Read Box Pocket Chart Use Redbox Near Me
Boxplots
Boxplots can be created for individual variables or for variables by grouping. The format is boxplot( ten , data=), where x is a formula and data= denotes the data frame providing the data. An example of a formula is y~group where a separate boxplot for numeric variable y is generated for each value of grouping. Add together varwidth=Truthful to make boxplot widths proportional to the foursquare root of the samples sizes. Add horizontal=TRUE to reverse the axis orientation.
# Boxplot of MPG past Car Cylinders
boxplot(mpg~cyl,data=mtcars, main="Motorcar Milage Data",
xlab="Number of Cylinders", ylab="Miles Per Gallon")
click to view
# Notched Boxplot of Tooth Growth Against 2 Crossed Factors
# boxes colored for ease of interpretation
boxplot(len~supp*dose, data=ToothGrowth, notch=TRUE,
col=(c("aureate","darkgreen")),
main="Tooth Growth", xlab="Suppliment and Dose")
click to view
In the notched boxplot, if 2 boxes' notches exercise non overlap this is 'strong evidence' their medians differ (Chambers et al., 1983, p. 62).
Colors recycle. In the example above, if I had listed six colors, each box would accept its own color. Earl F. Glynn has created an easy to use list of colors is PDF format.
Other Options
The boxplot.matrix( ) function in the sfsmisc parcel draws a boxplot for each column (row) in a matrix. The boxplot.north( ) office in the gplots package annotates each boxplot with its sample size. The bplot( ) function in the Rlab bundle offers many more options controlling the positioning and labeling of boxes in the output.
Violin Plots
A violin plot is a combination of a boxplot and a kernel density plot. They can be created using the vioplot( ) part from vioplot packet.
# Violin Plots
library(vioplot)
x1 <- mtcars$mpg[mtcars$cyl==four]
x2 <- mtcars$mpg[mtcars$cyl==six]
x3 <- mtcars$mpg[mtcars$cyl==eight]
vioplot(x1, x2, x3, names=c("iv cyl", "vi cyl", "8 cyl"),
col="gold")
title("Violin Plots of Miles Per Gallon")
click to view
Bagplot - A second Boxplot Extension
The bagplot(x, y) function in the aplpack package provides a bivariate version of the univariate boxplot. The bag contains 50% of all points. The bivariate median is approximated. The fence separates points in the contend from points exterior. Outliers are displayed.
# Example of a Bagplot
library(aplpack)
attach(mtcars)
bagplot(wt,mpg, xlab="Car Weight", ylab="Miles Per Gallon",
principal="Bagplot Example")
click to view
To Do
Try the boxplot exercises in this course on plotting and data visualization in R.
Source: https://www.statmethods.net/graphs/boxplot.html
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