Australian Census data on all electorates

Source: R/data.R

A dataset containing demographic and other information about each electorate from the Australian Census of Population and Housing.

The data were obtained from the Australian Bureau of Statistics, and downloaded from https://www.censusdata.abs.gov.au/datapacks/. Electorate boundaries match those in place at the time of the relevant data.

Census data for non-census years has been imputed. For more details on this process, see the help vignette: vignette("imputing-census-data", package = "eechidna")

Data for 2004, 2007, 2013 and 2010 was updated in October 2019. The older versions can be found in the GitHub repository.

abs2001

abs2004

abs2006

abs2007

abs2010

abs2011

abs2013

abs2016

abs2019

Format

Data frames with the following variables, variables with an asterisk are only available in the 2001, 2006, 2011 and 2016 data sets.

  • UniqueID: Numeric identifier that links the electoral division with Census and other election datasets.

  • DivisionNm: Name of electorate

  • State: State containing electorate

  • Population: Total population of electorate

  • Area*: Area of electorate division in square kilometres

  • Age00_04: Percentage of people aged 0-4.

  • Age05_14: Percentage of people aged 5-9.

  • Age15_19: Percentage of people aged 15-19.

  • Age20_24: Percentage of people aged 20-24.

  • Age25_34: Percentage of people aged 25-34.

  • Age35_44: Percentage of people aged 35-44.

  • Age45_54: Percentage of people aged 45-54.

  • Age55_64: Percentage of people aged 55-64.

  • Age65_74: Percentage of people aged 65-74.

  • Age75_84: Percentage of people aged 75-84.

  • Age85plus: Percentage of people aged 85 or higher.

  • Anglican: Percentage of people affiliated with the Anglican denomimation

  • AusCitizen: Percentage of people who are Australian Citizens

  • AverageHouseholdSize: Average number of people in a household

  • BachelorAbv: Percentage of people who have completed a Bachelor degree or above

  • Born_Asia: Percentage of people born in Asia

  • Born_MidEast: Percentage of people born in the Middle East

  • Born_SE_Europe: Percentage of people born in South Eastern Europe

  • Born_UK: Percentage of people born in the United Kingdom

  • BornElsewhere: Percentage of people who were born overseas, outside of Asia, Middle East, South Eastern Europe and the UK

  • BornOverseas_NS*: Percentage of people who did not answer the question relating to birthplace

  • Buddhism: Percentage of people affiliated with the Buddhist religion

  • Catholic: Percentage of people affiliated with the Catholic denomimation

  • Christianity: Percentage of people affiliated with the Christian religion (of all denominations)

  • Couple_NoChild_House: Percentage of households made up of a couple with no children

  • Couple_WChild_House: Percentage of households made up of a couple with children

  • CurrentlyStudying: Percentage of people who are currently studying

  • DeFacto: Percentage of people who are in a de facto marriage

  • DiffAddress: Percentage of people who live at a different address to what they did 5 years ago

  • DipCert: Percentage of people who have completed a diploma or certificate

  • Distributive: Percentage of employed persons who work in wholesale trade, retail trade, transport, post or warehousing related industries

  • EmuneratedElsewhere: Percentage of people who receive emuneration outside of Australia, out of the total population plus overseas visitors

  • EnglishOnly: Percentage of people who speak only English

  • Extractive: Percentage of employed persons who work in extractive industries (includes mining, gas, water, agriculture, waste, electricity)

  • FamilyIncome_NS*: Percentage of people who did not answer the question relating to family income

  • FamilyRatio: Average number of people per family

  • Finance: Percentage of employed persons who work in finance or insurance related industries

  • HighSchool: Percentage of people who have completed high school

  • HighSchool_NS*: Rate of nonresponse for questions relating to high school completion

  • HouseholdIncome_NS*: Percentage of people who did not answer the question relating to household income

  • Indigenous: Percentage of people who are Indigenous

  • InternetAccess: Percentage of people with access to the internet

  • InternetAccess_NS*: Rate of nonresponse for questions relating to internal access

  • InternetUse: Percentage of people who used internet in the last week (2001 only)

  • InternetUse_NS*: Rate of nonresponse for questions relating to internet use (2001 only)

  • Islam: Percentage of people affiliated with the Islamic religion

  • Judaism: Percentage of people affiliated with the Jewish religion

  • Laborer: Percentage of employed persons who work as a laborer

  • Language_NS*: Rate of nonresponse for questions relating to language spoken at home

  • LFParticipation: Labor force participation rate

  • ManagerAdminClericalSales: Percentage of employed persons who work in management, administration, clerical duties and sales

  • Married: Percentage of people who are married

  • MedianAge: Median age

  • MedianFamilyIncome: Median weekly family income (in $)

  • MedianHouseholdIncome: Median weekly household income (in $)

  • MedianLoanPay: Median mortgage loan repayment amount (of mortgage payments, in $)

  • MedianPersonalIncome: Median weekly personal income (in $)

  • MedianRent: Median weekly rental payment amount (of those who rent, in $)

  • Mortgage: Percentage of dwellings that are on a mortgage

  • NoReligion: Percentage of people with no religion

  • OneParent_House: Percentage of households made up of one parent with children

  • Other_NonChrist: Percentage of people affiliated with a religion other than Christianity, Buddhism, Islam and Judaism

  • OtherChrist: Percentage of people affiliated with a denomination of the Christian religion other than Anglican or Catholic

  • OtherLanguageHome: Percentage of people who speak a language other than English at home

  • Owned: Percentage of dwellings that are owned outright

  • PersonalIncome_NS*: Rate of nonresponse for questions relating to personal income

  • Professional: Percentage of employed persons who work as a professional

  • PublicHousing: Percentage of dwellings that are owned by the government, and rented out to tenants

  • Religion_NS*: Rate of nonresponse for questions relating to religion

  • Rent_NS*: Rate of nonresponse for questions relating to rental costs

  • Renting: Percentage of dwellings that are being rented

  • SocialServ: Percentage of employed persons who work in education and training, healthcare, social work, community, arts and recreation

  • SP_House: Percentage of households occupied by a single person

  • Tenure_NS*: Rate of nonresponse for questions relating to tenure

  • Tradesperson: Percentage of employed persons who specialise in a trade

  • Transformative: Percentage of employed persons who work in construction or manufacturing related industries

  • Unemployed: Unemployment rate

  • University_NS*: Rate of nonresponse for questions relating to University

  • Volunteer: Percentage of people who work as a volunteer

  • Volunteer_NS*: Rate of nonresponse for questions relating to working as a volunteer

An object of class data.frame with 150 rows and 70 columns.

Examples

library(eechidna)
library(dplyr)
data(abs2001)
abs2001 %>% select(DivisionNm, MedianAge, Unemployed, NoReligion, MedianPersonalIncome) %>% head()
#>   DivisionNm MedianAge Unemployed NoReligion MedianPersonalIncome
#> 1   ADELAIDE        37   7.779892  19.673954                349.5
#> 2      ASTON        34   4.722118  18.054206                449.5
#> 3   BALLARAT        35   8.957760  18.771159                349.5
#> 4      BANKS        37   5.301010   9.693882                349.5
#> 5     BARKER        38   6.330406  21.711487                349.5
#> 6     BARTON        37   5.802002  10.540373                449.5

# Join with two-party preferred voting data
library(ggplot2)
data(tpp01)
election2001 <- left_join(abs2001, tpp01, by = "UniqueID")
# See relationship between personal income and Liberal/National support
ggplot(election2001, aes(x = MedianPersonalIncome, y = LNP_Percent)) +
    geom_jitter() +
    geom_smooth(method='lm')
#> `geom_smooth()` using formula = 'y ~ x'