crime {ggbiplot}

U. S. Crimes

Description

This dataset gives rates of occurrence (per 100,000 people) various serious crimes in each of the 50 U. S. states, originally from the United States Statistical Abstracts (1970). The data were analyzed by John Hartigan (1975) in his book Clustering Algorithms and were later reanalyzed by Friendly (1991).

Usage

data(crime)

Format

A data frame with 50 observations on the following 10 variables.

state

state name, a character vector

murder

a numeric vector

rape

a numeric vector

robbery

a numeric vector

assault

a numeric vector

burglary

a numeric vector

larceny

a numeric vector

auto

auto thefts, a numeric vector

st

state abbreviation, a character vector

region

region of the U.S., a factor with levels Northeast South North Central West

Source

The data are originally from the United States Statistical Abstracts (1970). This dataset also appears in the SAS/Stat Sample library, Getting Started Example for PROC PRINCOMP, https://support.sas.com/documentation/onlinedoc/stat/ex_code/131/princgs.html, from which the current copy was derived.

References

Friendly, M. (1991). SAS System for Statistical Graphics. SAS Institute.

Hartigan, J. A. (1975). Clustering Algorithms. John Wiley and Sons.

Examples

data(crime)
library(ggplot2)
crime.pca <- 
  crime |> 
  dplyr::select(where(is.numeric)) |>
  prcomp(scale. = TRUE)

ggbiplot(crime.pca,
     labels = crime$st ,
     circle = TRUE,
     varname.size = 4,
     varname.color = "red") +
 theme_minimal(base_size = 14)