USCrimes | R Documentation |
This is a 3 dimensional Array of the US crime statistics downloaded from the "Uniform Crime Reporting Statistics" of the US government. It comprises the years 1960 through 2010 for all 50 states, Washington DC, and a total for the country.
data(USCrimes)
The format is: num [1:52, 1:51, 1:19] 3266740 226167 1302161 1786272 15717204 ... - attr(*, "dimnames")=List of 3 ..$ State: chr [1:52] "Alabama" "Alaska" "Arizona" "Arkansas" ... ..$ : chr [1:51] "1960" "1961" "1962" "1963" ... ..$ : chr [1:19] "Population" "ViolentCrimeRate" "MurderRate" "RapeRate" ...
The first dimension is the state, the dimnames match the variable
state.name
with the exception of including "District of Columbia"
in the 9th position (alphabetically) and "United States-Total" in
position 45 (alphabetical).
The second dimension is the year, ranging from 1960 to 2010. If indexing by year, remember to put the year in quotes.
The third dimension is the variable:
Total number of residents
The total of the violent crimes (Murder, Rape, Robbery, Assault) per 100,000 population
The number of Murders and Nonnegligent Manslaughters per 100,000 population
Forcible Rapes per 100,000 population
Robberies per 100,000 population
Aggravated Assults per 100,000
The total of the property crimes (Burglary, Theft, Vehicle Theft) per 100,000 population
Burglaries per 100,000 population
Larceny-Thefts per 100,000 population
Motor Vehicle Thefts per 100,000 population
The total of the violent crimes (Murder, Rape, Robbery, Assault
The number of Murders and Nonnegligent Manslaughters
Forcible Rapes
Robberies
Aggravated Assults
The total of the property crimes (Burglary, Theft, Vehicle Theft)
Burglaries
Larceny-Thefts
Motor Vehicle Thefts
Originally: "https://ucrdatatool.gov/"", but that site does not work any more. Likely source for similar data: "https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/publications"
data(USCrimes)
## maybe str(USCrimes)
# plot time series/sparkline for each state
if(require(spData) && interactive()) {
data(state.vbm)
plot(state.vbm)
tmp.x <- state.vbm$center_x
tmp.x <- c( tmp.x[1:8], 147, tmp.x[9:43], 83, tmp.x[44:50] )
tmp.y <- state.vbm$center_y
tmp.y <- c( tmp.y[1:8], 45, tmp.y[9:43], -18, tmp.y[44:50] )
tmp.r <- range( USCrimes[,,'ViolentCrimeRate'], na.rm=TRUE)
for(i in 1:52) {
subplot( plot(1960:2010, USCrimes[i,,'ViolentCrimeRate'],
ann=FALSE, bty='n', type='l', axes=FALSE),
tmp.x[i], tmp.y[i], size=c(0.2,0.2) )
}
}
## Gapminder style animation over time
if( interactive() ) {
x.r <- range( USCrimes[-c(9,45),,'Population'], na.rm=TRUE )
y.r <- range( USCrimes[-c(9,45),,'PropertyCrimeRate'], na.rm=TRUE )
tmpfun <- function(Year=1960, ... ) {
y <- as.character(Year)
plot( USCrimes[-c(9,45),y,'Population'],
USCrimes[-c(9,45),y,'PropertyCrimeRate'],
type='n', xlab='log Population',
ylab='Property Crime Rate',
main=y, xlim=x.r, ylim=y.r, log='x' )
text( USCrimes[-c(9,45),y,'Population'],
USCrimes[-c(9,45),y,'PropertyCrimeRate'],
state.abb, ... )
}
tmp.list <- list( Year=list('animate', from=1960, to=2010, delay=250) )
tmpcol <- c('blue','darkgreen','red','purple')[state.region]
tkexamp( tmpfun(col=tmpcol), tmp.list )
}
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