Pleleminary tasks

1. Launch RStudio as described here: Running RStudio and setting up your working directory

2. Prepare your data as described here: Best practices for preparing your data and save it in an external .txt tab or .csv files

3. Import your data into R as described here: Fast reading of data from txt|csv files into R: readr package.

Briefly, if your data is saved in an external .txt tab or .csv files, use the following script to import the data into R:

# If .txt tab file use this:
my_data <- read.delim(file.choose())

# or if .csv file:
my_data <- read.csv(file.choose())

In the following sections, we’ll use R built-in data sets.

Installing and loading the lattice package

# Install
install.packages("lattice")

# Load
library("lattice")

Main functions in the lattice package

Note that, other functions (ecdfplot() and mapplot()) are available in the latticeExtra package.

xyplot(): Scatter plot

• R function: The R function xyplot() is used to produce bivariate scatter plots or time-series plots. The simplified format is as follow:

xyplot(y ~ x, data)

• Data set: mtcars

my_data <- iris
head(my_data)

##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

• Basic scatter plot: y ~ x

# Default plot
xyplot(Sepal.Length ~ Petal.Length, data = my_data)

# Color by groups
xyplot(Sepal.Length ~ Petal.Length, group = Species, 
       data = my_data, auto.key = TRUE)

# Show points ("p"), grids ("g") and smoothing line
# Change xlab and ylab
xyplot(Sepal.Length ~ Petal.Length, data = my_data,
       type = c("p", "g", "smooth"),
       xlab = "Miles/(US) gallon", ylab = "Weight (1000 lbs)")

• Multiple panels by groups: y ~ x | group

xyplot(Sepal.Length ~ Petal.Length | Species, 
       group = Species, data = my_data,
       type = c("p", "smooth"),
       scales = "free")

cloud(): 3D scatter plot

• Data set: iris

my_data <- iris
head(my_data)

##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

• Scatter 3D plot: z ~ x * y

# Basic 3D scatter plot
cloud(Sepal.Length ~ Sepal.Length * Petal.Width, 
       data = iris)

# Color by groups; auto.key = TRUE to show legend
cloud(Sepal.Length ~ Sepal.Length * Petal.Width, 
       group = Species, data = iris,
       auto.key = TRUE)

Box plot, Dot plot, Strip plot

• Data set: ToothGrowth

ToothGrowth$dose <- as.factor(ToothGrowth$dose)
head(ToothGrowth)

##    len supp dose
## 1  4.2   VC  0.5
## 2 11.5   VC  0.5
## 3  7.3   VC  0.5
## 4  5.8   VC  0.5
## 5  6.4   VC  0.5
## 6 10.0   VC  0.5

• Basic plot: Plot len by dose

# Basic box plot
bwplot(len ~ dose,  data = ToothGrowth,
       xlab = "Dose", ylab = "Length")

# Violin plot using panel = panel.violin
bwplot(len ~ dose,  data = ToothGrowth,
       panel = panel.violin,
       xlab = "Dose", ylab = "Length")
# Basic dot plot
dotplot(len ~ dose,  data = ToothGrowth,
        xlab = "Dose", ylab = "Length")

# Basic stip plot
stripplot(len ~ dose,  data = ToothGrowth,
          jitter.data = TRUE, pch = 19,
          xlab = "Dose", ylab = "Length")

• Plot with multiple groups: Additional argument layout is used: c(3, 1) specifying the number of column and row, respectively

# Box plot
bwplot(len ~ supp | dose,  data = ToothGrowth,
       layout = c(3, 1),
        xlab = "Dose", ylab = "Length")

# Violin plot
bwplot(len ~ supp | dose,  data = ToothGrowth,
       layout = c(3, 1), panel = panel.violin,
        xlab = "Dose", ylab = "Length")

# Dot plot
dotplot(len ~ supp | dose,  data = ToothGrowth,
       layout = c(3, 1),
        xlab = "Dose", ylab = "Length")

# Strip plot
stripplot(len ~ supp | dose,  data = ToothGrowth,
       layout = c(3, 1), jitter.data = TRUE,
        xlab = "Dose", ylab = "Length")

Density plot and Histogram

• Basic plots

densityplot(~ len, data = ToothGrowth,
            plot.points = FALSE)

histogram(~ len, data = ToothGrowth,
            breaks = 20)

• Plot with multiple groups

densityplot(~ len, groups = dose, data = ToothGrowth,
            plot.points = FALSE, auto.key = TRUE)

See also

1. R base plots
   • Creating and Saving Graphs in R
   • Scatter Plots
   • Scatter Plot Matrices
   • Box Plots
   • Strip Charts: 1-D scatter Plots
   • Bar Plots
   • Line Plots
   • Pie Charts
   • Histogram and Density Plots
   • Dot Charts
   • Plot Group Means and Confidence Intervals
   • Graphical Parameters
2. ggplot2 Graphs

Infos

This analysis has been performed using R statistical software (ver. 3.2.4).