# Pie Charts

Pie charts are not recommended in the R documentation, and their features are somewhat limited. The authors recommend bar or dot plots over pie charts because people are able to judge length more accurately than volume. Pie charts are created with the function pie(x, labels=) where x is a non-negative numeric vector indicating the area of each slice and labels= notes a character vector of names for the slices.

## Simple Pie Chart

```# Simple Pie Chart slices <- c(10, 12,4, 16, 8) lbls <- c("US", "UK", "Australia", "Germany", "France") pie(slices, labels = lbls, main="Pie Chart of Countries")``` click to view

## Pie Chart with Annotated Percentages

```# Pie Chart with Percentages slices <- c(10, 12, 4, 16, 8) lbls <- c("US", "UK", "Australia", "Germany", "France") pct <- round(slices/sum(slices)*100) lbls <- paste(lbls, pct) # add percents to labels lbls <- paste(lbls,"%",sep="") # ad % to labels pie(slices,labels = lbls, col=rainbow(length(lbls)),    main="Pie Chart of Countries") ``` click to view

## 3D Pie Chart

The pie3D( ) function in the plotrix package provides 3D exploded pie charts.

```# 3D Exploded Pie Chart library(plotrix) slices <- c(10, 12, 4, 16, 8) lbls <- c("US", "UK", "Australia", "Germany", "France") pie3D(slices,labels=lbls,explode=0.1,    main="Pie Chart of Countries ")``` click to view

## Creating Annotated Pies from a data frame

```# Pie Chart from data frame with Appended Sample Sizes mytable <- table(iris\$Species) lbls <- paste(names(mytable), "\n", mytable, sep="") pie(mytable, labels = lbls,    main="Pie Chart of Species\n (with sample sizes)") ``` click to view