The following data objects are usually the inputs in R plots:

• vectors
• matrices
• data frames

# vector 
a<-c(1,2,3,4,5)
a

## [1] 1 2 3 4 5

is.vector(a)

## [1] TRUE

let<-letters[1:5]
let

## [1] "a" "b" "c" "d" "e"

either numbers or characters

#matrix
b<-cbind(a,a,a,a)

b

##      a a a a
## [1,] 1 1 1 1
## [2,] 2 2 2 2
## [3,] 3 3 3 3
## [4,] 4 4 4 4
## [5,] 5 5 5 5

is.matrix(b)

## [1] TRUE

numbers and characters

#matrix
c<-data.frame(a,a,a,a,let)

c

##   a a.1 a.2 a.3 let
## 1 1   1   1   1   a
## 2 2   2   2   2   b
## 3 3   3   3   3   c
## 4 4   4   4   4   d
## 5 5   5   5   5   e

is.data.frame(c)

## [1] TRUE

Graph the number of males per lek

males <- c(5, 4, 6, 4, 9) # males per lek

plot(males)

Let's add a title, a line to connect the points, and some color:

plot(males, type="o", col="blue")#blue points overlayed by a line 
title(main="Males per lek", col.main="red", font.main=4) # title red, bold/italic font

Now let's add a red line for females and specify the y-axis range directly so it will be large enough to fit the female data:

# Define 2nd vector
females <- c(2, 5, 4, 5, 12) 

# Graph y axis that ranges from 0 to 12
plot(males, type="o", col="blue", ylim=c(0,12))

# females red dashed line and square points
lines(females, type="o", pch=22, lty=2, col="red") 

# title red, bold/italic font
title(main="Males & females per lek", col.main="red", font.main=4) 

Now let's add a red line for females and specify the y-axis range directly so it will be large enough to fit the female data:

Next let's change the axes labels to match our data and add a legend

# Calculate range from 0 to max value of males and females
g_range <- range(0, females, males)

#Turn off axes and annotations (axis labels) so we can specify them ourself
plot(males, type="o", col="blue", ylim=g_range, 
   axes=FALSE, ann=FALSE)

Next let's change the axes labels to match our data and add a legend

Add the axis and box

plot(males, type="o", col="blue", ylim=g_range, 
   axes=FALSE, ann=FALSE)

# Make x axis using lek labels
axis(1, at=1:5, lab=c("CCL","STR","SAT","SJA","SUR"))

# Make y axis with horizontal labels that display ticks at 
# every 4 marks. 4*0:g_range[2] is equivalent to c(0,4,8,12).
axis(2, las=1, at=4*0:g_range[2])

# Create box around plot
box()

Add the axis and box

Add the data, title and legend

plot(males, type="o", col="blue", ylim=g_range, 
   axes=FALSE, ann=FALSE)
axis(1, at=1:5, lab=c("CCL","STR","SAT","SJA","SUR"))
axis(2, las=1, at=4*0:g_range[2])
box()

# Graph females with red dashed line and square points
lines(females, type="o", pch=22, lty=2, col="red")

# Create a title with a red, bold/italic font
title(main="Males and females in leks", col.main="red", font.main=4)

title(xlab="Leks", col.lab=rgb(0,0.5,0))
title(ylab="Total", col.lab=rgb(0,0.5,0))

legend(1, g_range[2], c("males","females"), cex=0.8, 
   col=c("blue","red"), pch=21:22, lty=1:2);

Add the data, title and legend

Bar graph of male data

barplot(males)

Graph males with specified labels for axes.

barplot(males, main="Males", xlab="Leks", ylab="Total", names.arg=c("CCL","STR","SAT","SJA","SUR"), 
  border="blue", density=c(10,20,30,40,50))

Now let's graph the total number of birds per lek using some color and show a legend:

hummers<-cbind(males,females,juve=c(4,4,6,6,16))

barplot(hummers, main="Hummingbirds", ylab= "Total",
   beside=TRUE, col=rainbow(5))

# Place the legend at the top-left corner with no frame  
legend("topleft", c("CCL","STR","SAT","SJA","SUR"), cex=0.6, 
   bty="n", fill=rainbow(5))

Now let's graph the total number of birds per day using some color and show a legend:

For showing data distribution and normality

# Get a random log-normal distribution
r <- rnorm(1000,5)

hist(r,col="skyblue")

For showing proportions

pie(males)

Add legend

pie(males, main="Males", col=rainbow(length(males)),
   labels=c("CCL","STR","SAT","SJA","SUR"))

Create a colored dotchart for age classes by lek

dotchart(t(hummers), color=c("red","blue","darkgreen"),
   main="Dotchart for hummingbirds", cex=0.8)

Different symbols

plot(1, 1, xlim=c(1,5.5), ylim=c(0,7), type="n", ann=FALSE) # Make an empty chart
text(1:5, rep(6,5), labels=c(0:4), cex=1:5, col=1:5)# Plot digits 0-4 with increasing size/color

points(1:5, rep(5,5), cex=1:5, col=1:5, pch=0:4)# Plot symbols 0-4 with increasing size/color
text((1:5)+0.4, rep(5,5), cex=0.6, (0:4))

points(1:5, rep(4,5), cex=2, pch=(5:9))# Plot symbols 5-9 with labels
text((1:5)+0.4, rep(4,5), cex=0.6, (5:9))

points(1:5, rep(3,5), cex=2, pch=(10:14))# Plot symbols 10-14 with labels
text((1:5)+0.4, rep(3,5), cex=0.6, (10:14))

points(1:5, rep(2,5), cex=2, pch=(15:19))# Plot symbols 15-19 with labels
text((1:5)+0.4, rep(2,5), cex=0.6, (15:19))

points((1:6)*0.8+0.2, rep(1,6), cex=2, pch=(20:25)) # Plot symbols 20-25 with labels
text((1:6)*0.8+0.5, rep(1,6), cex=0.6, (20:25))

On hummingbird data

class<-c(rep("male",5),rep("female",5),rep("juvenile",5))
humm.df<-data.frame(class,total=c(males, females, c(4,4,6,6,16)),
                    Leks= rep(c("CCL","STR","SAT","SJA","SUR"),3))

boxplot(total~class,data = humm.df)

On random data

Changing color and orientation

humm.df2<-data.frame(class,total=c(rnorm(5,1,1), rnorm(5,3,2), rnorm(5,3,1)),Leks= rep(c("CCL","STR","SAT","SJA","SUR"),3))

boxplot(total~class,data = humm.df2,col="yellow4",horizontal = T)

Changing color and orientation

# height of president divided by height of most successful opponent: 
body.size <- c(3.745756, 1.725416, 3.905743, 6.216381, 4.516818, 5.049753, 
               4.922817, 4.961822, 6.387712, 6.360082, 3.673467, 6.403956, 
               3.360937, 4.721525, 5.963445, 5.648205, 4.250537, 4.581020, 
               6.081036, 5.994140, 3.883612, 4.457508, 1.892721, 3.409522,
               5.053790, 3.896708, 6.422167, 4.993130, 2.226273, 6.255924, 
               4.098446, 2.568278, 3.914492, 6.052945, 3.985166, 2.329352, 
               2.622594, 2.034283, 5.583006, 3.434656, 4.476129, 4.466925, 
               4.490384, 3.497488, 4.974221, 5.177449, 4.735471, 5.836074, 
               5.886631, 6.510843)

#Bill length in long-billed hermits
frequency <- c(6.455821, 5.139507, 6.108490, 8.623173, 6.710728, 8.029906, 
               7.469104, 6.906462, 8.603421, 7.284242, 5.979938, 7.143694, 
               6.096457, 5.999354, 7.850083, 7.785403, 5.907416, 7.901530, 
               7.937979, 7.114081, 6.179503, 7.143809, 6.380096, 6.769819, 
               7.385331, 6.539280, 8.525748, 7.068429, 6.181722, 7.508457, 
               7.860184, 5.886500, 5.968909, 8.239845, 6.530752, 5.949638, 
               4.630713, 5.908844, 7.291094, 6.046808, 6.816406, 6.908434, 
               6.724284, 4.804671, 8.942853, 6.950045, 7.461648, 7.487176,
               7.943633, 7.275438)

plot(body.size, frequency, col="black", pch=21, bg = "grey", cex = 2,
      ylab="", xlab="", axes=F)
axis(1)
axis(2) 
reg1 <- lm(frequency~body.size)
abline(reg1, lwd=2) 
par(las=0)
mtext("Body size (g)", side=1, line=2.5, cex=1.5)
mtext("Frequency (kHz)", side=2, line=2.2, cex=1.5)
text(3, 8, "r = .58", cex=1.5)

def.par <- par(no.readonly = TRUE)
xhist <- hist(body.size, plot = FALSE)
yhist <- hist(frequency, plot = FALSE)
top <- max(c(xhist$counts, yhist$counts))

nf <- layout(matrix(c(2,0,1,3),2,2,byrow = TRUE), c(3,1), c(1,3), TRUE)
layout.show(nf)

 layout(matrix(c(2, 0, 1, 3),2, 2, byrow = TRUE), c(3,1), c(1,3), TRUE)
par(mar = c(3,3,1,1))
plot(body.size, frequency,  pch = 20, cex = 2)
par(mar = c(0,3,1,1))
barplot(xhist$counts, axes = FALSE, ylim = c(0, top), space = 0)
par(mar = c(3,0,1,1))
barplot(yhist$counts, axes = FALSE, xlim = c(0, top), space = 0,
        horiz = TRUE)
par(def.par)

Example with regression plot

# dev.off()
setwd("~/Desktop")
jpeg("reg plot.jpeg")
plot(body.size, frequency, col="black", pch=21, bg = "grey", cex = 2,
      ylab="", xlab="", axes=F)
axis(1)
axis(2) 
reg1 <- lm(frequency~body.size)
abline(reg1, lwd=2) 
par(las=0)
mtext("Body size (g)", side=1, line=2.5, cex=1.5)
mtext("Frequency (kHz)", side=2, line=3.7, cex=1.5)
text(3, 8, "r = .58", cex=1.5)
# dev.off()

Plots can be saved in other formats with these functions:

• tiff()

• png()

• pdf()