{"id":78497,"date":"2020-05-05T10:00:37","date_gmt":"2020-05-05T04:30:37","guid":{"rendered":"https:\/\/techvidvan.com\/tutorials\/?p=78497"},"modified":"2020-05-05T10:00:37","modified_gmt":"2020-05-05T04:30:37","slug":"lattice-package-in-r","status":"publish","type":"post","link":"https:\/\/techvidvan.com\/tutorials\/lattice-package-in-r\/","title":{"rendered":"Lattice Package in R with Functions and Graphs"},"content":{"rendered":"

Lattice is a powerful and elegant data visualization package for R programming, with an emphasis on multivariate data. It is inspired by trellis graphics.\u00a0 In this article of TechVidvan\u2019s R tutorial series<\/strong>, we are going to learn about the lattice package in R<\/strong>. We will study the functions and commands in the lattice package. We shall also look at the graphical capabilities of the package. So, let\u2019s go!<\/p>\n

\"Lattice<\/a>
\nLattice Package in R<\/h2>\n

The lattice package is a graphics and data visualization package inspired by the trellis graphics package. The main focus of the package is multivariate data. It has a wide variety of functions that enable it to create basic plots of the base R package as well as enhance on them. Let us start looking at all the functions and graphs in the lattice package, one-by-one.<\/p>\n

1. Scatter Plots in the Lattice Package<\/h3>\n

The xyplot()<\/strong> function can be used to create a scatter plot in R using the lattice package. The iris dataset is perfectly suited for this example.<\/p>\n

library(lattice)\nxyplot(Sepal.Length ~ Petal.Length,\n       data = iris)<\/pre>\n
Output:<\/strong><\/p>\n
\"Scatter<\/a><\/p>\n
We can color the points of the scatter plot based on the categories.<\/p>\n
xyplot(Sepal.Length ~ Petal.Length,\n       data = iris,\n       group = Species,\n       auto.key = TRUE)<\/pre>\n
Output:<\/strong><\/p>\n
\"color<\/a><\/p>\n
We can change the x and y labels and also add smoothing lines to the plot using the arguments in the xyplot() function.<\/strong><\/p>\n
xyplot(Sepal.Length ~ Petal.Length,\n       data = iris,\n       type = c(\"p\", \"g\", \"smooth\"),\n       xlab = \"Miles\/(US) gallons\",\n       ylab = \"Weight (1000lbs)\")<\/pre>\n
Output:<\/strong><\/p>\n
\"Lattice<\/a><\/p>\n
We can also create plots in multiple panels based on groups.<\/p>\n
xyplot(Sepal.Length ~ Petal.Length | Species,\n       group = Species,\n       data = iris,\n       type = c(\"p\", \"smooth\"),\n       scales = \"free\")<\/pre>\n
Output:<\/strong><\/p>\n
\"create<\/a><\/p>\n
2. 3D scatter plots<\/h3>\n
Using the cloud() function, we can create a 3D scatter plot. We can use the iris dataset for this example.<\/p>\n
cloud(Sepal.Length ~ Sepal.Length*Petal.Width,\n      data = iris)<\/pre>\n
Output:<\/strong><\/p>\n
\"create<\/a><\/p>\n
We can use the group argument to color the point based on groups, similarly to the xyplot() function.<\/p>\n
cloud(Sepal.Length ~ Sepal.Length*Petal.Width,\n      data = iris,\n      group = Species,\n      auto.key = TRUE)<\/pre>\n
Output:<\/strong><\/p>\n
\"the<\/a><\/p>\n
3. Boxplots in Lattice Package in R<\/h3>\n
The lattice package provides a bwplot() function that can be used to create a box plot. We will be using the ToothGrowth data set for this example.<\/p>\n
ToothGrowth$dose <- as.factor(ToothGrowth$dose)\nbwplot(len ~ dose, data = ToothGrowth,\n       xlab = \"Dose\",\n       ylab = \"Length\")<\/pre>\n
Output:<\/strong><\/p>\n
\"create<\/a><\/p>\n
Using the panel argument of bwplot<\/strong>() function, we can make a violin plot as well.<\/p>\n
bwplot(len ~ dose, data = ToothGrowth,\n           xlab = \"Dose\",\n           ylab = \"Length\",\n           panel = panel.violin)<\/pre>\n
Output:<\/strong><\/p>\n
\"the<\/a><\/p>\n
We can also create multiple plots based on the groups.<\/p>\n
bwplot(len ~ supp|dose,\n       data = ToothGrowth,\n       layout = c(3,1),\n       xlab = \"Dose\",\n       ylab = \"Length\")<\/pre>\n
Output:<\/strong><\/p>\n
\"create<\/a><\/p>\n
bwplot(len ~ supp|dose,\n       data = ToothGrowth,\n       layout = c(3,1),\n       xlab = \"Dose\",\n       ylab = \"Length\",\n       panel = panel.violin)<\/pre>\n
Output:<\/strong><\/p>\n
\"using<\/a><\/p>\n
4. Dotplots in Lattice Package in R<\/h3>\n
The R dotplot() function<\/strong>\u00a0 enables us to create dot plots in R. We will again use the ToothGrowth<\/strong> dataset for this example.<\/p>\n
dotplot(len ~ dose,\n        data = ToothGrowth,\n        xlab = \"Dose\",\n        ylab = \"Length\")<\/pre>\n
Output:<\/strong><\/p>\n
\"The<\/a><\/p>\n
dotplot(len ~ supp|dose,\n        data = ToothGrowth,\n        layout = c(3,1),\n        xlab = \"Dose\",\n        ylab = \"Length\")<\/pre>\n
Output:<\/strong><\/p>\n
\"final<\/a><\/p>\n
5. Strip Plots in the Lattice Package<\/h3>\n
Strip plots can be created in R using the stripplot()<\/strong> function of the lattice package. We will be using the same ToothGrowth<\/strong> dataset.<\/p>\n
stripplot(len ~ dose,\n          data = ToothGrowth,\n          jitter.data = TRUE,\n          pch = 19,\n          xlab = \"Dose\",\n          ylab = \"Length\")<\/pre>\n
Output:<\/strong><\/p>\n
\"stripplot()<\/a><\/p>\n
stripplot(len ~ supp|dose,\n          data = ToothGrowth,\n          layout = c(3,1),\n          xlab = \"Dose\",\n          ylab = \"Length\",\n          jitter.data = TRUE)<\/pre>\n
Output:<\/strong><\/p>\n
\"Lattice<\/a><\/p>\n
6. Density Plots in the Lattice Package<\/h3>\n
We can create density plots in R using the densityplot()<\/strong> function of the lattice package.<\/p>\n
densityplot(~ len, data = ToothGrowth,\n                  plot.points = FALSE)<\/pre>\n
Output:<\/strong><\/p>\n
\"the<\/a><\/p>\n
densityplot(~ len, data = ToothGrowth,\n            plot.points = FALSE,\n            groups = dose,\n            auto.key = TRUE)<\/pre>\n
Output:<\/strong><\/p>\n
\"Lattice<\/a><\/p>\n
7. Histograms in the Lattice Package<\/h3>\n
To create a histogram using the lattice package, we can use the histogram()<\/strong> function.<\/p>\n
histogram(~ len, data = ToothGrowth, \n          breaks = 20)<\/pre>\n
Output:<\/strong><\/p>\n
\"Histograms<\/a><\/p>\n
Summary<\/h2>\n
In this chapter of TechVidvan\u2019s R tutorial series, we learned about the Lattice Package in R<\/strong>. We studied the functions of the R Lattice package that create the various graphs and plots. We looked at how to create graphs like scatter plots, 3D scatter plots, boxplots, dotplots, stripplots, density plots<\/a>, and histograms.<\/p>\n
Do share your feedback in the comment section.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"
Lattice is a powerful and elegant data visualization package for R programming, with an emphasis on multivariate data. It is inspired by trellis graphics.\u00a0 In this article of TechVidvan\u2019s R tutorial series, we are...<\/p>\n","protected":false},"author":1,"featured_media":78522,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1020],"tags":[2574,2575],"class_list":["post-78497","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-r","tag-lattice-package-in-r","tag-r-lattice-package"],"yoast_head":"\nLattice Package in R with Functions and Graphs - TechVidvan<\/title>\n<meta name=\"description\" content=\"Lattice Package in R - Learn what is R lattice package and its functions, how to create graphs - scatter plots,boxplots,dotplots,stripplots,density plots,histograms\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/techvidvan.com\/tutorials\/lattice-package-in-r\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Lattice Package in R with Functions and Graphs - 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