-A scatterplot consists of an X axis (the horizontal axis), a Y axis (the vertical axis), and a series of dots. Each dot on the scatterplot represents one observation from a data set. The position of the dot on the scatterplot represents its X and Y values.

plot function

• ?plot

• Syntax

plot(x, y, type = , xlab = , ylab = , xlim = ,ylim = , col = , main = , ...)

Arguments

• x, y
  • provide the x and y coordinates for the plot.
• type
  • "p": points;
  • "l": lines;
  • "b": both points and lines;
  • "c": empty points joined by lines;
  • "o": overplotted points and lines;
  • "s" and "S": stair steps;
  • "h": histogram-like vertical lines.
• main
  • an overall title for the plot
• sub
  • a sub title for the plot
• xlab
  • a title for the x axis
• ylab
  • a title for the y axis
• xlim
  • range of x axis
• ylim
  • range of y axis
• …

Examples:

par(mfrow=c(2,2))  ##  multiple graphs on the same page par(mfrow = c(nrows, ncols))
plot(cars$speed,cars$dist)
plot(cars$speed,cars$dist,col="red")
plot(cars$speed,cars$dist, xlab = "speed", ylab="stopping distance", main="speed vs distance")
plot(cars$speed,cars$dist, xlab = "speed", ylab="stopping distance", main="speed vs distance",xlim = c(0,50),ylim=c(0,200),sub="Here is a subtitle")

• The different plot types

x <- 0:12
y <- sin(pi/5 * x)
op <- par(mfrow = c(3,3), mar = .1+ c(2,2,3,1))
for (tp in c("p","l","b",  "c","o","h",  "s","S","n")) {
   plot(y ~ x, type = tp, main = paste0("plot(*, type = \"", tp, "\")"))
   if(tp == "S") {
      lines(x, y, type = "s", col = "red", lty = 2)
      mtext("lines(*, type = \"s\", ...)", col = "red", cex = 0.8)
   }
}

• pch , lty

• A bar graph of a qualitative data sample consists of vertical parallel bars that shows the frequency distribution graphically.

• Syntax

barplot(height, width = , space = , names.arg = , main=, xlab = ,ylab=,...)

Arguments

• height : either a vector or matrix of values describing the bars which make up the plot.
• width : bar widths
• names.arg : a vector of names to be plotted below each bar or group of bars.
• beside : a logical value.If FALSE, stached bars; if TRUE, bars are drawn horizontally
• main, xlab, ylab, xlim, sub, col…
• ?barplot

-Example

data = c("a","b","a","c","a","b","c","c","c","c")
counts = table(data)
counts

## data
## a b c 
## 3 2 5

barplot(counts) 

barplot(counts,width=c(3,2,1), names.arg=c("apple","orange","pear"),col=c("red","orange","yellow"))

• When height argument is a matrix

data = matrix(1:9,3,3)
colnames(data) = c("apple","orange","pear")
rownames(data) = c("big","medium","small")
data

##        apple orange pear
## big        1      4    7
## medium     2      5    8
## small      3      6    9

barplot(data, beside = F,main="Stacked", legend.text = T,args.legend = list(x = "topleft"),col=c("red","orange","yellow"))

barplot(data, beside = T, main = "Side by side",legend.text = T,args.legend = list(x = "topleft"),col=c("red","orange","yellow"))

-Like a bar chart, a histogram is made up of columns plotted on a graph. Usually, there is no space between adjacent columns.

• Syntax

hist(x, breaks, freq, right, main, xlab, ylab, xlim, ylim,...)

Arguments

• x : a vector of values
• breaks : how to set breakpoints
• freq : logical; if TRUE, show frequencies; if FALSE, probability densities
• right : logical; if TRUE, the histogram cells are right-closed (left open) intervals.
• …
• ?hist

-Example

data = c(2,4,5,7,11,12,15,16,17,18,19,20)
hist(data)

• break points

data = rnorm(1000,20,2)
hist(data,main="default")

hist(data,breaks = 20, main="20 breaks" )

hist(data, breaks = c(0,10,15,18:22,25,30), main = "Customize the breakpoints")

• The box plot is a standardized way of displaying the distribution of data based on the five number summary: minimum, first quartile, median, third quartile, and maximum.

• Syntax

boxplot(x, data = , main = , xlab= ,ylab = ,...)

Arguments

• x : a vector or a formular e.g. y ~ group
• data : a data frame providing the data
• range : determines how far the plot whiskers extend out from the box
• ?boxplot

-Example

• for individual variable

boxplot(mtcars$mpg, ylab="Miles Per Gallon")

• for variables by group

boxplot(mpg~cyl,data=mtcars, main="Car Milage Data", 
    xlab="Number of Cylinders", ylab="Miles Per Gallon")

• Draws a curve corresponding to a function over the interval

• curve function -Syntax

curve(expr, from = , to = ,xlim = ,xlab = ,ylab = , main = ,...)

Arguments

• expr : The name of a function, or a call or an expression written as a function of x
• from, to : he range over which the function will be plotted
• add : logical; if TRUE add to an already existing plot

• …

• Examples

curve(cos, from = -3*pi, to = 3*pi)  ## a function

curve(x^3,from = -5,to=5) ## an expression

• normal distribution

curve(dnorm(x,mean=5,sd=2), from = -2, to=12, main="Use dnorm() function") ## a function

curve(1/(sqrt(2*pi)*2)*exp(-(x-5)^2/(2*4)),from = -2, to = 12, main ="Use an expression")

• add text to a plot -Syntax

text(x,y,labels,adj...)

• x,y : coordinates where the text labels should be written.
• labels : a character vector or expression specifying the text to be written
• adj : adjustment of the labels
• … -Example

x = y = 1:10
plot(x,y)
text(x,y+0.4,labels= letters[1:10],col="red")

abline function

• adds one or more straight lines through the current plot
• Syntax

abline(a = , b = , h = , v = ,  ...)

• a, b: the intercept and slope, single values.
• h : horizontal line

• v : vertical line

• Example

## set up a coordinate system
plot(c(-2,3), c(-1,5), type = "n", xlab = "x", ylab = "y",asp=1)

abline(v = 0, col = "red") ## add a vertical line at x = 0
text(0,4,"abline(v = 0)",adj = 1)
abline(h = 0, col = "blue") ## add a horizontal line at y = 0
text(1,0, "abline( h = 0 )",adj = c(0, -.1))
abline(a = 1, b = 2, col = "green")
text(1,3, "abline( 1, 2 )", adj = c(-.1, -.1))

l <- lm(dist ~ speed, data = cars)
plot(cars) ## draw the scatterplot first
abline(l,col="red") ## add a regression line

curve function with add = TRUE

• Same syntax as before, with the argument add = TRUE

• Example

samples = rnorm(1000,mean = 5,sd = 2)
hist(samples, probability = T)
curve(dnorm(x, mean=5,sd = 2),col="blue",add=TRUE)

pionts function

• add points to a plot
• Syntax

points(x,y, col = , pch = ,...)

• x, y : coordinate vectors of points to plot.

• pch : type of points

• Example

plot(cars,type="n")
carsLong = cars[cars$dist>=70,]
carsMid = cars[cars$dist>=30 & cars$dist<70,]
carsShort = cars[cars$dist<30,]
points(carsLong, col="red",pch=19)
points(carsMid, col="green",pch=19)
points(carsShort, col="blue",pch=19)

## add legends
legend("topleft",legend = c("long","mid","short"),col = c("red","green","blue"),pch = 19,border=NA)

x = -5:5
y = x^2 + rnorm(length(x))
plot(x,y,pch=6,col="red", main = "Main title", sub = "subtitle")
curve(x^2,from = -5, to = 5,lty = 3,col="blue",add=T)


abline(h = 10,col="green")
abline(v = 0,col = "yellow")
abline(5, 2,col="purple",lty=2) 
text(-2, 20, "write text here") 

legend(3,3,"Legend here",pch = 6,col="red")

• identify : identify points

identify(x,y,labels,...)

• locator : add points or lines

locator(type)

• Using packages (rCharts, iPlot,…)

library(rCharts)
n1 = nPlot(wt~mpg | cyl ,data = mtcars, color = "cyl",type="scatterChart")
n1$save('rchart.html', cdn = TRUE)
n1$show('inline', include_assets = TRUE, standalone = TRUE)