Introduction to ggplot

Lets color the R-World

Data for reference : Iris

Colouring and comparing sepal vs petal

qplot(Sepal.Length, Petal.Length, data = iris, color = Species)

You need to have the package ggplot installed  to proceed further:

install.packages("ggplot2")

#Adding the color parameter (here we have species)

qplot(Sepal.Length, Petal.Length, data = iris, color = Species)

#Adding another dimension in the size parameter

qplot(Sepal.Length, Petal.Length, data = iris, color = Species, size = Petal.Width)

# Adding the x and y axes and giving the title

qplot(Sepal.Length, Petal.Length, data = iris, color = Species,

      xlab = "Sepal Length", ylab = "Petal Length", 

      main = "Sepal vs. Petal Length in Sushovan's Iris data")

#Instead of dots or points, let's try line using geom parameter

qplot(Sepal.Length, Petal.Length, data = iris, geom = "line", color = Species)

#And now..... geom as bar though it does not make any sense here

  qplot(Species, data = iris, weight = Sepal.Length, geom = "bar", ylab = "Sepal.Length")

#Lets see the geom as bar in a user defined dataframe

movies = data.frame(

  director = c("spielberg", "spielberg", "spielberg", "jackson", "jackson"),

  movie = c("jaws", "avatar", "schindler's list", "lotr", "king kong"),

  minutes = c(124, 163, 195, 600, 187)

)

# Here the height of each bar is the total running time of the director's movies.

qplot(director, weight = minutes, data = movies, geom = "bar", ylab = "total length (min.)")

# `Orange` is another built-in data frame that describes the growth of orange trees.

qplot(age, circumference, data = Orange, geom = "line",

      colour = Tree,

      main = "How does orange tree circumference vary with age?")

R-File for reference : Iris R

That's it for today......Enjoy coloring the world!! :)