SOCR Data US Elections Counties2004

SOCR Data - Multivariate US 2004 Elections and County Dataset

Data Description

2000 US Census

These data represent a combined collective of multivariate data about the US population for 2000-2004. The dataset includes 2000 US census data and elections data from the 2004 general election in the US.

Meta-data

• Sources: 2000 US National Census and 2004 US National Elections
• Variables Description:
  • NAME: US County Name
  • STATE_NAME: US State
  • STATE_FIPS: The 2-digit FIPS code of the State or State equivalent
  • CNTY_FIPS: The 2-digit FIPS code of the County
  • PCountyFIPS: The 5-digit FIPS code identifying the State and county and equivalent entities
  • Bush: Number of votes for Bush
  • Kerry: Number of votes for Kerry
  • Nader: Number of votes for Nader
  • Total: Total number of votes
  • Bush_pct: Percent of votes for Bush
  • Kerry_pct: Percent of votes for Kerry
  • Nader_pct: Percent of votes for Nader
  • MDratio: physicians per 1,000 population (MDRATIO)
  • hosp: hospitals per 1,000 population
  • pcthisp: percentage of Hispanic origin
  • pcturban: percentage of urban population
  • urbrural: USDA urban/rural code (0=most urban, 9=most rural)
  • pctfemhh: percentage of households headed by female
  • pcincome: per capita income
  • pctpoor: percentage below the poverty line
  • pctlt9ed: percent of population with less than 9th grade level of education
  • pcthsed: percent home school educated
  • pctcoled: percentage of adults over 25 with 4+ years of college education
  • unemploy: unemployment rate
  • pctwhtcl: percent of adults employed in white collar jobs
  • homevalu: average home value
  • rent: average rent
  • popdens: population density
  • crowded:
  • ginirev:
  • SmokecurM: proportion of current Male smokers
  • SmokevrM: proportion of Male smokers (ever)
  • SmokecurF: proportion of current Female smokers
  • SmokevrF: proportion of Female smokers (ever)
  • Obese: Proportion of obese individuals
  • Noins: percentage of persons ages 18+ who do not have a health plan or health insurance
  • XYLENES__M:
  • TOLUENE:
  • TETRACHLOR:
  • STYRENE:
  • NICKEL_COM:
  • METHYLENE:
  • MERCURY_CO:
  • LEAD_COMPO:
  • BENZENE__I:
  • ARSENIC_CO:
  • POP2000: population according to the 2000 US Census
  • POP00SQMIL: The number of people per square mile in 2000
  • MALE2000: total number of males according to the 2000 US Census
  • FEMALE2000: total number of females according to the 2000 US Census
  • MAL2FEM: male-to-female percent
  • UNDER18: percent residents under 18 years
  • AIAN: American Indian and Alaska Native
  • ASIA: Asian
  • BLACK: Black
  • NHPI: Native Hawaiian and Other Pacific Islander
  • WHITE: White
  • AIAN_MORE: The percent of people in the county or county equivalent indicating Two or More Races including American Indian and Alaska Native in 2000
  • ASIA_MORE: The percent of people in the county or county equivalent indicating Two or More Races including Asian in 2000
  • BLK_MORE: The percent of people in the county or county equivalent indicating Two or More Races including Balck in 2000
  • NHPI_MORE:
  • WHT_MORE:
  • HISP_LAT: The percent of people in the county or county equivalent indicating Hispanic or Latino Origin, All Races in 2000
  • CH19902000: The population change between 1990 and 2000, as a percentage of the 1990 population
  • MEDAGE2000: Median age of the population in 2000
  • PEROVER65: The percent of people in the county or county equivalent, over the age of 65 in 2000.

Data Table

The complete data file is available here (1.2MB text CSV file). The table below shows a fragment of this complex multivariate dataset.

NAME	STATE_NAME	STATE_FIPS	CNTY_FIPS	PCountyFIPS	Bush	Kerry	Nader	Total	Bush_pct	Kerry_pct	Nader_pct	MDratio	hosp	pcthisp	pcturban	urbrural	pctfemhh	pcincome	pctpoor	pctlt9ed	pcthsed	pctcoled	unemploy	pctwhtcl	homevalu	rent	popdens	crowded	ginirev	SmokecurM	SmokevrM	SmokecurF	SmokevrF	Obese	Noins	XYLENES__M	TOLUENE	TETRACHLOR	STYRENE	NICKEL_COM	METHYLENE	MERCURY_CO	LEAD_COMPO	BENZENE__I	ARSENIC_CO	POP2000	POP00SQMIL	MALE2000	FEMALE2000	MAL2FEM	UNDER18	AIAN	ASIA	BLACK	NHPI	WHITE	AIAN_MORE	ASIA_MORE	BLK_MORE	NHPI_MORE	WHT_MORE	HISP_LAT	CH19902000	MEDAGE2000	PEROVER65
Lake_of_the_Woods	Minnesota	27	77	27077	1428	921	27	2376	60.1010101	38.76262626	1.136363636	66.8	22.27	6	0	9	8	17856	10.6	14	75.2	11	4.1	44.4	40100	244	3.4	2.7	0.37	0.2	0.46	0.19	0.41	0.32	0.08	1158.19	1093.06	0.06	13.98	0.00645	85.51	0.00063	0.00181	331.37	0.000137	4522	3.5	2272	2250	101	24.7	1.1	0.2	0.3	0	97.2	1.9	0.4	0.6	0	98.2	0.6	10.9	41.6	17.2
Ferry	Washington	53	19	53019	1969	1156	57	3182	61.87932118	36.32935261	1.79132621	56.02	14.01	14	0	9	12.5	14340	23.7	8.8	72.6	12	13.3	41.2	47800	257	3.2	6	0.38	0.24	0.5	0.21	0.42	0.38	0.12	42.19	68.14	0.15	0.7	0.00308	0.94	0.000407	0.01	70.41	0.0067	7260	3.3	3764	3496	108	26.9	18.3	0.3	0.2	0.1	75.5	20.9	0.6	0.4	0.2	78.7	2.8	15.3	40	12.6
Stevens	Washington	53	65	53065	10789	5763	175	16727	64.50050816	34.45327913	1.04621271	87.75	5.32	16	14.1	6	10.6	15201	17.2	7.1	80.9	12.1	9.4	46.3	56800	306	14.7	4.3	0.41	0.22	0.43	0.23	0.39	0.23	0.12	95.46	166.35	5.35	2.51	0.01	5.35	0.00482	0.05	114.79	0.00767	40066	16.2	19940	20126	99	28.7	5.7	0.5	0.3	0.2	90	7.4	1	0.5	0.3	92.6	1.8	29.5	39.2	12.9
Okanogan	Washington	53	47	53047	8336	5511	134	13981	59.62377512	39.41778127	0.958443602	111.94	8.19	83	12.3	7	12.9	18253	21.5	12.3	71.3	12	10.5	41.9	50600	277	6.8	6.2	0.45	0.27	0.56	0.3	0.53	0.3	0.21	122.72	200.01	3.09	2.84	0.01	5.53	0.00322	0.03	168.55	0.0057	39564	7.5	19706	19858	99	27.7	11.5	0.4	0.3	0.1	75.3	13.2	0.8	0.5	0.2	77.9	14.4	18.6	38.2	14
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...

The complete data file is available here (1.2MB text CSV file).

Example: Bubble Chart

You can paste these data in any of the SOCR Analyses or Charts to obtain quantitative results of explore the data graphically. For instance, you can paste these data in the SOCR Bubble Chart, map the variables (Year --> X, ElectoralVote --> Y, Diff(Popular-Electoral)Vote --> Z) and click UPDATE Graph to obtain the image below. Notice how the close elections are represented by smaller bubbles near the 50% of the electoral vote line, as the difference between the popular and the electoral votes for tight elections are small.

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• SOCR Home page: http://www.socr.ucla.edu

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