Introduction

This code through explores the Lattice package in R. The R lattice package allows users to create graphics, graphs, and R lattice graphs. A lattice in R is best known for its elegant, robust, and aesthetic data visualization system. This package was inspired by the Trellis graphics, but it is designed with emphasis on the multivariate data that allows for easy conditioning to produce “small multiple” plots.


Content Overview

Specifically, we’ll explain and demonstrate how to create various graphs using the Lattice package in R by using the US national unemployment rates analyzed by demographics between the years of 2010-2020.


Why You Should Care

This topic is valuable because it allows researchers, analysts, and other users of the R package to create compelling data visualizations that can help others to demonstrate their findings and research related to various data.


Learning Objectives

Specifically, you’ll learn how to create various graphs using the Lattice package. You will learn how to create a histogram, a xyplot scatterplot matrix, multiple R lattice histogram, and how to change the color of bars through various graph that can be created through the R Lattice package.



Body Title

Here, we’ll show how to produce a few of the varous graphs that can be created with the Lattice package. The various graphs that can be created includes: 1. Bar Chart 2. Boxplot 3. 3D Scatter Plot 4. 3D Counter Plot 5. Kernel Density Plot 6. Dotplot 7. Histogram 8. 3D Level Plot 9. Parallel Coordinates Plot 10. Scatterplot Matrix (Splom, xyplot) 11. Strip Plots 12. 3D Wireframe Graph

High-Level Functions in Lattice 1. Histogram 2. Kernel Density Plot 3. Theoretical Quantile Plot 4. Two-sample Quantile Plot 5. Stripchart (Comparative 1-D Scatter Plots) 6. Comparative Box-and-Whisker Plots 7. Bar Plot 8. Cleveland Dot Plot 9. Scatter Plot 10. Scatter Plot Matrix 11. Contour Plot of Surfaces 12. False Color Level Plot of Surfaces


Further Exposition

This is based/expanded on the theory/work/extension of Deepayan Sarkar. Sarkar wrote the Lattice package to provide better defaults for various graphics. This package improves on the base-R graphics and also provides the ability to display multivariate relationships of various data. The Lattice package supports the creation of trellis graphs, which display a variable and display the relationship between variables which are conditioned on one or other various variables.


Basic Example

A basic example shows how to create a R Histogram using the Lattice package.

# Histogram of the US unemployment rate between years 2010 - 2020

histogram(~ dat2$Year, dat2$Unemployment_rate, data = dat2,
          main = "US Employment Rate",
          xlab = "Year",
          ylab = "Unemployment Rate")


Advanced Examples

More specifically, this can be used for creating a xyplot graph type, which is a scatterplot matrix.

# Some code

panel.smoother <- function(x, y) {
  panel.xyplot(x, y) 
  panel.loess(x, y) 
}
attach(dat2)

unemploymentRate <- cut(Unemployment_rate,10) 
xyplot(Year~unemploymentRate, scales=list(cex=.8, col="red"),
       panel=panel.smoother,
       xlab="Unemployment Rate", ylab="Year",
       main="US Employment Rate Over the Years")


What’s more, it can also be used for creating multiple R lattice histograms.

# R Lattice Histograms displaying the various unemployment rates based off of demographics. 

histogram(~ Unemployment_rate | Demographic, data = dat2,
          main = "US Uemployment Rate Histogram",
          xlab = "Year",
          ylab = "Unemployment Rates",
          col = c("gray85", "goldenrod1", "blue4", "chartreuse" ))


Most notably, it’s valuable for creating various scatterplots including the multiple panel scatterplot output below.

# 3D Scatter Plot

xyplot( Unemployment_rate ~ Year | Demographic,
       group = Demographic,
       data = dat2,
       type = c("p", "smooth"),
       scales = "free")



Further Resources

Learn more about [package, technique, dataset] with the following:




Works Cited

This code through references and cites the following sources: