UK?
Using the Seatbelts dataset we will attempt to visualize the impact of seatbelt legislation on driver deaths in the UK
◮ The data contains monthly fatality data from 1969-1984 with a dummy
variable for the month/year the seatbelt law went into effect
◮ Automobile accidents will likely have a seasonal component, so we will also
want to examine the data on a month-by-basis
> # Create data frame from ts object and add year/month data > seatbelts.data<-as.data.frame(Seatbelts) > seatbelts.data<-transform(seatbelts.data,year=floor(as.vector(time(Seatbelts))) + month=(rep(1:12,nrow(seatbelts.data/12)))) > # Create a plot that shows seasonality of accidents as well as effect of law > driver.plot<-ggplot(seatbelts.data,aes(year,DriversKilled, + colour=law))+geom_line()+xlab("Year")+ylab("Drivers + Killed")+facet_wrap(~month,ncol=6) > driver.plot<-driver.plot+opts(title="Drivers Fatalities in U.K. + by Month from 1969-1984")
Drew Conway Making Pretty Pictures with ggplot2
SLIDE 10
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources Major EU Stock Indices Driver Fatalities in the U.K. and Seatbelt Law
Drivers Fatalities in U.K. by Month from 1969-1984
Drivers Fatalities in U.K. by Month from 1969−1984
Year Drivers Killed
60 80 100 120 140 160 180 60 80 100 120 140 160 180 1 7 1970 1972 1974 1976 1978 1980 1982 1984 2 8 1970 1972 1974 1976 1978 1980 1982 1984 3 9 1970 1972 1974 1976 1978 1980 1982 1984 4 10 1970 1972 1974 1976 1978 1980 1982 1984 5 11 1970 1972 1974 1976 1978 1980 1982 1984 6 12 1970 1972 1974 1976 1978 1980 1982 1984 law 0.2 0.4 0.6 0.8 1 Drew Conway Making Pretty Pictures with ggplot2
SLIDE 11
Introduction Scatter Plots Time Series Plots Other Examples and Online Resources
Additional Resources
Learning R Blog
http://learnr.wordpress.com/
An outstanding resource for examples
- f how to use ggplot2 for several
plotting tasks ◮
Some of the most useful posts are the many side-by-side comparisons of lattice and ggplot2
gcsescore Percent of Total 10 20 30 2 4 6 8 2 2 4 6 8 4 6 2 4 6 8 8 10 20 30 10 gcsescore count 500 1000 1500 2000 500 1000 1500 2000 6 2 4 6 8 2 8 2 4 6 8 4 10 2 4 6 8
Hadley’s Resources
http://had.co.nz/ggplot2/
The developer has numerous resources and examples on his website ◮
The reference manual > data(movies) > m <- ggplot(movies, aes(x = rating)) > m <- m + geom_histogram()
rating count 1000 2000 3000 4000 5000 6000 2 4 6 8 10
◮
The ggplot2 book ◮ Mastering the grammar of graphics ◮ Building up a plot layer by layer ◮ A toolbox of techniques ◮ Scales, axes and legends ◮ Positioning ◮ Manipulating data
REvolution Computing Blog
http://blog.revolution-computing.com/
Choropleth Challenge ◮
Plotting the US unemployment data
- n a color-coded map
Promoting open government in Brazil ◮
DC R hacker Eduardo Leoni uses ggplot2 at CongressoAberto.com.br Drew Conway Making Pretty Pictures with ggplot2