Grafiken in R - Grafikausgabe, von R bereitgestellte Grafikfunktionen

Vorlesung Programmieren in statistischer Software: R
Sommersemester 2009
Kapitel 4
Grafiken in R
Grafikausgabe, von R bereitgestellte Grafikfunktionen, Erweiterung von Grafiken,
Trellis Grafiken
Christian Heumann
Foliengestaltung von Martin Dörr
Inhalt dieses Abschnitts
1
Grafiken
Grafikausgabe
Von R bereitgestellte Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
Grafiken
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte Grafikfunktionen
Erweiterung von Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Trellis Grafiken
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.3
Grafikausgabe
Heumann
Die Grafikausgabe von R erfolgt in ein sogenanntes Gerät
Ein Gerät ist zum Beispiel ein Fenster auf dem Bildschirm oder eine Datei
Es stehen dabei zum Beispiel folgende Geräte zur Verfügung:
bitmap(), jpeg(), pdf(), pictex(), png(), bzw.
postscript(), xfig(), x11(), X11(), quarz().
Unter Windows(TM) gibt es auch noch bmp() und win.metafile().
Beispiel:
x11()
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
öffnet ein Grafikfenster auf dem Bildschirm und
dev.off()
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
schließt das Fenster wieder.
Trellis Grafiken
4.4
Beispiel zur Grafikausgabe: Zeichnen der Dichte der Standard–Normalverteilung
auf dem Bildschirm
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
> x11()
> curve(from=-3, to=3, dnorm(x), ylab="Dichte der N(0,1)-Verteilung")
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.5
Beispiel zur Grafikausgabe: Zeichnen der Dichte der Standard–Normalverteilung
in eine Datei
Statt auf dem Bildschirm, lassen wir uns die Grafik direkt in ein gewünschtes
Dateiformat ausgeben, zum Beispiel PDF oder Postscript.
Heumann
> pdf("dichteN01.pdf")
> curve(from=-3, to=3, dnorm(x), ylab="Dichte der N(0,1)-Verteilung")
> dev.off()
Die Datei dichteN01.pdf wird dabei im aktuellen Arbeitsverzeichnis angelegt, welches man
mit dem Befehl getwd() herausfinden kann. Sie können das Ergebnis mit dem Acrobat Reader
betrachten. Die Postscript–Version geht ganz analog:
> postscript("dichteN01.ps")
> curve(from=-3, to=3, dnorm(x), ylab="Dichte der N(0,1)-Verteilung")
> dev.off()
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
0.4
Streudiagramm
Koplots
Histogramm
0.3
Zeichnen von Funktionen
Weitere Funktionen
0.2
Erweiterung von Grafiken
−1
0
x
1
2
3
0.3
0.2
0.1
−2
0.0
−3
Dichte der N(0,1)−Verteilung
0.4
0.1
Trellis Grafiken
0.0
Dichte der N(0,1)−Verteilung
Normal–QQ–Plot
−3
−2
−1
0
x
1
2
3
4.6
Typischer Ablauf
Allgemeines Vorgehen: Erzeugen der Grafik auf dem Bildschirm, bis diese den
eigenen Wünschen entspricht, danach Ausgabe in das gewünschte Dateiformat
durch einfaches Abändern des Ausgabegeräts.
Eine Liste der aktuell geöffneten Geräte erhält man mit dev.list().
Mit dev.set() läßt sich ein Gerät für die nächsten Zeichenoperationen
auswählen.
Daneben gibt es die Befehle dev.copy() und dev.print(), siehe
Online–Hilfe.
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.7
Von R bereitgestellte Grafikfunktionen
R stellt eine Reihe von Standard–Grafikfunktionen zur Verfügung. Beispiele sind
Boxplots und Streudiagramme.
Für die folgenden Beispiele laden wir wieder den Mietspiegeldatensatz:
> daten <- read.table(file=
"http://www.statistik.lmu.de/service/datenarchiv/miete/miete03.asc",
header=TRUE
)
> attach(daten)
Öffnen Sie einen Editor (zum Beispiel Wordpad), um die eingegebenen R Befehle
speichern zu können!
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.8
Balkendiagramm
Heumann
Ein einfaches Balkendiagramm erhält man mit barplot(). Mit table() erzeugen
wir die Häufigkeitsverteilung der Variablen rooms des Datensatzes.
> table(rooms)
rooms
1
2
3
4
5
6
255 715 759 263 47 14
> barplot( table(rooms) )
Die Funktion barplot() nimmt also die Auszählung der Variablen rooms nicht
selbst vor, sondern dies muss vorher durch die Funktion table() erledigt werden.
Wie man sich in der Online–Hilfe überzeugt, können der Funktion eine Reihe von
Parametern übergeben werden. Als Beispiel schreiben wir folgenden Befehl in unseren
Editor
barplot(table(rooms),col="gray",border="blue",
main="Balkendiagramm für die Variable rooms",
xlab="Anzahl der Räume",
ylab="Absolute Häufigkeiten",
ylim=c(0,800) )
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
und bringen diesen zur Ausführung durch Kopieren und Einfügen an der R
Kommandozeile (oder durch den Befehl source(), wenn wir den Inhalt des
Editorfensters in einer Datei im aktuellen Verzeichnis abgespeichert haben).
4.9
Heumann
Beispiel Balkendiagramm: Fortsetzung
800
Balkendiagramm für die Variable rooms
Grafiken in R
600
Grafiken
Von R bereitgestellte
Grafikfunktionen
400
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
200
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
0
Absolute Häufigkeiten
Grafikausgabe
Erweiterung von Grafiken
1
2
3
4
5
6
Trellis Grafiken
Anzahl der Räume
4.10
Beispiel Balkendiagramm: Fortsetzung
Man erkennt, dass bei der Skalierung der Grafik die Schriftgröße sehr (zu) klein
werden kann. Man kann dies beispielsweise durch Änderung des globalen
Grafikparameters cex ändern (character extension)
> cex.alt <- par("cex")
> par(cex=2)
barplot(table(rooms),col="gray",border="blue",
main="Balkendiagramm für die Variable rooms",
xlab="Anzahl der Räume",
ylab="Absolute Häufigkeiten",
ylim=c(0,800) )
> par(cex=cex.alt)
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.11
Heumann
Beispiel Balkendiagramm: Fortsetzung
600
Grafiken in R
400
Grafiken
Grafikausgabe
200
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
0
Absolute Häufigkeiten
800
Balkendiagramm für die Variable rooms
Streudiagramm
1
2
3
4
5
6
Koplots
Histogramm
Anzahl der Räume
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Zu beachten ist, dass par() innerhalb der Geräteauswahl verwendet werden muss:
Trellis Grafiken
pdf("barplot2.pdf")
par(cex=2)
barplot(table(rooms),col="gray",border="blue",
main="Balkendiagramm für die Variable rooms",
xlab="Anzahl der Räume",
ylab="Absolute Häufigkeiten",
ylim=c(0,800) )
dev.off()
4.12
Heumann
Noch ein Balkendiagramm
Wir verwenden die Datei VADeaths:
VADeaths
barplot(VADeaths, beside=T, legend=T, ylim=c(0,99),
ylab="Tote pro 1000",
main="Sterberaten in Virginia 1940")
Grafiken in R
Sterberaten in Virginia 1940
Grafiken
80
50−54
55−59
60−64
65−69
70−74
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
60
Streudiagramm
Koplots
Histogramm
40
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
20
Erweiterung von Grafiken
Trellis Grafiken
0
Tote pro 1000
Gruppierter Boxplot
Rural Male
Rural Female
Urban Male
Urban Female
4.13
Heumann
Kuchendiagramm
pie(table(rooms), clockwise=T)
5 6
Grafiken in R
1
Grafiken
4
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
2
Histogramm
Normal–QQ–Plot
3
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.14
Heumann
Boxplot
Einen Boxplot kann man mit dem Befehl boxplot() erstellen. Als Beispiel erstellen
wir einen Boxplot der Variable nmqm (Nettomiete pro qm):
boxplot(nmqm, main="Boxplot der Nettomiete pro qm",
col="lightgray", border="red")
Grafiken in R
Boxplot der Nettomiete pro qm
Grafiken
20
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
15
Kuchendiagramm
Boxplot
Gruppierter Boxplot
10
Streudiagramm
Koplots
Histogramm
5
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.15
Gruppierter Boxplot
R erlaubt auch die einfache Erstellung gruppierter Boxplots. D.h. wir wollen eine
5–Punkte Zusammenfassung der Verteilung einer Variable innerhalb der Kategorie
einer zweiten (Faktor–)Variable. Mit dem folgenden Befehl erhalten wir einen Boxplot
der Nettomiete pro qm aufgeschlüsselt nach der Anzahl der Zimmer:
> boxplot(nmqm ~ rooms,
main="Nettomiete pro qm nach Anzahl der Zimmer",
xlab="Anzahl der Zimmer",
ylab="Nettomiete pro qm")+ + +
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Nettomiete pro qm nach Anzahl der Zimmer
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Boxplot
Gruppierter Boxplot
15
Streudiagramm
Koplots
Histogramm
10
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
5
Nettomiete pro qm
20
Kuchendiagramm
1
2
3
4
5
6
Anzahl der Zimmer
4.16
Heumann
Streudiagramm
Das Kommando pairs() erlaubt die einfache Erstellung einer
Streudiagramm–Matrix. Im folgenden werden die Nettomiete und die Wohnfläche in
xy–Diagrammen dargestellt:
> pairs( cbind(nm,wfl), labels=c("Nettomiete", "Wohnfläche") )
50
100
Grafiken in R
150
1500
Grafiken
Grafikausgabe
1000
Von R bereitgestellte
Grafikfunktionen
Nettomiete
Balkendiagramm
500
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
150
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
100
Wohnfläche
Erweiterung von Grafiken
50
Trellis Grafiken
500
1000
1500
4.17
Heumann
Koplots
Koplots (conditional plots) erlauben die Darstellung zweier Variablen gegeben eine
dritte oder eine dritte und eine vierte Variable. Im folgenden erhält man ein
Streudiagramm von Nettomiete und Wohnfläche getrennt für jede Ausprägung der
Anzahl der Zimmer (1 bis 6):
> coplot( nm~wfl | as.factor(rooms), panel= panel.smooth )
Given : as.factor(rooms)
Grafiken in R
Grafiken
6
Grafikausgabe
5
4
Von R bereitgestellte
Grafikfunktionen
3
2
Balkendiagramm
1
Kuchendiagramm
50
100
150
50
100
150
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
nm
Zeichnen von Funktionen
Weitere Funktionen
1500
Erweiterung von Grafiken
500
1000
Trellis Grafiken
50
100
150
wfl
4.18
Heumann
Koplots
Simultane Betrachtung von vier Variablen:
> coplot( nm~wfl | as.factor(rooms) * as.factor(badextra),
panel= panel.smooth )
Given : as.factor(rooms)
Grafiken in R
6
Grafiken
5
4
Grafikausgabe
3
Von R bereitgestellte
Grafikfunktionen
2
1
50
100
Balkendiagramm
150
50
100
150
50
100
150
Kuchendiagramm
1500
Boxplot
Gruppierter Boxplot
1
1000
Streudiagramm
Koplots
500
Histogramm
nm
Normal–QQ–Plot
Zeichnen von Funktionen
1500
Weitere Funktionen
Trellis Grafiken
500
0
1000
Erweiterung von Grafiken
50
100
150
50
100
150
50
100
150
wfl
4.19
Histogramm
Hierzu stehen die Befehle hist() und, nach Laden der MASS–Bibliothek mittels
library(MASS), die Funktion truehist() zur Verfügung. Beispiele anhand von
Nettomiete pro qm und Anzahl der Zimmer:
par( mfrow=c(2,2) )
hist(nmqm)
truehist(nmqm)
hist(rooms)
truehist(rooms)
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Histogram of nmqm
0.15
Boxplot
0.10
500
Kuchendiagramm
300
Gruppierter Boxplot
0.05
Streudiagramm
Koplots
100
Frequency
Balkendiagramm
Histogramm
0.00
0
0
5
10
15
20
5
10
15
20
Normal–QQ–Plot
Zeichnen von Funktionen
nmqm
nmqm
Weitere Funktionen
Erweiterung von Grafiken
Histogram of rooms
1.0
400
0.0
0.5
200
0
Frequency
600
1.5
Trellis Grafiken
1
2
3
4
rooms
5
6
1
2
3
4
rooms
5
6
4.20
Heumann
Normal–QQ-Plot
#
n
x
y
z
w
Daten
<- 200
<- rnorm(n=n)
<- rt(n=n, df=6)
<- rt(n=n, df=2)
<- exp(rnorm(n=n))
# Referenzverteilung ist Normalverteilung
par( mfrow=c(2,2) )
qqnorm(x)
qqnorm(y)
qqnorm(z)
qqnorm(w)
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Normal Q−Q Plot
4
2
0
Sample Quantiles
−6
2
1
0
−1
Sample Quantiles
−2
●
Boxplot
●
Gruppierter Boxplot
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Normal Q−Q Plot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
●
Weitere Funktionen
−3
−2
−1
0
1
2
3
−3
−2
−1
0
1
2
3
Erweiterung von Grafiken
Theoretical Quantiles
Theoretical Quantiles
Normal Q−Q Plot
Normal Q−Q Plot
Trellis Grafiken
−2
−1
0
1
2
3
10
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Sample Quantiles
20
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−60 −40 −20
Sample Quantiles
40
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−3
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1
2
3
4.21
Heumann
Zeichnen von Funktionen
Die Funktion curve() haben wir bereits kennengelernt. Sie erlaubt das Zeichnen von
Funktionen. Beispiel:
curve(x^4, from=-1, to=1, col="blue",
ylab=expression(paste("Blau: ", x^4, " rot: ", x^2)) )
curve(x^2, from=-1, to=1, add=TRUE, col="red" )
Grafiken in R
Grafiken
Grafikausgabe
0.0 0.2 0.4 0.6 0.8 1.0
Blau: x4 rot: x2
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
−1.0
−0.5
0.0
0.5
1.0
x
4.22
Weitere Funktionen
contour() für Höhenlinien
dotchart() für sog. Dotcharts (Ersatz für Balkendiagramme)
image(), Bilder, mit Farben als dritter Dimension
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
mosaicplot(), Mosaikgrafiken zur (mehrdimensinalen) Darstellung
kategorialer Variablen (Kontingenztafeln)
Balkendiagramm
persp(), perspektivische Oberflächen über der xy–Ebene
Gruppierter Boxplot
Kuchendiagramm
Boxplot
Streudiagramm
qqplot(), allgemeiner QQ–Plot
scatterplot3d() im Zusatzpaket scatterplot3d
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.23
Beispiel: Dichte der bivariaten Normalverteilung
Wir nehmen an: µ = (0, 0)0 und σ12 = σ22 = 1 und ρ = 0. Im folgenden erzeugen wir
ein Gitter der xy–Ebene, anschliessend wird die Dichte der bivariaten
Normalverteilung (dmvnorm()) an jeder Stelle des Gitters ausgewertet.
library(mvtnorm)
x <- seq(from=-2, to=2, by=0.1)
y <- x
z <- matrix(nrow=length(x), ncol=length(y), data=0 )
for ( i in 1:nrow(z) ) for ( j in 1:ncol(z) )
z[i,j] <- dmvnorm( cbind( x[i], y[j] ) )
image(x,y,z)
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
2
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
1
Koplots
Histogramm
Normal–QQ–Plot
0
Weitere Funktionen
Erweiterung von Grafiken
−1
Trellis Grafiken
−2
y
Zeichnen von Funktionen
−2
−1
0
1
2
x
4.24
Beispiel Fortsetzung: Dichte der bivariaten Normalverteilung
Heumann
contour(x,y,z)
2
Grafiken in R
0.02
0.02
Grafiken
0.04
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
1
0.08
0.1
Balkendiagramm
0.12
Kuchendiagramm
Boxplot
0
Gruppierter Boxplot
Streudiagramm
0.14
Koplots
−1
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
0.06
−2
Weitere Funktionen
0.02
Erweiterung von Grafiken
0.02
Trellis Grafiken
−2
−1
0
1
2
4.25
Beispiel Fortsetzung: Dichte der bivariaten Normalverteilung
Heumann
persp(x, y, z, theta = 30, phi = 30, expand = 0.5, col = "lightblue")
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
z
Boxplot
Gruppierter Boxplot
Streudiagramm
y
Koplots
Histogramm
Normal–QQ–Plot
x
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.26
Erweiterung von Grafiken
Heumann
Es gibt eine große Zahl von Parametern
Die Erklärung jedes einzelne Parameters würde den Rahmen dieses Kurses
sprengen
Der Befehl par() ohne Argumente liefert eine Übersicht über alle
Grafikparameter und ihre Voreinstellung
Die Parameter von par() können verändert werden. Wir haben bereits
kennengelernt: par(cex=2) für eine global größere Schrift und
par( mfrow=c(2,2) ), um 4 Grafiken in einem Gerät in der Anordnung
einer 2×2–Matrix zu plotten (multi figure).
Nützliche Befehle sind zum Beispiel
points() und lines()
axis() zur Veränderung der Achsenbeschriftungen
legend() zum Anbringen von Legenden
Innerhalb der Grafikfunktionen: xlim, ylim zur Festlegung der Skala
arrows() zum Zeichnen von Pfeilen
text() und mtext() zum Beschriften außerhalb und innerhalb der Grafik
···
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.27
Beispiel einer selbstgebauten Grafik
Heumann
Die Ausführung sollte schrittweise geschehen, um jeweils den Effekt jedes einzelnen
Befehls auf die Grafik zu erkennen.
par(cex=2)
par(las=1)
x <- seq(from=-1, to=1, by=0.01)
y1<- x^2
y2<- x^4
matplot(x,y1, type="l",
axes=FALSE,
main="Beispiel",
xlab="x",
ylab=expression(paste("Schwarz: ", x^2, " rot: ", x^4)) )
matlines(x,y2, type="l", col=2)
axis(1, at=c(-1, 0, 1), labels=c("-1.0", "0.0", "1.0" ),
col = "gold", lty = 1, lwd = 2 )
axis(2, at=c(0, 0.5, 1.0), labels=c("0.0", "0.5", "1.0" ),
col = "blue", lty = 1, lwd = 2 )
legend(-0.5, 0.75,
legend=c(expression(paste("y=",x^2)),
expression(paste("y=",x^4))
),
col=c("black", "red"),
lwd=2
)
box()
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
Das Ergebnis ist die folgende Grafik:
4.28
Heumann
Beispiel einer selbstgebauten Grafik
Schwarz: x2 rot: x4
Beispiel
1.0
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
2
y=x
y=x4
0.5
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
0.0
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
−1.0
0.0
1.0
x
4.29
Heumann
Beispiel einer erweiterten Grafik
n <- 100
x <- runif(n=n)
a <- 3
b <- 2
y <- a + b*x + rnorm(n=n, mean=0, sd=0.1)
plot(x,y)
abline(a=a,b=b)
abline(h=mean(y))
abline(v=mean(x))
mtext(paste("Mittelwert von x"), side=1, at=mean(x) )
mtext(paste("Mittelwert von y"), side=2, at=mean(y) )
text(0.2,4.5, "Wahre Regressionsgerade", pos=4)
arrows(0.4, 4.4, 0.6, 4.2)
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
5.0
Gruppierter Boxplot
●
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Trellis Grafiken
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4.30
Trellis Grafiken
Heumann
Die sogenannten Trellis–Grafiken (Cleveland, 1993) stehen nach Eingabe von
Grafiken in R
library(lattice)
Grafiken
Grafikausgabe
zur Verfügung. Die Initialisierung erfolgt durch
trellis.device()
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
bzw. durch
trellis.device(file="trellis1.pdf", device="pdf")
wenn eine Dateiausgabe gewünscht wird. Es sind dann folgende Standard–Grafiken
zur Verfügung:
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.31
Übersicht über Trellis–Grafiken, vgl. Ligges, U., p.167
barchart()
bwplot()
cloud()
contourplot()
densityplot()
dotplot()
histogram()
levelplot()
piechart()
qq()
splom()
wireframe()
xyplot()
Balkendiagramm
Boxplot
Punktwolke (3D)
Höhenlinien
Kerndichteschätzer
Punktegrafiken
Histogramm
Levelgrafiken
Kuchendiagramm
QQ–Plots
Streudiagramme
3D–Flächen
Allgemeine Zeichenfunktion
Heumann
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
4.32
Heumann
Beispiel 1 einer Trellis–Grafik
xyplot(nm~wfl | as.factor(rooms),
main="Nettomiete versus Wohnfläche gegen Anzahl Zimmer" )
Nettomiete versus Wohnfläche gegen Anzahl Zimmer
50
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Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
0
50
100
150
50
100
150
wfl
4.33
Heumann
Beispiel 2 einer Trellis–Grafik
xyplot(
nm~wfl | as.factor(rooms) * as.factor(badextra) )
50 100150
1
1
1
2
50 100150
1
3
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4
50 100150
1
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1500
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Grafikausgabe
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Grafiken
1000
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
●
500
●
Kuchendiagramm
Boxplot
Gruppierter Boxplot
0
nm
0
1
0
2
0
3
0
4
0
5
0
6
1500
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1000
500
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Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
Erweiterung von Grafiken
● ●● ●
●
●
Trellis Grafiken
0
50 100150
50 100150
50 100150
wfl
4.34
Heumann
Beispiel 3 einer Trellis–Grafik
splom( cbind(nm,nmqm,wfl) )
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Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
100
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
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Weitere Funktionen
Erweiterung von Grafiken
Trellis Grafiken
Scatter Plot Matrix
4.35
Heumann
Beispiel 3a einer Trellis–Grafik
super.sym <- trellis.par.get("superpose.symbol")
trellis.device()
#trellis.device(file="trellis3a.pdf", device="pdf", color=TRUE)
splom( ~cbind(nm,wfl, nmqm),
groups=rooms,
key=list(
columns=6,
points=list(pch = super.sym$pch[1:6],
col = super.sym$col[1:6]
),
text=list(c("1","2","3","4","5","6"))
)
)
#dev.off()
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
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Erweiterung von Grafiken
Trellis Grafiken
●
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Scatter Plot Matrix
4.36
Beispiel 4 einer Trellis–Grafik aus der Online–Hilfe
Heumann
data(volcano) ## 87 x 61 matrix
wireframe(volcano, shade = TRUE,
aspect = c(61/87, 0.4),
light.source = c(10,0,10))
Grafiken in R
Grafiken
Grafikausgabe
Von R bereitgestellte
Grafikfunktionen
Balkendiagramm
Kuchendiagramm
Boxplot
Gruppierter Boxplot
Streudiagramm
Koplots
volcano
Histogramm
Normal–QQ–Plot
Zeichnen von Funktionen
Weitere Funktionen
row
column
Erweiterung von Grafiken
Trellis Grafiken
4.37