ohio.cdp

Description

ohio.cdp is a SpatialPolygonsDataFrame with polygons made from the 2000 US Census tiger/line boundary files (http://www.census.gov/geo/www/tiger/) for Census Designated Places (CDP). It also contains 86 variables from the Summary File 1 (SF 1) which contains the 100-percent data (http://www.census.gov/prod/cen2000/doc/sf1.pdf).

All polygons are projected in CRS("+proj=longlat +datum=NAD83")

Usage

1

Details

ID Variables

data field name Full Description
place FIPS code
state State FIPS code
name CDP name
designation city/town/CDP/etc.

Census Variables

Census SF1 Field Name data field name Full Description
(P007001) pop2000 population 2000
(P007002) white white alone
(P007003) black black or african american alone
(P007004) ameri.es american indian and alaska native alone
(P007005) asian asian alone
(P007006) hawn.pi native hawaiian and other pacific islander alone
(P007007) other some other race alone
(P007008) mult.race 2 or more races
(P011001) hispanic people who are hispanic or latino
(P008002) not.hispanic.t Not Hispanic or Latino
(P008003) nh.white White alone
(P008004) nh.black Black or African American alone
(P008005) nh.ameri.es American Indian and Alaska Native alone
(P008006) nh.asian Asian alone
(P008007) nh.hawn.pi Native Hawaiian and Other Pacific Islander alone
(P008008) nh.other Some other race alone
(P008010) hispanic.t Hispanic or Latino
(P008011) h.white White alone
(P008012) h.black Black or African American alone
(P008013) h.american.es American Indian and Alaska Native alone
(P008014) h.asian Asian alone
(P008015) h.hawn.pi Native Hawaiian and Other Pacific Islander alone
(P008016) h.other Some other race alone
(P012002) males males
(P012026) females females
(P012003 + P012027) age.under5 male and female under 5 yrs
(P012004-006 + P012028-030) age.5.17 male and female 5 to 17 yrs
(P012007-009 + P012031-033) age.18.21 male and female 18 to 21 yrs
(P012010-011 + P012034-035) age.22.29 male and female 22 to 29 yrs
(P012012-013 + P012036-037) age.30.39 male and female 30 to 39 yrs
(P012014-015 + P012038-039) age.40.49 male and female 40 to 49 yrs
(P012016-019 + P012040-043) age.50.64 male and female 50 to 64 yrs
(P012020-025 + P012044-049) age.65.up male and female 65 yrs and over
(P013001) med.age median age, both sexes
(P013002) med.age.m median age, males
(P013003) med.age.f median age, females
(P015001) households households
(P017001) ave.hh.sz average household size
(P018003) hsehld.1.m 1-person household, male householder
(P018004) hsehld.1.f 1-person household, female householder
(P018008) marhh.chd family households, married-couple family, w/ own children under 18 yrs
(P018009) marhh.no.c family households, married-couple family, no own children under 18 yrs
(P018012) mhh.child family households, other family, male householder, no wife present, w/ own children under 18 yrs
(P018015) fhh.child family households, other family, female householder, no husband present, w/ own children under 18 yrs
(H001001) hh.units housng units total
(H002002) hh.urban urban housing units
(H002005) hh.rural rural housing units
(H003002) hh.occupied occupied housing units
(H003003) hh.vacant vacant housing units
(H004002) hh.owner owner occupied housing units
(H004003) hh.renter renter occupied housing units
(H013002) hh.1person 1-person household
(H013003) hh.2person 2-person household
(H013004) hh.3person 3-person household
(H013005) hh.4person 4-person household
(H013006) hh.5person 5-person household
(H013007) hh.6person 6-person household
(H013008) hh.7person 7-person household
(H015I003)+(H015I011) hh.nh.white.1p (white only, not hispanic ) 1-person household
(H015I004)+(H015I012) hh.nh.white.2p (white only, not hispanic ) 2-person household
(H015I005)+(H015I013) hh.nh.white.3p (white only, not hispanic ) 3-person household
(H015I006)+(H015I014) hh.nh.white.4p (white only, not hispanic ) 4-person household
(H015I007)+(H015I015) hh.nh.white.5p (white only, not hispanic ) 5-person household
(H015I008)+(H015I016) hh.nh.white.6p (white only, not hispanic ) 6-person household
(H015I009)+(H015I017) hh.nh.white.7p (white only, not hispanic ) 7-person household
(H015H003)+(H015H011) hh.hisp.1p (hispanic) 1-person household
(H015H004)+(H015H012) hh.hisp.2p (hispanic) 2-person household
(H015H005)+(H015H013) hh.hisp.3p (hispanic) 3-person household
(H015H006)+(H015H014) hh.hisp.4p (hispanic) 4-person household
(H015H007)+(H015H015) hh.hisp.5p (hispanic) 5-person household
(H015H008)+(H015H016) hh.hisp.6p (hispanic) 6-person household
(H015H009)+(H015H017) hh.hisp.7p (hispanic) 7-person household
(H015B003)+(H015B011) hh.black.1p (black) 1-person household
(H015B004)+(H015B012) hh.black.2p (black) 2-person household
(H015B005)+(H015B013) hh.black.3p (black) 3-person household
(H015B006)+(H015B014) hh.black.4p (black) 4-person household
(H015B007)+(H015B015) hh.black.5p (black) 5-person household
(H015B008)+(H015B016) hh.black.6p (black) 6-person household
(H015B009)+(H015B017) hh.black.7p (black) 7-person household
(H015D003)+(H015D011) hh.asian.1p (asian) 1-person household
(H015D004)+(H015D012) hh.asian.2p (asian) 2-person household
(H015D005)+(H015D013) hh.asian.3p (asian) 3-person household
(H015D006)+(H015D014) hh.asian.4p (asian) 4-person household
(H015D007)+(H015D015) hh.asian.5p (asian) 5-person household
(H015D008)+(H015D016) hh.asian.6p (asian) 6-person household
(H015D009)+(H015D017) hh.asian.7p (asian) 7-person household

Source

Census 2000 Summary File 1 [name of state1 or United States]/prepared by the U.S. Census Bureau, 2001.

References

http://www.census.gov/
https://www.census.gov/geo/maps-data/data/tiger-line.html
http://www.census.gov/prod/cen2000/doc/sf1.pdf

Examples

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data(ohio.cdp)

############################################
## Helper function for handling coloring of the map
############################################
color.map<- function(x,dem,y=NULL){
	l.poly<-length(x@polygons)
	dem.num<- cut(dem ,breaks=ceiling(quantile(dem)),dig.lab = 6)
	dem.num[which(is.na(dem.num)==TRUE)]<-levels(dem.num)[1]
	l.uc<-length(table(dem.num))
if(is.null(y)){
	col.heat<-heat.colors(16)[c(14,8,4,1)] ##fixed set of four colors
}else{
	col.heat<-y
	}
dem.col<-cbind(col.heat,names(table(dem.num)))
colors.dem<-vector(length=l.poly)
for(i in 1:l.uc){
	colors.dem[which(dem.num==dem.col[i,2])]<-dem.col[i,1]
	}
out<-list(colors=colors.dem,dem.cut=dem.col[,2],table.colors=dem.col[,1])
return(out)
}
############################################
## Helper function for handling coloring of the map
############################################

colors.use<-color.map(ohio.cdp,ohio.cdp$pop2000)
plot(ohio.cdp,col=colors.use$colors)
#text(coordinates(ohio.cdp),ohio.cdp$name,cex=.3)
title(main="Census Designated Places \n of Ohio, 2000", 
sub="Quantiles (equal frequency)")
legend("bottomright",legend=colors.use$dem.cut,
fill=colors.use$table.colors,bty="o",
title="Population Count",bg="white")



###############################
### Alternative way to do the above
###############################
## Not run: 
####This example requires the following additional libraries
library(RColorBrewer)
library(classInt)  
library(maps)
####This example requires the following additional libraries

data(ohio.cdp)

map('state',region='ohio')
plotvar <- ohio.cdp$pop2000
	nclr <- 4
	#BuPu
	plotclr <- brewer.pal(nclr,"BuPu")
	class <- classIntervals(plotvar, nclr, style="quantile")
	colcode <- findColours(class, plotclr)
	plot(ohio.cdp, col=colcode, border="transparent",add=TRUE)
	#transparent
title(main="Census Designated Places\n of Ohio, 2000", 
sub="Quantiles (equal frequency)")
map.text("county", "ohio",cex=.7,add=TRUE)
map('county','ohio',add=TRUE)
legend("bottomright","(x,y)", legend=names(attr(colcode, "table")),
fill=attr(colcode, "palette"), 
cex=0.9, bty="o", title="Population Count",bg="white")

## End(Not run)

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