A Guide to the ABS Census Datasets
Source:vignettes/articles/a-guide-to-abs-census-datasets.Rmd
a-guide-to-abs-census-datasets.Rmd
This guide explores the get_census_data
function in the scgElectionsAU package, designed to
retrieve Census data from the Australian Bureau of Statistics (ABS). The
function simplifies access to Census DataPacks for 2011, 2016, and 2021
at the Statistical Area Level 1 (SA1) geographic level. Census data
provides comprehensive demographic, social, and economic information
that can be linked to electoral data for analysis of voting patterns.
Below, we detail the function’s parameters, available datasets, usage
examples, and the context of ABS Census data collection.
Introduction to ABS Census Data
The Australian Bureau of Statistics (ABS) conducts the Census of Population and Housing every five years, collecting data on the key characteristics of people and dwellings in Australia. The Census provides a comprehensive snapshot of the nation, covering demographics, education, employment, income, housing, and more. The data is published through various products including DataPacks, Community Profiles, and GeoPackages.
The get_census_data
function provides access to Census DataPacks at the SA1 geographic
level. SA1s are the smallest geographic unit for which Census data is
publicly released, containing approximately 200-800 people. This
granular level of data is particularly useful for linking Census
demographics to electoral results.
The get_census_data Function
The get_census_data
function retrieves Census data from ABS DataPacks, downloading and
extracting specific tables from ZIP archives hosted on the ABS website.
Each table contains different Census variables organised by topic.
| Parameter | Description | Valid Options |
|---|---|---|
census_year |
The Census year to retrieve data for. | 2011, 2016, 2021 |
table |
The table identifier to retrieve (e.g., “G01”). See
abs_census_tables for available tables. |
See table descriptions below |
Census Profiles
The Census DataPacks contain different profile types depending on the year:
- General Community Profile (GCP): Used for 2016 and 2021 Census. Tables are prefixed with “G” (e.g., G01, G02). Contains approximately 60 tables covering all major Census topics.
- Basic Community Profile (BCP): Used for 2011 Census. Tables are prefixed with “B” (e.g., B01, B02). Contains approximately 46 tables with core Census variables.
Table Categories
The tables are organised by topic:
- Person Characteristics: Age, sex, marital status, ancestry, country of birth, language, religion
- Education: School attendance, highest year of school, qualifications, field of study
- Employment: Labour force status, occupation, industry, hours worked, income
- Family & Household: Family composition, household composition, number of children
- Housing: Dwelling structure, tenure, mortgage, rent, bedrooms, motor vehicles
- Health & Assistance: Long-term health conditions, need for assistance, unpaid care
Data Sources and Collection
The ABS collects Census data through the national Census conducted every five years. The data is processed, quality-checked, and released approximately 12-18 months after Census night. DataPacks are made available in CSV format within ZIP archives, organised by geographic level.
Key points about the data:
- Confidentiality: Small random adjustments are made to cell values to protect respondent confidentiality
- Geographic Structure: SA1s are the building blocks of the Australian Statistical Geography Standard (ASGS), nesting within SA2, SA3, SA4, and State/Territory boundaries
- Comparability: While many tables are consistent across years, some topics are only available in certain Census years (e.g., health conditions in 2021 only)
Looking Up Available Tables
The abs_census_tables dataset provides a reference of
all available tables and their descriptions:
Example: Finding Tables
# View all available tables
head(abs_census_tables)
#> table
#> 1 G01
#> 2 G02
#> 3 G03
#> 4 G04
#> 5 G05
#> 6 G06
#> description
#> 1 Selected person characteristics by sex
#> 2 Selected medians and averages
#> 3 Place of usual residence by place of enumeration on Census Night by age
#> 4 Age by sex
#> 5 Registered marital status by age by sex
#> 6 Social marital status by age by sex
#> census_years
#> 1 2016,2021
#> 2 2016,2021
#> 3 2016,2021
#> 4 2016,2021
#> 5 2016,2021
#> 6 2016,2021
# Find tables related to income
abs_census_tables[grep("income", abs_census_tables$description, ignore.case = TRUE), ]
#> table
#> 17 G17
#> 32 G32
#> 33 G33
#> 57 G57
#> 58 G58
#> 59 G59
#> 79 B17
#> 90 B28
#> 91 B29
#> description
#> 17 Total personal income (weekly) by age by sex
#> 32 Total family income (weekly) by family composition
#> 33 Total household income (weekly) by household composition
#> 57 Total family income (weekly) by labour force status of partners for couple families with no children
#> 58 Total family income (weekly) by labour force status of parents/partners for couple families with children
#> 59 Total family income (weekly) by labour force status of parent for one parent families
#> 79 Total personal income (weekly) by age by sex
#> 90 Total family income (weekly) by family composition
#> 91 Household income (weekly) by household composition
#> census_years
#> 17 2016,2021
#> 32 2016,2021
#> 33 2016,2021
#> 57 2016,2021
#> 58 2016,2021
#> 59 2016,2021
#> 79 2011
#> 90 2011
#> 91 2011
# Find tables available in 2021
abs_census_tables[grep("2021", abs_census_tables$census_years), ]
#> table
#> 1 G01
#> 2 G02
#> 3 G03
#> 4 G04
#> 5 G05
#> 6 G06
#> 7 G07
#> 8 G08
#> 9 G09
#> 10 G10
#> 11 G11
#> 12 G12
#> 13 G13
#> 14 G14
#> 15 G15
#> 16 G16
#> 17 G17
#> 18 G18
#> 19 G19
#> 20 G20
#> 21 G21
#> 22 G22
#> 23 G23
#> 24 G24
#> 25 G25
#> 26 G26
#> 27 G27
#> 28 G28
#> 29 G29
#> 30 G30
#> 31 G31
#> 32 G32
#> 33 G33
#> 34 G34
#> 35 G35
#> 36 G36
#> 37 G37
#> 38 G38
#> 39 G39
#> 40 G40
#> 41 G41
#> 42 G42
#> 43 G43
#> 44 G44
#> 45 G45
#> 46 G46
#> 47 G47
#> 48 G48
#> 49 G49
#> 50 G50
#> 51 G51
#> 52 G52
#> 53 G53
#> 54 G54
#> 55 G55
#> 56 G56
#> 57 G57
#> 58 G58
#> 59 G59
#> 60 G60
#> 61 G61
#> 62 G62
#> description
#> 1 Selected person characteristics by sex
#> 2 Selected medians and averages
#> 3 Place of usual residence by place of enumeration on Census Night by age
#> 4 Age by sex
#> 5 Registered marital status by age by sex
#> 6 Social marital status by age by sex
#> 7 Indigenous status by age by sex
#> 8 Ancestry by country of birth of parents
#> 9 Country of birth of person by age by sex
#> 10 Country of birth of person by year of arrival
#> 11 Proficiency in spoken English by year of arrival by age
#> 12 Proficiency in spoken English of parents by age of dependent children
#> 13 Language used at home by proficiency in spoken English by sex
#> 14 Religious affiliation by sex
#> 15 Type of education institution attending by sex
#> 16 Highest year of school completed by age by sex
#> 17 Total personal income (weekly) by age by sex
#> 18 Core activity need for assistance by age by sex
#> 19 Type of long-term health condition by age by sex
#> 20 Count of selected long-term health conditions by age by sex
#> 21 Type of long-term health condition by selected person characteristics
#> 22 Australian Defence Force service by age by sex
#> 23 Voluntary work for an organisation or group by age by sex
#> 24 Unpaid domestic work: number of hours by age by sex
#> 25 Unpaid assistance to a person with a disability or health condition or due to old age by age by sex
#> 26 Unpaid child care by age by sex
#> 27 Relationship in household by age by sex
#> 28 Number of children ever born
#> 29 Family composition
#> 30 Family composition and country of birth of parents by age of dependent children
#> 31 Family blending
#> 32 Total family income (weekly) by family composition
#> 33 Total household income (weekly) by household composition
#> 34 Number of motor vehicles by dwellings
#> 35 Household composition by number of persons usually resident
#> 36 Dwelling structure
#> 37 Tenure and landlord type by dwelling structure
#> 38 Mortgage repayment (monthly) by dwelling structure
#> 39 Mortgage repayment (monthly) by family composition
#> 40 Rent (weekly) by landlord type
#> 41 Dwelling structure by number of bedrooms
#> 42 Dwelling structure by household composition and family composition
#> 43 Selected labour force education and migration characteristics by sex
#> 44 Place of usual residence 1 year ago by sex
#> 45 Place of usual residence 5 years ago by sex
#> 46 Labour force status by age by sex
#> 47 Labour force status by sex of parents by age of dependent children for couple families
#> 48 Labour force status by sex of parent by age of dependent children for one parent families
#> 49 Highest non-school qualification: level of education by age by sex
#> 50 Highest non-school qualification: field of study by age by sex
#> 51 Highest non-school qualification: field of study by occupation by sex
#> 52 Highest non-school qualification: level of education by occupation by sex
#> 53 Highest non-school qualification: level of education by industry of employment by sex
#> 54 Industry of employment by age by sex
#> 55 Industry of employment by hours worked by sex
#> 56 Industry of employment by occupation
#> 57 Total family income (weekly) by labour force status of partners for couple families with no children
#> 58 Total family income (weekly) by labour force status of parents/partners for couple families with children
#> 59 Total family income (weekly) by labour force status of parent for one parent families
#> 60 Occupation by age by sex
#> 61 Occupation by hours worked by sex
#> 62 Method of travel to work by sex
#> census_years
#> 1 2016,2021
#> 2 2016,2021
#> 3 2016,2021
#> 4 2016,2021
#> 5 2016,2021
#> 6 2016,2021
#> 7 2016,2021
#> 8 2016,2021
#> 9 2016,2021
#> 10 2016,2021
#> 11 2016,2021
#> 12 2016,2021
#> 13 2016,2021
#> 14 2016,2021
#> 15 2016,2021
#> 16 2016,2021
#> 17 2016,2021
#> 18 2016,2021
#> 19 2021
#> 20 2021
#> 21 2021
#> 22 2021
#> 23 2016,2021
#> 24 2016,2021
#> 25 2016,2021
#> 26 2016,2021
#> 27 2016,2021
#> 28 2016,2021
#> 29 2016,2021
#> 30 2016,2021
#> 31 2016,2021
#> 32 2016,2021
#> 33 2016,2021
#> 34 2016,2021
#> 35 2016,2021
#> 36 2016,2021
#> 37 2016,2021
#> 38 2016,2021
#> 39 2016,2021
#> 40 2016,2021
#> 41 2016,2021
#> 42 2016,2021
#> 43 2016,2021
#> 44 2016,2021
#> 45 2016,2021
#> 46 2016,2021
#> 47 2016,2021
#> 48 2016,2021
#> 49 2016,2021
#> 50 2016,2021
#> 51 2016,2021
#> 52 2016,2021
#> 53 2016,2021
#> 54 2016,2021
#> 55 2016,2021
#> 56 2016,2021
#> 57 2016,2021
#> 58 2016,2021
#> 59 2016,2021
#> 60 2016,2021
#> 61 2016,2021
#> 62 2016,2021
# Find 2011 Census tables (B-prefix)
abs_census_tables[grep("^B", abs_census_tables$table), ]
#> table
#> 63 B01
#> 64 B02
#> 65 B03
#> 66 B04
#> 67 B05
#> 68 B06
#> 69 B07
#> 70 B08
#> 71 B09
#> 72 B10
#> 73 B11
#> 74 B12
#> 75 B13
#> 76 B14
#> 77 B15
#> 78 B16
#> 79 B17
#> 80 B18
#> 81 B19
#> 82 B20
#> 83 B21
#> 84 B22
#> 85 B23
#> 86 B24
#> 87 B25
#> 88 B26
#> 89 B27
#> 90 B28
#> 91 B29
#> 92 B30
#> 93 B31
#> 94 B32
#> 95 B33
#> 96 B34
#> 97 B35
#> 98 B36
#> 99 B37
#> 100 B38
#> 101 B39
#> 102 B40
#> 103 B41
#> 104 B42
#> 105 B43
#> 106 B44
#> 107 B45
#> 108 B46
#> description
#> 63 Selected person characteristics by sex
#> 64 Selected medians and averages
#> 65 Place of usual residence on Census Night by place of usual residence 5 years ago by sex
#> 66 Age by sex
#> 67 Registered marital status by age by sex
#> 68 Social marital status by age by sex
#> 69 Indigenous status by age by sex
#> 70 Ancestry by country of birth of parents
#> 71 Country of birth of person by age by sex
#> 72 Country of birth of person by year of arrival in Australia
#> 73 Proficiency in spoken English/language by year of arrival in Australia by sex
#> 74 Proficiency in spoken English of parents by age of dependent children
#> 75 Language spoken at home by sex
#> 76 Religious affiliation by sex
#> 77 Type of educational institution attending by age by sex
#> 78 Highest year of school completed by age by sex
#> 79 Total personal income (weekly) by age by sex
#> 80 Need for assistance with core activities by age by sex
#> 81 Voluntary work for an organisation or group by age by sex
#> 82 Unpaid domestic work: number of hours by age by sex
#> 83 Unpaid assistance to a person with a disability by age by sex
#> 84 Unpaid child care by age of carer by sex of carer
#> 85 Relationship in household by age by sex
#> 86 Number of children ever born by age of parent
#> 87 Family composition
#> 88 Family composition and country of birth of parents
#> 89 Family blending
#> 90 Total family income (weekly) by family composition
#> 91 Household income (weekly) by household composition
#> 92 Number of motor vehicles by dwellings
#> 93 Household composition by number of persons usually resident
#> 94 Dwelling structure
#> 95 Tenure type and landlord type by dwelling structure
#> 96 Mortgage repayment (monthly) by dwelling structure
#> 97 Mortgage repayment (monthly) by family composition
#> 98 Rent (weekly) by landlord type
#> 99 Dwelling structure by number of bedrooms
#> 100 Dwelling structure by household composition and family composition
#> 101 Selected labour force education and migration characteristics by sex
#> 102 Labour force status by age by sex
#> 103 Labour force status of parents by age of dependent children by family composition
#> 104 Non-school qualification: level of education by age by sex
#> 105 Non-school qualification: field of study by age by sex
#> 106 Non-school qualification: field of study by occupation by sex
#> 107 Non-school qualification: level of education by industry by sex
#> 108 Industry of employment by age by sex
#> census_years
#> 63 2011
#> 64 2011
#> 65 2011
#> 66 2011
#> 67 2011
#> 68 2011
#> 69 2011
#> 70 2011
#> 71 2011
#> 72 2011
#> 73 2011
#> 74 2011
#> 75 2011
#> 76 2011
#> 77 2011
#> 78 2011
#> 79 2011
#> 80 2011
#> 81 2011
#> 82 2011
#> 83 2011
#> 84 2011
#> 85 2011
#> 86 2011
#> 87 2011
#> 88 2011
#> 89 2011
#> 90 2011
#> 91 2011
#> 92 2011
#> 93 2011
#> 94 2011
#> 95 2011
#> 96 2011
#> 97 2011
#> 98 2011
#> 99 2011
#> 100 2011
#> 101 2011
#> 102 2011
#> 103 2011
#> 104 2011
#> 105 2011
#> 106 2011
#> 107 2011
#> 108 2011Available Tables and Examples
The following sections detail selected tables available for each
topic, including example usage of the get_census_data
function.
Person Characteristics
G01/B01: Selected Person Characteristics by Sex
The G01 (2016, 2021) or B01 (2011) table
provides a summary of key person characteristics, including:
- Age distribution (
Age_0_4_yr_M,Age_0_4_yr_F, etc.) - Country of birth (
Australia_M,Australia_F,Elsewhere_M,Elsewhere_F) - Indigenous status (
Indigenous_P_Tot_M,Indigenous_P_Tot_F) - Language spoken at home
- Citizenship and year of arrival
This table is useful for understanding the basic demographic profile of an area.
Example Usage:
g01 <- get_census_data(
census_year = 2021, # OR 2016
table = "G01" # OR "B01" (2011)
)Sample Data:
| SA1_CODE_2021 | Tot_P_M | Tot_P_F | Tot_P_P | Age_0_4_yr_M | Age_0_4_yr_F | Age_0_4_yr_P | Age_5_14_yr_M | Age_5_14_yr_F | Age_5_14_yr_P | Age_15_19_yr_M | Age_15_19_yr_F | Age_15_19_yr_P | Age_20_24_yr_M | Age_20_24_yr_F | Age_20_24_yr_P | Age_25_34_yr_M | Age_25_34_yr_F | Age_25_34_yr_P | Age_35_44_yr_M | Age_35_44_yr_F | Age_35_44_yr_P | Age_45_54_yr_M | Age_45_54_yr_F | Age_45_54_yr_P | Age_55_64_yr_M | Age_55_64_yr_F | Age_55_64_yr_P | Age_65_74_yr_M | Age_65_74_yr_F | Age_65_74_yr_P | Age_75_84_yr_M | Age_75_84_yr_F | Age_75_84_yr_P | Age_85ov_M | Age_85ov_F | Age_85ov_P | Counted_Census_Night_home_M | Counted_Census_Night_home_F | Counted_Census_Night_home_P | Count_Census_Nt_Ewhere_Aust_M | Count_Census_Nt_Ewhere_Aust_F | Count_Census_Nt_Ewhere_Aust_P | Indigenous_psns_Aboriginal_M | Indigenous_psns_Aboriginal_F | Indigenous_psns_Aboriginal_P | Indig_psns_Torres_Strait_Is_M | Indig_psns_Torres_Strait_Is_F | Indig_psns_Torres_Strait_Is_P | Indig_Bth_Abor_Torres_St_Is_M | Indig_Bth_Abor_Torres_St_Is_F | Indig_Bth_Abor_Torres_St_Is_P | Indigenous_P_Tot_M | Indigenous_P_Tot_F | Indigenous_P_Tot_P | Birthplace_Australia_M | Birthplace_Australia_F | Birthplace_Australia_P | Birthplace_Elsewhere_M | Birthplace_Elsewhere_F | Birthplace_Elsewhere_P | Lang_used_home_Eng_only_M | Lang_used_home_Eng_only_F | Lang_used_home_Eng_only_P | Lang_used_home_Oth_Lang_M | Lang_used_home_Oth_Lang_F | Lang_used_home_Oth_Lang_P | Australian_citizen_M | Australian_citizen_F | Australian_citizen_P | Age_psns_att_educ_inst_0_4_M | Age_psns_att_educ_inst_0_4_F | Age_psns_att_educ_inst_0_4_P | Age_psns_att_educ_inst_5_14_M | Age_psns_att_educ_inst_5_14_F | Age_psns_att_educ_inst_5_14_P | Age_psns_att_edu_inst_15_19_M | Age_psns_att_edu_inst_15_19_F | Age_psns_att_edu_inst_15_19_P | Age_psns_att_edu_inst_20_24_M | Age_psns_att_edu_inst_20_24_F | Age_psns_att_edu_inst_20_24_P | Age_psns_att_edu_inst_25_ov_M | Age_psns_att_edu_inst_25_ov_F | Age_psns_att_edu_inst_25_ov_P | High_yr_schl_comp_Yr_12_eq_M | High_yr_schl_comp_Yr_12_eq_F | High_yr_schl_comp_Yr_12_eq_P | High_yr_schl_comp_Yr_11_eq_M | High_yr_schl_comp_Yr_11_eq_F | High_yr_schl_comp_Yr_11_eq_P | High_yr_schl_comp_Yr_10_eq_M | High_yr_schl_comp_Yr_10_eq_F | High_yr_schl_comp_Yr_10_eq_P | High_yr_schl_comp_Yr_9_eq_M | High_yr_schl_comp_Yr_9_eq_F | High_yr_schl_comp_Yr_9_eq_P | High_yr_schl_comp_Yr_8_belw_M | High_yr_schl_comp_Yr_8_belw_F | High_yr_schl_comp_Yr_8_belw_P | High_yr_schl_comp_D_n_g_sch_M | High_yr_schl_comp_D_n_g_sch_F | High_yr_schl_comp_D_n_g_sch_P | Count_psns_occ_priv_dwgs_M | Count_psns_occ_priv_dwgs_F | Count_psns_occ_priv_dwgs_P | Count_Persons_other_dwgs_M | Count_Persons_other_dwgs_F | Count_Persons_other_dwgs_P |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 10102100701 | 179 | 128 | 305 | 6 | 9 | 7 | 12 | 5 | 18 | 16 | 12 | 23 | 0 | 6 | 3 | 21 | 12 | 36 | 13 | 15 | 30 | 31 | 16 | 49 | 36 | 28 | 57 | 28 | 18 | 48 | 14 | 10 | 22 | 0 | 4 | 5 | 165 | 125 | 283 | 10 | 8 | 22 | 3 | 0 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 7 | 127 | 94 | 219 | 30 | 29 | 56 | 144 | 110 | 252 | 13 | 11 | 23 | 152 | 115 | 262 | 6 | 3 | 7 | 10 | 5 | 19 | 5 | 9 | 15 | 0 | 0 | 0 | 4 | 4 | 12 | 46 | 56 | 106 | 18 | 8 | 32 | 55 | 34 | 87 | 11 | 5 | 16 | 4 | 0 | 8 | 0 | 0 | 0 | 154 | 122 | 275 | 13 | 10 | 26 |
G02/B02: Selected Medians and Averages
The G02 (2016, 2021) or B02 (2011) table
provides key summary statistics for each SA1, including:
- Median age (
Median_age_persons) - Median household income
(
Median_tot_hhd_inc_weekly) - Median personal income
(
Median_tot_prsnl_inc_weekly) - Median mortgage repayment
(
Median_mortgage_repay_monthly) - Median rent (
Median_rent_weekly) - Average household size (
Average_household_size) - Average number of bedrooms
(
Average_num_psns_per_bedroom)
This table is particularly useful for socioeconomic analysis and identifying areas by income levels.
G04/B04: Age by Sex
The G04 (2016, 2021) or B04 (2011) table
provides detailed age breakdowns by sex, with single-year age groups and
summary categories:
- Single year of age from 0 to 100+
- Male, Female, and Total counts for each age
This table is useful for detailed demographic analysis and population pyramids.
G07/B07: Indigenous Status by Age by Sex
The G07 (2016, 2021) or B07 (2011) table
provides Indigenous status by age groups:
- Aboriginal (
Aboriginal_M,Aboriginal_F,Aboriginal_P) - Torres Strait Islander (
Torres_Strait_Islander_M, etc.) - Both Aboriginal and Torres Strait Islander
- Non-Indigenous population
- Indigenous status not stated
G09/B09: Country of Birth by Age by Sex
The G09 (2016, 2021) or B09 (2011) table
provides country of birth information:
- Australia-born population
- Major countries of birth (England, New Zealand, China, India, etc.)
- Regional groupings (Oceania, Europe, Asia, Americas, Africa)
Education
G16/B16: Highest Year of School Completed by Age by Sex
The G16 (2016, 2021) or B16 (2011) table
provides school completion levels:
- Year 12 or equivalent
- Year 11 or equivalent
- Year 10 or equivalent
- Year 9 or equivalent
- Year 8 or below
- Did not go to school
Employment & Income
G17/B17: Total Personal Income (Weekly) by Age by Sex
The G17 (2016, 2021) or B17 (2011) table
provides personal income distribution:
- Income ranges (Negative/Nil, $1-$149, $150-$299, … $3000+)
- By age group and sex
- Not stated/not applicable
G46/B40: Labour Force Status by Age by Sex
The G46 (2016, 2021) or B40 (2011) table
provides employment status:
- Employed (full-time, part-time)
- Unemployed (looking for work)
- Not in the labour force
G60/B46: Occupation by Age by Sex
The G60 (2016, 2021) table provides occupation
categories (ANZSCO major groups):
- Managers
- Professionals
- Technicians and trades workers
- Community and personal service workers
- Clerical and administrative workers
- Sales workers
- Machinery operators and drivers
- Labourers
Note: 2011 uses table B46 for industry of employment.
Family & Household
G29/B25: Family Composition
The G29 (2016, 2021) or B25 (2011) table
provides family types:
- Couple family with children
- Couple family without children
- One parent family
- Other family types
Housing
G36/B32: Dwelling Structure
The G36 (2016, 2021) or B32 (2011) table
provides dwelling types:
- Separate house
- Semi-detached/townhouse
- Flat/apartment (by number of storeys)
- Other dwelling types (caravan, cabin, etc.)
G37/B33: Tenure Type and Landlord Type by Dwelling Structure
The G37 (2016, 2021) or B33 (2011) table
provides housing tenure:
- Owned outright
- Owned with a mortgage
- Rented (from real estate agent, state housing authority, private landlord, etc.)
- Other tenure types
Health & Assistance (2021 Only)
G19: Type of Long-Term Health Condition by Age by Sex
The G19 table (2021 only) provides health condition
data:
- Arthritis
- Asthma
- Cancer
- Dementia
- Diabetes
- Heart disease
- Kidney disease
- Lung condition
- Mental health condition
- Stroke
- Other long-term health conditions
Note: This table is only available for the 2021 Census.
Linking Census Data to Electoral Data
Census data at SA1 level can be linked to electoral data using the
ABS boundary correspondence files available through get_boundary_data.
The Votes by SA1 dataset from get_election_data
provides vote counts at SA1 level that can be joined with Census
demographics.
Example: Linking Census to Electoral Data
# Get 2021 Census income data
census_income <- get_census_data(census_year = 2021, table = "G02")
# Get SA1 voting data from 2022 election
voting_sa1 <- get_election_data(
file_name = "Votes by SA1",
date_range = list(from = "2022-01-01", to = "2023-01-01"),
category = "Statistics"
)
# Join datasets by SA1 code
# Note: Column names may need adjustment based on actual data structure
merged_data <- merge(
voting_sa1,
census_income,
by.x = "StatisticalAreaID",
by.y = "SA1_CODE_2021"
)