Prepare the data

mtcars data sets are used in the examples below.

# Convert cyl column from a numeric to a factor variable
mtcars$cyl <- as.factor(mtcars$cyl)
head(mtcars)

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

Basic qq plots

In the example below, the distribution of the variable mpg is explored :

library(ggplot2)
# Solution 1
qplot(sample = mpg, data = mtcars)
# Solution 2
ggplot(mtcars, aes(sample=mpg))+stat_qq()

Change qq plot point shapes by groups

In the R code below, point shapes are controlled automatically by the variable cyl.

You can also set point shapes manually using the function scale_shape_manual()

# Change point shapes by groups
p<-qplot(sample = mpg, data = mtcars, shape=cyl)
p
# Change point shapes manually
p + scale_shape_manual(values=c(1,17,19))

Read more on point shapes : ggplot2 point shapes

Change qq plot colors by groups

In the R code below, point colors of the qq plot are automatically controlled by the levels of cyl :

# Change qq plot colors by groups
p<-qplot(sample = mpg, data = mtcars, color=cyl)
p

It is also possible to change manually qq plot colors using the functions :

• scale_color_manual() : to use custom colors
• scale_color_brewer() : to use color palettes from RColorBrewer package
• scale_color_grey() : to use grey color palettes

# Use custom color palettes
p+scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))
# Use brewer color palettes
p+scale_color_brewer(palette="Dark2")
# Use grey scale
p + scale_color_grey() + theme_classic()

Read more on ggplot2 colors here : ggplot2 colors

Change the legend position

p + theme(legend.position="top")
p + theme(legend.position="bottom")
p + theme(legend.position="none") # Remove legend

The allowed values for the arguments legend.position are : “left”,“top”, “right”, “bottom”.

Read more on ggplot legends : ggplot2 legend

Customized qq plots

# Basic qq plot
qplot(sample = mpg, data = mtcars)+
labs(title="Miles per gallon \n according to the weight",
       y = "Miles/(US) gallon")+
theme_classic()
# Change color/shape by groups
p <- qplot(sample = mpg, data = mtcars, color=cyl, shape=cyl)+
labs(title="Miles per gallon \n according to the weight",
       y = "Miles/(US) gallon")
p + theme_classic()

Change colors manually :

# Continuous colors
p + scale_color_brewer(palette="Blues") + theme_classic()
# Discrete colors
p + scale_color_brewer(palette="Dark2") + theme_minimal()
# Gradient colors
p + scale_color_brewer(palette="RdBu")

Read more on ggplot2 colors here : ggplot2 colors

Infos

This analysis has been performed using R software (ver. 3.1.2) and ggplot2 (ver. 1.0.0)

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