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List of datasets available in TableBuilder, summary information, links to publications and data item lists
TableBuilder datasets are grouped into themed data series. You can subscribe to one or more data series in TableBuilder. When you subscribe to a data series, you and all members of your organisation can access all of the datasets within that data series.
Use Ctrl+F (Windows) or Command+F (Mac) to search this list.
|TableBuilder||Description||Data item list||Release date|
|Aboriginal and Torres Strait Islander Peoples|
|National Aboriginal and Torres Strait Islander Health, 2018-19||Collects information on the health and wellbeing of Aboriginal and Torres Strait Islander people.||Data items||26/03/2020|
|National Aboriginal and Torres Strait Islander Health Survey, Core Content - Risk Factors and Selected Health Conditions, 2012-13||Collects information on the health and wellbeing of Aboriginal and Torres Strait Islander people.||Data items||28/07/2015|
|National Aboriginal and Torres Strait Islander Health Survey, Detailed Conditions and Other Health Data, 2012-13||Collects information on the health and wellbeing of Aboriginal and Torres Strait Islander people.||Data items||28/08/2014|
|Aboriginal and Torres Strait Islander Health Survey, Nutrition and Physical Activity, 2012-13||Provides key health indicators of the Aboriginal and Torres Strait Islander population. Demographic information includes education, employment, income, languages and household information. Nutrition and physical activity information includes sedentary behaviour, selected health conditions, biomedical information, health risk factors and food.||Data items||17/07/2015|
|National Aboriginal and Torres Strait Islander Social Survey, 2014-15||Presents information on a range of demographic, social, environmental and economic characteristics of Aboriginal and Torres Strait Islander people, including personal and household characteristics.||Data items||27/05/2016|
|Australian Census Longitudinal Data|
|Australian Census Longitudinal Dataset, 2006-2011-2016||Uses data from the Census of Population and Housing to build a rich longitudinal picture of Australian society. The ACLD can uncover new insights into the dynamics and transitions that drive social and economic change over time, and how these vary for diverse population groups and geographies.||Data items||18/09/2019|
|Australian Census Longitudinal Dataset, 2011-2016||Uses data from the Census of Population and Housing to build a rich longitudinal picture of Australian society. The ACLD can uncover new insights into the dynamics and transitions that drive social and economic change over time, and how these vary for diverse population groups and geographies.||Data items||18/09/2019|
|Businesses in Australia|
|Businesses in Australia, 2018-19 (free)||Contains all businesses that were active in the Australian economy in the 2018-19 financial year. The data are sourced from the ABS’ integrated product, the Business Longitudinal Data Analysis Environment (BLADE) which combines taxation and other administrative data.||Data items||30/04/2020|
|Census of Population and Housing|
|Census of Population and Housing, 2006 Basic (free) and Pro (subscribed)||All Census records for occupied private dwellings with their associated family and person records, and persons from non-private dwellings together with a record for the associated non-private dwelling. Includes age, marital status, citizenship and ancestry, languages, employment and income, journey to work, education, geography, family composition, household and dwelling information.||Data items||24/08/2009|
|Census of Population and Housing, 2011 Basic (free) and Pro (subscribed)||All Census records for occupied private dwellings with their associated family and person records, and persons from non-private dwellings together with a record for the associated non-private dwelling. Includes age, marital status, citizenship and ancestry, languages, employment and income, journey to work, education, geography, family composition, household and dwelling information.||Data items||15/08/2012|
|Census of Population and Housing, 2016 Basic (free) and Pro (subscribed)||All Census records for occupied private dwellings with their associated family and person records, and persons from non-private dwellings together with a record for the associated non-private dwelling. Includes age, marital status, citizenship and ancestry, languages, employment and income, journey to work, education, geography, family composition, household and dwelling information.||Data items||06/08/2019|
|Census of Population and Housing: Estimating Homelessness, 2016||Presents detailed estimates of the prevalence of homelessness in TableBuilder from the ABS' Census of Population and Housing for 2016||Data items||16/08/2019|
|Census of Population and Housing: Index of Household Advantage and Disadvantage, 2016||The experimental Index of Household Advantage and Disadvantage (IHAD) summarises relative socio-economic advantage and disadvantage for households, using the 2016 Census of Population and Housing.||Data items||29/10/2019|
|Childhood Education and Care|
|Childhood Education and Care, 2017||Collected every three years and is designed to provide a range of information about children aged 0–12 years and their families. The information collected includes the child care arrangements used by parents to care for their children, use of formal and informal care, cost and duration of the care and the attendance of children at preschool programs and other early childhood learning activities.||Data items||23/04/2018|
|Crime and Safety|
|Crime Victimisation, 2012-13||Provides data about victims for a selected range of personal and household offences||Data items||28/04/2014|
|Personal Safety, 2016||Provides data on the nature and extent of violence experienced by men and women since the age of 15||Data items||08/11/2018|
|Cultural Activities, 2017-18||Designed to provide annual statistics about participation and attendance in selected cultural activities.||28/05/2019|
|Disability, Ageing and Carers|
|Disability, Ageing and Carers, 2012||Provides data on people with a disability, people aged 65 years or more, and assistance providers. Data items include household, family, income, person, conditions, restrictions, specific and broad activities, recipients, and assistance providers.||Data items||08/07/2014|
|Disability, Ageing and Carers, 2015||Provides data on people with disability, older people (aged 65 years or more) and people who care for people with disability or older people. Data items include household, family, income, person, conditions, restrictions, specific and broad activities, recipients, and assistance providers.||Data items||18/10/2016|
|Disability, Ageing and Carers, 2018||Provides data on people with disability, older people (aged 65 years or more) and people who care for people with disability or older people. Data items include household, family, income, person, conditions, restrictions, specific and broad activities, recipients, and assistance providers.||Data items||20/11/2019|
|Education and Work|
|Education and Work, 2011||Includes data on labour force characteristics, participation in study, educational institution, educational attainment, and selected characteristics of apprentices and trainees.||Data items||15/05/2012|
|Education and Work, 2012||Includes data on labour force characteristics, participation in study, educational institution, educational attainment, and selected characteristics of apprentices and trainees.||Data items||28/05/2013|
|Education and Work, 2013||Includes data on labour force characteristics, participation in study, educational institution, educational attainment, and selected characteristics of apprentices and trainees.||Data items||28/03/2014|
|Education and Work, 2014||Data items||19/05/2015|
|Education and Work, 2015||Data items||22/02/2016|
|Education and Work, 2016||Data items||29/11/2016|
|Education and Work, 2017||Data items||06/11/2017|
|Education and Work, 2018||Data items||08/11/2018|
|Education and Work, 2019||Data items||13/11/2019|
|Education and Work, 2020||Data items||11/11/2020|
|Education and Work, 2021||Data items||09/11/2021|
|Employee Earnings and Hours|
|Employee Earnings and Hours, 2018||Detailed earnings and hours statistics for characteristics such as industry, occupation, sex, age, full-time/part-time, and method of setting pay||Data items||11/09/2020|
|Employee Earnings and Hours, 2021||Detailed earnings and hours statistics for characteristics such as industry, occupation, sex, age, full-time/part-time, and method of setting pay||Data items||29/03/2022|
|General Social Data|
|General Social Survey, 2014||Includes data on demographic characteristics, health and disability, housing, education, work, income, financial stress, assets and liabilities, information technology, transport, voluntary work, family and community, homelessness, crime and participation in sport and recreational activities.||Data items||23/09/2015|
|Income, Housing, Wealth and Expenditure|
|Income and Housing, 2015-16||Provides estimates of income, wealth and housing. These measures can be classified by a range of household, income unit, person or loan characteristics.||Data items||29/06/2018|
|Income and Housing, 2017-18||Provides estimates of income, wealth and housing. These measures can be classified by a range of household, income unit, person or loan characteristics.||Data items||24/07/2019|
|Barriers and Incentives to Labour Force Participation, Retirement and Retirement Intentions, 2018-19||Provides detailed information on characteristics of people who are not participating, or not participating fully, in the labour force and the factors that influence them to join or leave the labour force, and on information on retirement trends, the factors which influence decisions to retire, and the income arrangements that retirees and potential retirees have made to provide for their retirement.||Data items||28/08/2020|
|Characteristics of Employment, 2014 to 2021||Weekly earnings of employees, casual workers, independent contractors, trade union membership, labour hire, job flexibility, job security||Data items||14/12/2021|
|Jobs in Australia, annually 2011-12 to 2018-19||Jobs in Australia provides statistics from the Longitudinal Employer Employee Database (LEED) to enable simultaneous analysis of met supply and demand in the Australian labour market. The LEED is a cross-sectional database, which uses administrative tax data to incorporate information from all employees and employers in Australia.||Data items||17/12/2021|
|Labour Force Status of Families, annually 2009-2018, quarterly from March 2019||Enables detailed analysis of how families engage with the labour market and provides statistics on broad family dynamics including the number and age of children in the household.||Data items||11/10/2021|
|Participation, Job Search and Mobility, annually from 2015||Provides statistics relating to people looking for work, finding work, losing jobs, changing jobs, or the reasons why people are not working or looking for work.||Data items||07/07/2021|
|Australian Census and Migrants, 2011, 2016||Contains linked data from the 2016 Census of Population and Housing and from the Department of Social Services Permanent Migrant Database (PMD).||Data items||15/10/2019|
|Australian Census and Temporary Entrants, 2016||Contains linked data from the 2016 Census of Population and Housing and data on temporary visa holders from the Department of Home Affairs.||Data items||15/10/2019|
|Characteristics of Recent Migrants, 3-yearly from 2010||Enables analysis of data about migrants arriving in the last 10 years including employment outcomes related to visa, birth country and education.||Data items||12/06/2020|
|Census of Motor Vehicles, annually from 2013 to 2021||Includes all vehicles registered with a state, territory or motor vehicle authority for unrestricted use on public roads.||Data items||27/08/2021|
|Motor Vehicle Use, 2016, 2018, 2020||Estimates of road registered vehicle usage including; total and average kilometres travelled, tonnes carried, tonne-kilometres travelled and fuel use.||Data items||01/02/2021|
|Road Freight Movements, 2014||Statistics on tonnes, tonne-kilometres, total distance travelled of freight moved in Australia between selected ASGS statistical areas by road||Data items||20/09/2017|
|National Health Survey|
|National Health Survey, 2011-12, 2014-15, 2017-18||Includes demographic and geographic information, health risk factors, health conditions and health actions. Additionally, biomedical data for NHS respondents who agreed to participate.||Data items||30/04/2019|
|Australian Health Survey, Core Content - Risk Factors and Selected Health Conditions, 2011-12||Provides data for the common topics and combined samples of the National Health Survey and National Nutrition and Physical Activity Survey 2011-12, components of the Australian Health Survey (AHS) 2011-12. The focus of this current release is on the Core Content, primarily health risk factors and selected health conditions, as well as data from the National Health Measures Survey, the biomedical component of the AHS||Data items||30/04/2014|
|Nutrition and Physical Activity|
|Australian Health Survey, Nutrition and Physical Activity, 2011-12||Includes demographic and geographic information, health risk factors, health conditions and health actions. Additionally, biomedical data for NHS respondents who agreed to participate.||Data items||06/11/2015|
|Australian Health Survey, Core Content - Risk Factors and Selected Health Conditions, 2011-12||Provides data for the common topics and combined samples of the National Health Survey and National Nutrition and Physical Activity Survey 2011-12, components of the Australian Health Survey (AHS) 2011-12. The focus of this current release is on the Core Content, primarily health risk factors and selected health conditions, as well as data from the National Health Measures Survey, the biomedical component of the AHS||Data items||30/04/2014|
|Patient Experiences, 2016-17||Data on access and barriers to, and experiences of, health care services including GPs, specialists, dental professionals, hospitals and EDs.||Data items||12/04/2018|
|Preschool Education, annually from 2016||Contains statistics on children enrolled in and attending a preschool program across Australia and is derived from administrative data provided by state and territory and Australian Government education departments and the Catholic Education Office of the Archdiocese of Canberra and Goulburn.||Data items||28/5/2021|
|Qualifications and Work|
|Qualifications and Work, 2018-19||Presents detailed information about the educational history of people and the relevance of each qualification to their working lives.||Data items||29/09/2020|
|Sport and Physical Recreation|
|Participation in Sport and Physical Recreation, 2013-14||Data on persons aged 15 years and over who participated in sport and physical activities as players, competitors or physically undertook an activity.||Data items||18/02/2015|
|Work-Related Injuries, 2017-18||People who experienced a work-related injury or illness, including type of injury, job details and work-related injury rates.||Data items||27/09/2019|
|Work-Related Training and Adult Learning|
|Work-Related Training and Adult Learning, 2016-17||Provides annual statistics about formal study and non-formal learning, with a focus on work-related training and personal interest learning.||Data items||17/01/2018|
|Work-Related Training and Adult Learning, 2021||Provides annual statistics about formal study and non-formal learning, with a focus on work-related training and personal interest learning.||Data items||11/03/2022|
Registering and logging into TableBuilder, introducing the home page
Register and log in
If you forget your credentials, you can use the 'forgotten' links on the log in page to retrieve your user ID or reset your password. You need access to the email address you registered with and your secret question and answer.
- if you can't remember your secret question and answer
- to unlock your account if you attempt to log in with the wrong password several times
- if you have changed your email address
Home page features
Once logged in, the TableBuilder home page displays information in three panels.
This is the catalogue of datasets that you have access to. See How to access to subscribe to additional data series.
Saved and predefined tables
When a dataset is selected in the first panel, your saved tables associated with that dataset are displayed, as well as any pre-prepared tables (predefined tables) that have been provided.
This provides general information about TableBuilder and specific information about the selected dataset.
1. Datasets panel
This panel shows all the dataset folders that you have access to:
- clicking the arrow expands the folder to display sub-folders (triangle icon) and datasets (cube icon)
- select a dataset with a single click to display any saved or predefined tables for this dataset in the middle panel, and additional information about the dataset in the third panel
- double-click on a dataset to open it and start creating a new table
2. New table button
Select a dataset in the Datasets panel, then click this button to start creating a new table. Alternatively, double-click on the dataset to open it.
3. Saved and predefined tables panel
This panel shows your saved tables and any predefined tables that are available for the selected dataset.
- Predefined tables are accessible to all users.
- Saved tables are tables you have saved and are only accessible by you.
When a dataset is selected in the Datasets panel, you can double-click on a table in the Saved and predefined tables panel to open and modify it.
4. Open table button
Select a table in the Predefined tables panel, then click Open Table to use and modify the selected table. Alternatively, double-click on the table to open it.
5. Description panel
The panel on the right provides general information about TableBuilder.
When a dataset is selected in the first panel and there is further information available about the dataset or its predefined tables, the information displays in the description panel.
6. Header bar menus
When you first open your TableBuilder session, the Datasets menu (the home page) is the only available menu. When you are on other screens, you can click on this menu to return to the home page.
After you have opened a dataset, additional menus appear for:
- Table view - select this menu to return to the table view for the dataset you have most recently opened
- Graph view - this menu is only selectable if you have created a table in Table view
- Map view - this is only selectable if the dataset you have open has geography enabled for mapping, and you have included mappable geographic variables in your table
Use the Search box in the top right corner to search across all datasets that you have access to. The results show all datasets that include the search term in any field, including:
- dataset names
- your saved table names
- predefined tables
8. TableBuilder user guide
Access this user guide at any time by clicking on the question mark icon on the top right corner of the screen. The user guide opens in a new tab so you can click between the user guide and your session.
9. TableBuilder tour
The TableBuilder tour opens when you log into TableBuilder for the first time. You can take the tour again at any time by clicking on the three vertical dots menu in the top right of the screen.
10. Logging out
- Log out is located at the top right of the screen in the three vertical dots menu.
- Before logging out, save any data you want to retain.
- Logging out completely closes your TableBuilder session. If you only close your browser or tab without logging out, your session stays active until it times out.
Taking the tour
When you open TableBuilder for the first time, a tour of TableBuilder features opens. The tour takes you through the home page features, saved tables, opening a dataset, creating a table, and getting started for graphs and maps.
To take the tour again, you can open it from the three vertical dots menu in the top right of the screen.
Some datasets have tables that have already been created and are available to all users. These are known as predefined tables. If there are predefined tables available for a dataset, they are displayed in the middle panel of the TableBuilder homepage when the dataset is selected in the first panel.
Opening a predefined table displays the table with selected variables and its data. Predefined tables can also used as a starting point and be further modified as required. Predefined tables can be saved, graphed, mapped or downloaded like any other table. When predefined tables are opened, the data is automatically retrieved, so predefined tables for large datasets may take some time to open.
1. For example, the Census TableBuilder Basic dataset 2016 Census - Employment, Income and Education has six predefined tables available for users.
2. Double clicking on the 2016 Census Total Personal Income (weekly) by Sex predefined table opens a table showing State by Sex by Total Personal Income (weekly) with data already retrieved.
If there has been no activity in TableBuilder for 30 minutes, the session times out. The following message displays and you need to log in again to continue working. Any unsaved data is lost.
Dataset help information
Access dataset information and data item lists, understand what is being counted in a table
When a dataset is open, there are a number of ways to find out more information about the dataset and variables.
Information is available via the i link next to the dataset title in the Table view.
- For Census datasets, the i link opens Census Dictionary information.
- For all other datasets, the i link opens the dataset's associated microdata publication. This includes the full data item list in the Data downloads section (or in the Downloads tab in older publications).
i links open in a new tab or window so you can switch between your table and the help information.
Census TableBuilder variables also have variable specific information in the Census Dictionary. Click on the i link next to the variable name in the table to open the Census Dictionary description. Data quality information for Census variables can be found using the Data Quality Statements linked to corresponding entries in the Census Dictionary. These statements include information about non-response rates and any known data quality issues for each Census variable.
Census variables and geographies
To maintain the confidentiality of respondents and to ensure the output of quality data, some system restrictions have been implemented. These restrictions include:
- not allowing you to download individual records
- perturbing the output in your tables
- preventing the cross-tabulation of certain variables.
You need to agree to Conditions of use when using TableBuilder. The ABS may impose a limit on the maximum number of tables per user.
Understanding what is being counted in a table
The type of record you are counting is displayed at the top of the table.
Census datasets provide information about persons, families and dwellings. Select the appropriate dataset based on what you want to count.
Examples of records that may be counted in TableBuilder include:
- motor vehicles
Census of Population and Housing datasets
Place of usual residence - counting persons and families
This is the place where a person usually lives. It may or may not be the place where the person was counted on Census Night. Usual residence data less likely to be influenced by seasonal factors such as school holidays and snow seasons, and provide information about the usual residents of an area. It is often used by government agencies when allocating funds to regions.
Place of enumeration (location on census night) - counting persons, families and dwellings
Census place of enumeration is a count of every person in Australia on Census Night, based on where they were located on that night. This may or may not be the place at which they usually live. It includes people who are on long-distance trains, buses or aircraft, or on board vessels in or between Australian ports. It includes overseas visitors.
This type of count provides a snapshot of an area on Census night. Although the Census is timed to attempt to capture the typical situation, holiday resort areas such as the Gold Coast and snow fields may show a large enumeration count compared with the usual residence count.
Persons, 15 years and over
The Census also provides information about the working population. This consists of persons aged 15 years and over who were employed in the week prior to Census night. The data collected relate to all workers, regardless of the hours worked. The Journey to Work data on which this is based are used by transport authorities, associated bodies, organisations and other interested people to plan public transport systems, and for the development and release of residential and commercial land.
Building a basic table
Open a dataset, using and removing rows and columns, variables and categories
Open a dataset
On the TableBuilder home page, click the triangle to expand the folder to display the datasets that you have access to. Either double-click the dataset or select the dataset and use the New table button at the bottom of the panel to start creating a new table.
This opens the Table view where you can build and modify tables. There are two panels:
- the left panel shows the variables and categories that can be added to your table
- the right panel is where you build your table
Add variables and categories to a table
Variables and categories
When a dataset is opened in Table view, the left panel shows a list of variables and categories included in that dataset that can be added to your table.
- Variables (or data items) are characteristics about the records in the dataset. For example, Age or Indigenous status (variables) are characteristics about people (records). There may be multiple similar variables in a dataset, such as Age in single years and Age in 5 year groupings.
- Categories are the responses to the questions that have been provided by the respondent. Each variable has multiple categories. For example, the categories of the variable Age in single years may be 0, 1, 2, 3 etc. Categories must be complete (include options for all possible responses) and mutually exclusive (not overlap).
Related variables are grouped together in folders. Click on the folders to view the available variables and categories.
In most cases, the default setting is to show the left panel. To hide the left panel select the < arrow at the top of the menu. To show it again select the > arrow.
Hide left panel option
Show left panel option
Rows, columns, wafers and filters
To create a table, select a variable from the list in left panel and add it to the table in the rows, columns, wafers, or filters.
- Rows are horizontal displays of data, with the row headings appearing down the left side of the table.
- Columns are vertical displays of data, with the column headings appearing across the top of the table.
- Wafers are where data is displayed in multiple layers of a table. This can be a useful option for including a time or geography variable for example. When tables using wafers are exported or downloaded to a spreadsheet, each wafer appears on a different tab. Wafers may also be called layers or sheets.
- Filters are used to limit the data in a table to only display data for specific variable categories. For example, by including New South Wales in a filter, the table results displays counts for New South Wales only, rather than the whole of Australia. See Add and remove a filter.
Selecting variables and categories
There are three ways to select variables or categories to be added to a table:
- Open the variable folder in the left panel and click in the tick boxes for the categories. Use the Add to Row, Column, Filter or Wafer buttons at the top of the left panel. This option is useful for selecting a few categories of a variable. You can also use Shift-click to select multiple categories at once.
- Drag the variable or category name to the right. A pop-up menu appears with options for adding to Column, Row or Wafer. Dropping the variable onto one of these options selects all categories of the variable at once. Dropping a category adds that category only.
- Click the arrow at the end of the variable name to show the Select a level drop-down list. Click on the variable in the drop-down list to select all categories of the variable at once. Hierarchical variables may have multiple options for selection, e.g. Age in 10 year ranges, Age in 5 year ranges and Age in single years. Then use the Add to Row, Column, Filter or Wafer buttons at the top of the panel.
Using the 2016 Census - Cultural Diversity dataset we create a table with Age in Ten Year Groups in the rows and Registered Marital Status in the columns.
1. In the left panel, click the Selected Person Characteristics folder to expand the list of available variables.
2. Expand the Age in Ten Year Groups folder to see the list of categories.
3. Select the tick boxes next to the categories to be added to the table, in this example 20-29, 30-39, 40-49, 50-59.
4. Click the add to Row button.
5. TableBuilder adds the selected categories to the table. Categories that are in your table are shown in bold in the left panel.
6. When the first variable is added to the table, TableBuilder also adds a default summation (what the table is counting). For 2016 Census - Cultural Diversity dataset, the default summation is counting the number of persons at their place of usual residence. See Types of records being counted in a Table and Summation options for continuous variables sections for more detail on summation.
7. Next, add the Registered Marital Status variable to the column headings. Using the drag and drop shortcut, all the available categories in a particular variable can be added to the table. The Column, Row and Wafer options appear. Drop onto Column.
8. TableBuilder adds all the available categories from Marital Status to the column headings.
9. Click Retrieve data to populate the table with data.
10. The table is now populated with data. The cell count for the table is displayed above the table.
'Select a level' drop-down list
Another way to add a variable to a table is to use the 'Select a level below' to select all drop-down list to quickly select all categories. This is useful when there are a large number of categories or for hierarchical variables.
1. Click the arrow to the right of the geographic area variable. A drop-down list displays. Main Statistical Area Structure (Main ASGS) is a hierarchical variable so there are multiple options (levels) that you can choose.
2. Selecting State from the drop-down list includes all the available categories at this level in the hierarchy. When the Main Statistical Area Structure variable is expanded it can be seen that TableBuilder has selected all the available categories at this level in the hierarchy. At the top of the hierarchy TableBuilder indicates the number of categories are currently selected (in this case, 9 categories).
3. Click the Add to Row button. TableBuilder adds all the selected categories to the row headings.
4. Click Retrieve data to populate the table.
Shift-click to select multiple variable categories
Another way to quickly select multiple categories is to use Shift-click. This selects a range of variable categories. For example, to add all categories of the Age variable from 0 to 18.
1. In the left panel, expand the Age variable and select the first category in your range (in this case, 0).
2. Hold down the Shift key and click the last category in the range (in this case, 18).
3. TableBuilder automatically selects all the categories in between.
4. Click Add to Row or Add to Column to add the categories to the table.
Move a variable to a different axis
To swap the columns, rows and wafers, drag and drop the variable names from within the table.
1. Starting with a table with Sex in the rows and state in the columns, drag and drop the Sex variable name onto the column headings. Drop the variable once the column header area turns light blue.
2. This adds Sex to the column headings. As Sex was dragged to the space above State, Sex and State are displayed as nested variables. For more information about nesting, see Add multiple variables to rows columns or wafers.
3. Now drag the State variable name onto the row. Drop the variable once the row header area turns light blue.
4. The table updates to show State in the rows.
5. Variables can also be dragged and dropped to the Wafer area.
6. The table shows Sex in the Wafer and State in the rows. Click the Wafer drop down menu to select a different category in this case, Male, Female or Total can be selected.
Remove a variable
The easiest way to remove an entire variable from the table is to drag and drop the variable name onto the Remove icon above the table. Use drag and drop for row, column or wafer variables.
1. Drag and drop the Marital Status variable name onto Remove.
2. TableBuilder removes the entire variable from the table.
Instead of removing an entire variable, you can use the Remove button at the top of the left panel to remove one or more categories. If categories that have been removed are subsequently re-added, they appear in the order that they were added, not their original order.
For example to remove all the categories of the Marital Status variable from the table:
1. Click the folder icon to expand Marital Status. The categories that are currently in the table appear in bold (in this case, all the categories are in the table).
2. Select the tick boxes for the categories to be removed from the table (for example Not applicable), then click Remove. TableBuilder removes these categories from the table.
3. Click Retrieve data again to refresh the data in the table.
Clear the table
1. Click the Clear table icon.
2. TableBuilder confirms the deletion of the table. Click OK. TableBuilder clears the table.
To choose a different dataset, click the Datasets tab in the blue header menu. This returns you to the TableBuilder home page.
If you can't see the dataset you are interested in, your organisation may not have subscribed to the data series you are trying to access. Check which datasets your organisation has access to in Registration Centre, using the same user ID and password that you use for TableBuilder. To subscribe to additional data series, see How to access. For a list of all data series and datasets, see Topics.
Switching to another dataset clears the current table. If you want to use the current table again, save the table before switching datasets.
Building advanced tables
Hierarchical variables, adding multiple variables, using wafers and filters
Datasets may include variables that are represented as hierarchies. This is where there are different levels of a variable that can be displayed. Geographic variables are often available as hierarchical variables. Examples:
- Greater Capital City Statistical Areas (GCCSA) contains a hierarchy of several levels, with STATE at the top level, GCCSA at the next level, and Statistical Area 4 (SA4) at the lowest level.
- Age variable may contain 10 year groupings at the top level, with 5 year groupings at the next level, and individual ages at the lowest level.
Beside each variable in the left panel of the Table view you can select the > button to see how many levels a variable includes. Selecting one of items in the Select a level below list selects all categories at that level. All categories for single level variables can also be selected this way.
The highest level of the hierarchical variable is always displayed first in the list, the next level is displayed second, and the most detailed level is last.
Click on the > next to the variable name. Selecting SA4 here selects all SA4s in all States.
Click on the > next to one of the State level categories. Selecting SA4 here selects all SA4s in that State only.
Click on the > next to one of the Greater Capital City Statistical Area (GCCSA) level categories. Selecting SA4 here selects all SA4s in that GCCSA only.
Changing the level of a hierarchical variable in a table
For hierarchical variables, drill down within the table. By clicking on the underlined category name, the next level down of the variable displays. For example, clicking on New South Wales displays the next level down: Greater Sydney, Rest of NSW, etc.
Display of next level down for New South Wales.
Collapse back up to the State level by clicking on the double arrow. This displays all variables for the higher level.
Add a variable to wafers
You can also add variables to the third dimension of a table - wafers.
1. Using our earlier example table, add the Country of Birth of Person variable to the wafer. Click and drag Country of Birth towards the table. Drop the variable onto Wafer. Alternatively, you can use the Add to wafer button at the top. A separate wafer (layer) for each country is added to the table.
2. Retrieve data.
3. The wafer displays above the table. The wafer for all people born in Oceania is displayed. Change the displayed wafer by using the drop-down menu next to Wafers.
4. To remove a variable from the wafer, click on the X next to the wafer variable or drag the wafer variable to the Remove icon.
Add multiple variables to rows, columns or wafers
You can add multiple variables to a table so that the variables are nested within rows, columns or wafers. Nesting is where multiple variables are on the same axis, such as Age and Marital status in the Row axis. The maximum number of variables that can be nested on an axis is 10 variables. This is also the maximum number of variables that can be included in a table. For performance reasons it is better to have less than 10 variables in your table, particularly for large classifications or datasets.
Some features are not available when there are nested variables in a table. For example, mapping is not available if a geographic field is nested with another variable. A geographic variable can only be mapped if all the other variables are nested on the opposite axis to the geographic variable (or in the wafer).
Once you have created your table, you can drag variables to change the order of nesting within a row, column or wafer. You can also drag variables between the rows, columns and wafers to rearrange your table.
To nest variables in a table, add variables one at a time to the row, column or wafer. Variables can be added using the drag and drop method or the Add to Row, Column or Wafer buttons.
- Select Age categories between 15 and 29 years and Add to row.
- Then select Indigenous Status, and Add to row.
- Add Sex to column and retrieve data.
- The variables Age and Indigenous Status display as nested variables.
Add and remove a filter
When filters are applied to a table, only records that match the filters are included in the results. Filters are an alternative to selecting and including specific variable categories only in the table, and can be removed to show all categories again.
1. The following table shows Labour Force Status (LFSP) by State with no filters applied.
2. Select a single category and click Add to Filter.
3. TableBuilder adds the filter to the Filters list above the table.
4. Additional categories can be added to the filter if necessary. However, only one category can be added from any given variable. For example Sex - Male and Sex - Female cannot both be added as a filter at the same time.
5. The following version of the table has two filters added. With the addition of these filters, the counts in the table now only include individuals who are both Male and Married.
6. To remove a filter, click the X next to the filter name.
Cell counts, sorting, totals and other table options
Cell counts, sorting, totals, labels, codes , zero suppression, displaying percentages and RSEs
To see how large your table is, check the cell count above the table. This shows the number of rows, columns and wafers for all cells (total) and displayed cells. The displayed cell count may differ from the total cell count if row or column totals are not displayed or if the Zero suppression option is turned on. If the table has more than 10,000 cells in the total cell count, the table automatically goes into Large table mode. The largest table (including totals and wafers) that can be built in TableBuilder is 40 million cells. Techniques for reducing the size of the displayed table and total cell count are outlined in the Troubleshooting section.
Sort table columns or rows
Rows and columns can be sorted using the double arrow next to the variable and category names. Rows are sorted alphabetically by the variable labels. Columns are sorted by the data (counts) in the column. If row categories are removed and then re-added to a table, they appear in the order they have been added, not their original order. Categories can be re-ordered by using the sort option. Row variables can be sorted either by their category labels or codes.
Use the double arrows shown against the row variable label to sort based on the row labels.
Clicking the double arrow on row headings sorts based on the category names for that variable. You can toggle between:
- ascending order
- descending order
- default order
Clicking the double arrow at the top of each column sorts based on data counts in that column. You can toggle between:
- ascending order
- descending order
- default order
Show or hide totals in a table
TableBuilder can automatically add totals to tables. Click on the three vertical dots menu next to the variable name to show or hide the total for the variable. For certain variables it may not make sense to add totals, in which case the Totals option does not appear.
Category labels and codes
By default, the category labels show the names of the categories (such as Divorced, Separated, Married for the variable Marital Status). By clicking the three vertical dots menu next to the variable name, the table displays the numeric category codes instead. This can be a useful option for large classifications or variables with long category labels, such as the Australian Statistical Geography Standard (ASGS).
Table displaying category labels
Table displaying numeric category codes instead of labels
Automatically retrieve data
Whenever variables or categories in the table are changed, you need to click on Retrieve Data to populate the data in the table. Alternatively, you can select the Automatically retrieve data option (looped arrow on the Retrieve data button). When this option is activated, TableBuilder automatically updates the data whenever the table is changed (for example, adding or removing a variable).
For performance reasons it is usually better to leave this option turned off, particularly with larger tables and datasets.
Zero suppression helps you reduce noise in tables to focus on the most relevant cells of the table. When zero suppression is enabled, TableBuilder automatically removes rows and columns that contain only zeros. This can be useful for large tables with many small and zero values, as it can reduce the size of the table significantly, making it easier to focus on the results.
To activate or deactivate zero suppression, go to the Options menu at the top of the table and select from the Rows and/or Columns options.
If wafers are included in a table, then TableBuilder determines whether to suppress a row or column by looking at the entire cube, not just the currently visible wafer. A row or column is only suppressed if it contains only zeros on all of the wafers. This means that rows and columns with all zero values still appear in the table if a row or column only contains zeros on the current wafer, but has values on at least one of the other wafers.
For example, without zero suppression this table has 13 columns and 9 rows.
With zero suppression enabled, TableBuilder automatically removes all the columns that have only zeros in them. This reduces the number of columns down to 11, by removing Not applicable and Not determined. The row count remains the same even though row suppression is enabled because this table does not have any rows that only have zero values.
Use the Option menu above the table to change the counts in the table to percentages. The percentages option can be set to show percentages for:
- no percentages (none)
Percentages are calculated differently based on the option selected.
Percentages are not supported when opening certain predefined tables that contain grand totals.
Replaces the values in the table with a percentage of the total in each row.
Replaces the values in the table with a percentage of the total in each column.
Replaces the values with a percentage of the grand total. If you are using wafers then this shows the total percentage across all the wafers.
Selecting none removes percentages from the table and reverts back to counts.
Relative standard error
The relative standard error (RSE) options allow you to include RSE figures for your table. After retrieving data, use the Options button above the table to display the data counts only (Counts), RSEs only or a combination of both.
The RSE options menu is greyed out until you retrieve data for your table.
Some datasets, including Census TableBuilder datasets, are not weighted so the RSE options do not appear. RSEs are available for survey-based datasets that are subject to sampling variability. For help interpreting RSEs, see Relative standard error.
Table displaying counts only.
Table displaying counts and RSEs.
Table displaying RSEs only.
Search, save, download and print
Using search, how to save, download and print tables, graphs and maps
Searching in TableBuilder
There are two ways to search within TableBuilder:
- across all datasets and tables that you have access to (search box at the top right of all screens)
- within a selected dataset (search box at the bottom left of the dataset you have open)
Search across all datasets and tables
Use the search box in the top right corner to search across all datasets and tables. The results are presented by type:
- table (your saved tables and predefined tables)
TableBuilder displays results from all the datasets you have access to.
The results return in a table format with the following columns:
- Item - indicates in which dataset or table the search term has been found
- Type - indicates the type of result: dataset, table, variable, category
- Location - indicates the path to locate the search term
Navigate your search results
Click on a result in the panel on the right to open that item.
To return to the search page and continue with the same search results, use the back button on your browser toolbar.
Use the Filter tick boxes on the left panel to narrow down the results:
- by dataset - display only specified folders or datasets
- by type - display only specified dataset, table, variable or category
- if no filters are ticked, results display for all datasets
If your search term returns a large number of results, TableBuilder only displays the first 2,000 results per type (dataset, table, variable or category). The search may show no results for other datasets that also include the search term.
Try refining your search to a more specific term so that your search includes all results.
All datasets search error
Some searches may get stuck on the "loading" screen and not return any results. To continue working in TableBuilder you need to:
- Close the tab or window where you are working in TableBuilder using the x. You will not be able to use the log out option.
- Clear your browser cache. For Edge and Chrome, use Ctrl+Alt+Del to open the clear cache options. Other browsers may have different ways to access the cache options.
- Clear the cache.
- Navigate back to the log in page and enter your credentials.
- Try a different search term, or use the other search option: search within a selected dataset.
Search within a selected dataset
In addition to searching across all the available datasets, you can also search within the currently selected dataset. In the Table view, the Dataset search is at the bottom of the left panel.
Use the search box to display variables and categories that include your search term:
- Type your search term and either click Enter on your keyboard or click the triangle next to the search box
- Searching is not case sensitive, and you can search for a whole or partial word
- The number of results within the open dataset is shown below the search box
- The first result in the variable folder structure is displayed in the left panel
- Use the arrows below the search box to navigate through the results - the single arrows display the next or previous result, the double arrows display the first or final result
- Click the X button to clear your search and revert to the full list of available variables
Census datasets with mesh block take a long time to display search results. You may prefer to search using the 'all datasets' search function (top right) and use the filter to limit the results to the dataset you are interested in. Use the back button on your browser toolbar to return to the search results after viewing each selection.
Saving a table
You can save the tables you create in TableBuilder. Once saved, the tables are available the next time you log in. Saved tables are only visible and accessible by the person who created the table.
1. Once a table has been created, click on the Save Table button above the table.
2. Enter a name for the table and click Save. The name of the table must be unique and no longer than 255 characters.
Open a saved table
There are three ways you can access your saved tables:
1. From any screen in TableBuilder, click on the Saved and large tables option in the three vertical dots menu at the top right of the screen. This opens the main saved tables view where you can see all your saved tables across all datasets. From this view you can open any of the saved datasets, even if you have a different dataset open in the Table view.
2. From the home page, select the dataset that you used to create your table so that all saved and predefined tables associated with the selected dataset appear in the middle panel of the home page. For this view, you can only see the saved tables for the selected dataset.
3. From the Table view page, click on the Saved and predefined tables tab at the top of the variables panel on the left. For this view, you can only see the saved tables for the open dataset.
4. Select the table and click Open.
5. If a table is currently open, any unsaved table content will be lost. The table you are opening will replace the currently active table.
Managing saved tables
The main view for Saved and large tables is accessed via the three vertical dots menu in the top right corner. In the Saved tables panel on the left there are options to open, copy, delete and rename saved tables.
To open a saved table:
- Select the tick box next to the table
- Click Open
To create a copy of a saved table:
- Select the tick box next to the table to be copied
- Click Copy
- A copy of the saved table is created called 'saved table' or 'saved table1' etc, which you may rename.
To delete a saved table:
- Select the tick box next to the table to be deleted
- You can select one or more tables
- Click Delete
- Click OK to confirm the table or tables to be deleted
- Tables cannot be retrieved once they are deleted
To rename a saved table:
- Select the tick box next to the table to be renamed
- Enter a new name in the text box
- Saved table names must be unique
- Click Rename
Table download formats
After a table has been created, go to the Download Table drop-down list in the top right corner. You don't need to click Retrieve data first as downloading automatically retrieves the data.
Tables can be downloaded in the following formats:
- Excel 2007 (.xlsx) (max 16,384 columns x 65,000 rows and < 100,000 cells)
- Comma Separated Value (.csv)
- CSV string value (.csv)
- SDMX Structure Definition (.xml)
- SDMX Archive (.zip)
Percentages in downloaded tables
When downloading tables containing percentages, the percentage symbol is only displayed in Excel format downloads. Other formats such as CSV include the percentage value but do not show the percent symbol (%) after the value.
Relative standard errors in downloaded tables
Where relative standard error (RSE) data is available for a table, this data is included in the downloaded table. The RSE data is downloaded even if it is not currently displayed in the table in Table View. Some datasets, including Census TableBuilder datasets, do not have RSEs. RSEs are only applicable for sample data and weighted data. For further information, see the Relative standard error section.
Excel: downloads include RSE data in a separate Excel worksheet (tab).
CSV: downloads include a separate column for RSE data.
SDMX: RSE data is represented as an attribute value in the SDMX Generic Data observation element. This attribute is only added when the dataset is weighted and has RSE values in the associated data cube. For example:
Annotations in downloaded tables
Annotations provide additional information or notes about features or aspects relating to the data or dataset. If the table contains annotations they are included in the downloaded table.
- Annotation symbols in the table cells on the first worksheet
- Annotation details in footnotes under the table
- Annotation symbols in a separate column
- Annotation details immediately after the table data
- SDMX downloaded at the dataset level contains dataset level annotation descriptions and symbols in the <Annotations> ... </Annotations> section of the XML.
Printing is best suited to smaller tables. For larger tables, downloading the table in Excel format and printing the table from within Excel provides more control over the print layout and formatting.
Click the Print table button above the table to print the current table.
This opens your browser's print dialogue box, which may also include options to print to PDF.
Large table features, creating, queuing and downloading large tables
When a table has more than 10,000 cells including totals, TableBuilder automatically enters Large table mode and displays a warning message.
Totals are included in the table count, whether or not they are displayed. Hiding totals, by selecting Totals in the three vertical dots menu within the table headings, reduces the size of the displayed table only, not the actual table, and does not affect the cell count for Large table mode.
Zero suppression hides rows or columns where all cells are zeros. Using Zero suppression does not reduce the total cell count for Large table mode. This is because the data for the cells must be retrieved before TableBuilder can determine whether the row or columns contain only zeros.
Retrieve data is no longer available in large table mode. Instead, the structure of the large table is built in TableBuilder and can then be queued to retrieve the data. Large tables may complete straight away or may take 24 hours or longer to complete, depending on the size of the large tables and the queue. Once the table has processed, it can be downloaded. Downloaded large tables are available for download again for 28 days.
Building a large table
1. When building a large table, TableBuilder displays a summary version of the full table, with only two categories displaying for each variable. A message indicating that you are working in large table mode and the cell count of the large table displays above the table. This shows the number of rows, columns, wafers and the total cell count. The largest table that can be built in TableBuilder is 40 million cells, including row and column totals and wafers.
2. Although you can only see part of the table, you can continue using table functions, such as adding and removing variables or categories from the rows, columns and wafers. In large table mode, dragging variables with a large number of categories from one axis to another (such as large geographical classifications) may take some time.
3. Large table structures can also be saved using the Save table button. Saving the table structure allows you to modify the table in the future. Large table structures are not automatically saved by queuing the large table. Queuing a large table saves the output data only, which is available for download for 28 days. While the large table is still displayed in the Large tables list, the large table structure can also be reopened and saved by selecting view.
Using mesh blocks
Some Census TableBuilder Pro 2016 and 2021 databases include mesh block level detail, the smallest geographical unit used in TableBuilder. Mesh blocks to enable you to build your own custom geographic areas. If you want to display a geography in a table that is not already provided in TableBuilder, you can use mesh blocks to accurately approximate a large range of other statistical regions. See the Custom data section for help in customising your own geographies and Census Dictionary for more information about mesh blocks.
Mesh blocks are ideal for building custom geographic areas. However, you may also want to add mesh blocks directly to your table. TableBuilder has a limit of adding 60,000 categories from any one variable to a table. As there are more than 60,000 mesh blocks in each of Australia, New South Wales, Victoria and Queensland you need to select a smaller geographic area when using mesh blocks. Because of the very detailed information, you may need to build a number of tables if you want to include mesh blocks as a variable in your table.
1. If you try to add all mesh blocks to your table, an error message is displayed indicating 'A maximum of 60,000 categories can be added to a table. 'Untick all' at the top of the variable panel and select fewer categories'.
2. The number of items you currently have selected is displayed at the top of the left panel. TableBuilder stops selecting categories when it reaches the 60,000 limit. Before continuing, clear your current selection by clicking on Untick All.
3. You can then select a smaller number of categories to build a table. This example shows all mesh blocks in South Australia being successfully selected.
Queued large tables
1. Once your large table structure is ready, select a download format at the top right of the window. Excel format can only be selected if the large table is within the Excel export limits.
2. If a large table has too many rows, columns or cells, the Excel option is greyed out and cannot be selected. Excel 2007 downloads are limited to 16,384 columns x 65,000 rows and less than 100,000 cells. After selecting your preferred format, click the Queue table button.
3. Enter a name for the large table, and click Queue table.
4. You are returned to the Table view. TableBuilder displays a message that the request has been successfully added to the large table queue. This message means that your large table output will be available for download once it has completed. While the large table output data is saved within TableBuilder, your large table structure has not yet been saved. If you also want to save your large table structure so that you can modify or queue it again it in the future, you also need to use the Save table button.
5. To check the status of your queued table, click on the Saved and large tables link in the confirmation message at the top of the screen. Alternatively, go to the three dots menu in the top right of the screen, and select Saved and large tables.
6. While a job is queued and processing, you can continue to work on other tables, or create other large tables for queuing. You can also log out of TableBuilder and come back later. Your table continues running in the background.
7. In the Saved and large tables view, you can check the status of your queued table. When the table has the status of Completed, click here to download, the table has finished processing and can be downloaded. Tables can be downloaded any number of times until they expire after 28 days.
8. The data for completed large tables is stored in TableBuilder for 28 days. The Expiry time is listed in the Saved and large tables view. After this date the large table will be deleted from TableBuilder and no longer be available for downloading. To use a large table again in TableBuilder, save the large table structure using the Save table button in the Table view. The large table can then be queued again.
Create, edit, download and upload your own custom variable groupings
Create and save a custom data group within TableBuilder
You can create your own grouping of categories within a variable. These are also known as 'recodes'. Custom groups can be saved in TableBuilder and downloaded and shared with other users for uploading. Custom data is useful if you want to create your own classification or load more recent electoral boundaries. Once you create your grouping, you can add it to a table like any other variable.
You can only combine categories from one variable or one level of a variable. You cannot create a new custom data group using:
- two or more original variables, such as Sex and Age - an error is displayed if you try to add more than one variable
- categories from two different levels of a hierarchical variable, such as NSW and Melbourne - TableBuilder allows you to build and save a multi-level hierarchical variable, but does not allow you to add it to a table
To start creating your custom data, click on the Custom data button at the bottom of the left panel in Table view.
1. This example uses the 2016 Census - Cultural Diversity dataset. Click on the Custom data button.
2. In the Step 1 panel, select the categories you want to group together, then click on the double arrows to add them to the panel on the right.
For example, to create a group of States in the Main Statistical Area Structure (Main ASGS) field, select the States from the list and click »»
3. The selected categories now appear in the Step 2 panel on the right. After adding all the categories you need, click Save.
4. Enter a name for your new custom group and click Save.
5. TableBuilder adds the new group to the My custom data list in the left panel of the Custom data view.
6. Your saved custom data group is now available in the left panel of the Table view.
- Custom groups of geographical areas are found in a separate Custom Geography folder below the other folders.
- Custom groups for other variables are found with the original variable.
7. The custom group can be added to a table.
8. You can edit a group that you have created previously. However, if you have used your custom group in a saved table, the old version of the group will continue to display in the table. To update to the new version, you need to remove and re-add it to the table.
Download a saved custom data group
You can download a Custom data group you have built in TableBuilder to share with other users.
1. Click on the Custom data button at the bottom of the left panel.
2. In the My custom data panel, select the tick box next to the group to be downloaded and click the Download button.
3. Depending on the browser, the file either saves to the default downloads folder, or a prompt appears to save or open the file. For example:
4. The custom group is downloaded in a Comma Separated Values (CSV) format, and can be edited outside TableBuilder or shared with other users.
Download a classification to edit outside TableBuilder
You can download a whole classification to edit outside TableBuilder. This option is useful for very large classifications, such as geographies, or where you would like to use a TableBuilder classification to build your own classification outside TableBuilder
1. This example uses 2016 Census - Main Statistical Area Structure (Main ASGS) (UR). Click on the Custom data button on the left panel in Table view. Then select the whole classification you are interested in using the single arrow > at the end of the variable name. In this example, SA2 is selected. Click on the double arrow »» to move the selected classification to the second panel.
2. Once the classification has loaded, it may display over more than one page. You can view other pages using the page navigator below Step 2 panel. Click the Save button.
3. Choose a name for your classification. You cannot use a custom group name you have previously used.
4. In the My custom data panel on the left, select the tick box next to the group to be downloaded and click the Download button.
5. Depending on the browser, the file either saves to the default downloads folder, or a prompt appears to Save or Open the file. For example:
6. The custom group downloads in a Comma Separated Values (CSV) format, and can be edited outside TableBuilder.
Edit a downloaded custom data group outside TableBuilder
When a custom group is downloaded as a file in Comma Separated Values (CSV) format, the file can be opened and edited in a text editor or application such as Excel. It is important to be careful when editing a saved custom groups file in Excel, as it may make changes to the data that will prevent the file from opening in TableBuilder again. For example, Excel may strip leading zeros from codes in the file, such as ValueCode, which will not be able to be loaded back into TableBuilder. It is best to use a text editor instead, such as UltraEdit, to upload the new group.
A downloaded custom group opened in a text editor.
A downloaded custom group opened in a spreadsheet.
The first row contains the headings, and each subsequent row represents a single item in the custom group. The heading row must not be edited or the file cannot be uploaded to TableBuilder.
Rows can be added, edited or removed (except the header row) to change the composition of the group.
Upload a custom data group
Custom group files that have been created or edited in your own system or shared from other users can be uploaded into TableBuilder.
To upload a custom group:
- You must have access to the dataset that the custom group was created in.
- The dataset that relates to the custom group must be open.
- Upload files must be in CSV format.
- The structure of the custom group file must be retained using the same column headings.
- The name of the group in the saved file must not be the same as an existing custom group. TableBuilder displays an error if a custom group with the same name as an existing group is attempted to be loaded. Delete the existing custom group, rename it, or rename the group saved in the file (by changing the value of the GroupName in the final column).
- Only one saved group can be uploaded at a time.
1. To load a custom group from a file, open the dataset that was used to create the recode, and click on the Custom Data button at the bottom of the left panel.
2. In the My custom data panel, click the Upload button.
3. Browse to the location where you saved your custom group file and select the file. When uploaded, TableBuilder adds the new group to the My custom data panel.
4. If there is a problem with the upload, an error message is displayed.
Common errors when uploading a custom data group:
| Upload error. 61 out of 65 lines successfully imported. A values code or name is not found.
The ValueCode column, which is the numeric code for a variable name, may be missing leading zeros. Check if the classification you have edited includes leading zeros.
| Upload error. 0 out of 1,464 lines successfully imported. A group with this name already exists.
The Custom Data group has previously been uploaded or the name has already been used. You will need to change the value of the GroupName in the final column to load the file.
| Upload error. 0 out of 1,464 lines successfully imported. A tables code or name is not found.
The upload file doesn't match the dataset that is open. You will need to open the matching dataset to load the file. If you already have the correct file open, the information in the FactTableCode or FactTableName may be incorrect. You can check what this should be by downloading any custom data from the same dataset.
| Uploaded file has invalid CSV header. Expecting column names FactTableCode, FactTableName, FieldCode, FieldName, ValueSetCode, ValueSetName, ValueCode, ValueName, GroupName but read [, FactTableName, FieldCode, FieldName, ValueSetCode, ValueSetName, ValueCode, ValueName, GroupName]
The header row contains an error. Check the header row in your file to ensure it has the correct names, as listed in the examples pictured above.
|The requested URL was rejected. Please consult with your administrator.||This message may be caused by a number of different actions. In this context it may be caused by trying to load an incorrect file type, such as an XLS. Only CSV files can be used when uploading Custom Data Groups.|
|No error but file does not upload||Your upload file may be too large. The maximum upload file is 20 million bytes (19.07MB)|
Upload Commonwealth and state electoral divisions and local government areas
Commonwealth electoral divisions (CED), state electoral divisions (SED) and local government areas (LGA) boundaries change over time. ABS has prepared upload files to assist users to update the boundaries available within Census TableBuilder.
TableBuilder upload files for CEDs, SEDs and LGAs are available for use with Census 2016 datasets:
Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures (see Downloads tab)
Files for use with Census 2021 will be added here as they are released.
1. Download CSV file from the Downloads tab in Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures and save it to your computer.
2. Files are available for Australia and for each state and territory. These files are suitable for use with the following 2016 Census of Population and Housing - TableBuilder Pro datasets:
2016 Census - Counting Persons, Place of Enumeration (MB) - compatible files are annotated with en (enumeration)
2016 Census - Counting Persons, Place of Usual Residence (MB) - compatible files are annotated with ur (usual residence)
3. Log into TableBuilder and open the dataset you are interested in. This example uses 2016 Census - Counting Persons, Place of Usual Residence (MB).
- Click on to the Custom data button on the left panel of the Table view.
- Click the upload button at the bottom left of the screen.
4. Find the location where the CED files have been saved and select the region you are interested in (Australia, state or territory). This example uses 2020_lga_act_ur_csv.
5. When the upload has completed, a message appears on the right to confirm the number of rows that have been loaded from the CSV file (not including the heading row). The uploaded custom data appears in the My custom data panel under Custom Geography. If you receive an error when uploading a file, check the errors and causes listed in the Upload a custom data group section above.
6. In the Table view tab the custom data you uploaded appears under the Custom Geography folder. You can select multiple tick boxes at once by holding down the Shift key to add the NSW CEDs to a table.
Summation options for continuous variables
How to use summation options, ranges and quantiles for continuous variables
Understanding what is being counted
When you open a dataset and build a table, most datasets display the default summation above the table. This tells you what you are counting in your table. For example, your table may be counting persons, families, households, or motor vehicles. Some datasets also allow you to choose a summation option where you can vary what the table is counting. For example, a dataset may include options for counting number of drinks of alcohol consumed or number of kilometres travelled.
The i link next to the default summation provides further information about what is being counted for the default summation.
For tables that do not use the default summation, an annotation displays below the table indicating what is being counted.
Categorical and continuous variables
Some datasets include categorical variables only while other datasets also include continuous variables.
Categorical variables have limited discrete responses, such as State/Territory or Marital status.
Continuous variables can take any numerical value and can be measured. In TableBuilder continuous variables may have options to calculate sum, median, mean, ranges or quantiles.
In TableBuilder, some variables may be included as both categorical or continuous. For example:
- Age may be categorical, where you can select specific ages to include in your table, and continuous, where you can calculate the median age for a population.
- Income may be provided as a categorical variable in set ranges, such as $0-$499, $500-$999 etc, and may also be provided as a continuous variable, where you can create your own custom ranges, including decimal places.
Summation options functions
Datasets that include continuous variable functions have a Summation options folder at the top of the variable list panel on the left of the Table view. Summation options control what is being measured in the table. If a summation option is not added to the table or if there is no summations options folder, TableBuilder automatically adds the default summation option for that dataset.
Summation options allow you to calculate the following functions for continuous variables:
- sum - add all responses, such as total number of drinks consumed for a population
- median - the midpoint of the frequency distribution
- mean - average
- ranges - create your own custom intervals
- quantiles - divide the population into evenly distributed groups such as quartiles, quintiles or deciles
For example, instead of counting the number of males and females who consume alcohol, you can display the total number of standard drinks consumed by males and females. For survey data, this is weighted based on population estimates.
A table that includes a sum, median or mean for a continuous variable only includes those records in the dataset that have a valid value. For example, records with responses for the continuous variable such as 'N/A' or 'Did not respond' are excluded. The records that have valid responses for a variable are determined for each individual cell of the table, including total cells. For further information about valid values, see Interpreting sums, means and medians.
Add a sum, median or mean to a table
1. Click on Summation options at the top of the left panel in Table view. Summation options are only visible for datasets that include continuous variables.
2. Select one of the sum, median or mean tick boxes and Add to row, column or wafer. In this example, the Sum of Number of standard drinks by day has been added to row.
3. Only one sum, median or mean can be added to a table, for the same or another continuous variable:
- If you try to add a second sum, median or mean to a table that already includes one, TableBuilder automatically removes the existing one and adds the new one.
- If you try to add more than one summation at the same time by ticking more than one of sum, median or mean, TableBuilder displays a error message "Only one summation option can be added to a table"
4. The Weighted sum of Number of standard drinks by day has been added to the row.
5. Other variables can be added to the table. The variable Sex is added to column, and the data retrieved. This table displays the Weighted sum of Number of standard drinks by day, which is 59 million standard drinks for all males in Australia and 28 million for all females.
6. To display the median or mean Number of standard drinks consumed instead of the sum, select the new option from the summation options on the left, and Add to row again. This automatically replaces the summation option currently in the table.
7. After retrieving the data, the Weighted median Number of standard drinks by day was 3.2 drinks for Males, 2.2 drinks for Females and 2.8 drinks for all persons.
8. Similarly, when the Weighted mean Number of standard drinks by day is added to the row, it automatically replaces the median. The Weighted mean of Number of standard drinks by day was 4.7 drinks for Males, 3.1 drinks for Females and 4.0 drinks for all persons. The mean is calculated based on the population of people who have a valid response, and does not include people who do not drink or children. See Interpreting sums, means and medians for more information about valid responses for continuous variables.
9. If all Summation Options are removed from the table, TableBuilder automatically adds in the Default summation option back into the table. If the weighted mean is removed from the above table, by dragging it into Remove, TableBuilder confirms that 'Removed all the summation options from the table. Your table is now using the default summation option, listed in the Filter'. In this case, the table has reverted to counting Selected persons.
Interpreting sums, means and medians
Estimates of sums, medians, means and ranges for continuous variables must be interpreted carefully. You should read the entry for the continuous variable in the data item list for the dataset, checking the population and the 'special response' categories.
A continuous variable on a dataset has an associated range of 'valid value' responses, and also may have various categories of response that are 'special', for example a special response may be 'Not applicable' or 'Not stated'. These special responses may occur for a variety of reasons, such as the relevant question does not apply to certain records, or the information is unable to be determined. Read the dataset documentation and data item list for detailed information. To open the website dataset information, click the i link at the top left next to the dataset name when in Table view. This opens in a new tab so you can continue working in TableBuilder.
Whenever a sum or mean is included in a table for a continuous variable, the statistic is estimated for the variable's reference population with a valid response.
A continuous variable that does have possible special responses appears in two different sections of the variables list panel:
- as a selectable summation option (continuous variable)
- as a categorical variable under the relevant grouping
The version that appears as a categorical variable contains categories for each of the special response types, and one for 'valid' responses. You can use this variable for population estimates of the various special response types (such as 'No Response'). It is highly recommended when interpreting a table of means or sums of a variable that the corresponding categorical variable be used in separate tabulations of population counts.
When interpreting a table of median estimates, it is also important to understand the population for which the estimate applies, and the valid responses. If there are a small number of records making up a cell's reference population with a valid response, the cell may be suppressed, showing a value of '0' or 'np'. The suppression occurs to prevent the release of disclosive information. The relative standard error (RSE) for each median estimate is estimated using the Woodruff method, which is a replicate weight method. Further information is available in the Relative standard error section.
1. When working with sum, median and mean, check the data item list for the dataset to see the population to which the variable applies.
2. From the TableBuilder publication, download the TableBuilder data item list. In this example, respondents who Did not consume alcohol in the last week or Have never consumed alcohol and respondents who are younger than 15 years are not included in the sum, median or the mean.
3. From the above example, searching for Number of standard drinks consumed using the search box in the lower left corner, finds two results in the variables list. One is a continuous variable (summation option) and one is a categorical variable that can be used to find the number of records that recorded a valid response, and that were used to calculate the mean.
4. If a table is created using Sex and the categorical version of Number of standard drinks consumed, the weighted number of persons whose responses contributed to the sum and mean are displayed. This table is now counting persons (in 000's). The categorical variable for Number of standard drinks consumed provides estimates of the size of the population to which the above sum, median and mean are calculated. It also provides the sizes of the populations to which it does not apply, for example, the category 'Have never consumed alcohol', which also includes people under the age of 15 years.
There were weighted counts of 5.8 million males and 4.5 million females whose responses were included in the sum and mean. An incorrect result would have occurred for mean if the persons who did not consume any alcohol were recorded as consuming a valid value of 0 standard drinks.
Continuous variables on a dataset usually allow you to create ranges to include in your table. Ranges allow you to merge responses to continuous variables in a way that suits your analysis. For example, Age ranges can be created from Age in single years to 15-17 years, 18-29 years, 30-49 years and 50+.
Categorical variables can also be grouped using Custom data.
When using a ranges variable in a table, the ranges span all valid values for that variable. The table does not include records which did not provide a valid response for that variable. Even if all the categories within a ranges variable are added to a table, the grand total of the table may therefore be less than the total population due to records without a valid value being excluded. See Interpreting sums, means and medians for more information about valid responses for continuous variables. You should also read the entry for the continuous variable in the data item list for the dataset and check the population, and the 'special response' categories. Information about each variable's population is available in the dataset's data item list on the ABS website. To open the website dataset information, click the i link at the top left next to the dataset name when in Table view. This opens in a new tab so you can continue working in TableBuilder.
1. In the left panel, open the Summation options folder to select the continuous variable to be put into ranges. Click on the Range button.
2. The Ranges and quantiles screen appears.
- Enter a name for the range (no longer than 25 characters).
- Enter the minimum and maximum values for your range in To and From.
- When selecting the From and To values, select less than \(<\) or less than or equal to \(\le\) in the drop-down menu to choose whether to include the lower boundary or upper boundary in each range.
- Enter an increment for each range.
3. If values are selected outside the allowable range values, TableBuilder displays information about the minimums and maximums you can select. You can use this information to help you decide on appropriate range parameters. Click Next.
4. The ranges to be included are displayed. Edit by clicking Back or continue by clicking Create.
5. This creates your range, and adds it to a new Ranges folder in the variables list panel in the Table View below the Summation options folder. Click on the Ranges folder to view your range. The Ranges variable is now saved and can be used to a table now or for future tables using this dataset.
6. Custom ranges can be added to a table like any other variable, by dragging and dropping, or using the Add buttons at the top of the left panel.
Copy and delete ranges
1. To copy or delete a ranges variable, open the Ranges folder below the Summation options folder in the left hand panel. Click the Manage button next to your variable.
2. The Ranges management screen opens.
3. To copy a range, click the Copy button. The Ranges and quantiles screen opens with the parameter values for the existing Ranges variable entered. Change the parameters and rename the range, then clicking the Next button to continue to create the new range.
4. To delete a range permanently, click Delete. A confirmation screen opens showing items that you have created using this range:
- any groups you have created (using Custom data)
- any tables you have saved
Clicking OK deletes these groups and tables as well as the ranges variable.
Quantiles can be created for continuous variables on a dataset. Some datasets only include categorical variables, so quantiles cannot be created. Categorical variables can be grouped using Custom data.
Quantiles are ranges that have an equal distribution in each group. In TableBuilder you can create:
- median (two equal groups)
- terciles (three equal groups)
- quartiles (four equal groups)
- quintiles (five equal groups)
- sextiles (six equal groups)
- septiles (seven equal groups)
- octiles (eight equal groups)
- noniles (nine equal groups)
- deciles (ten equal groups)
Quantiles can be applied to the whole population or to a sub-population by using a filter.
Creating and using quantiles
1. In the left panel, open the Summation options folder to select the variable to be put into ranges. Click on the Range button.
2. The Ranges and quantiles screen appears, with the Custom ranges tab open.
- Select the Quantile tab.
- Enter a name for the Quantile (no longer than 25 characters).
- Click the drop-down menu for the Number of Ranges to select the number of groups from 2 to 10.
- Click the drop-down menu for Equal distribution of and choose the distribution variable. You can equally distribute by either:
record counts - equal groups based on the number of records (e.g. number of persons, households or motor vehicles)
the continuous variable you are working with - equal groups based on what the continuous variable is counting (e.g. height in cm, weekly income in dollars or number of kilometres travelled)
For example, if you select the variable Estimated average daily intake over week (in mls) as the continuous variable, for the Equal distribution variable:
- If 'Selected persons level' is selected as the equal distribution variable, these deciles can be interpreted as equally distributing the number of persons into ten groups. Each group has an equal share of the number: 10%.
- If 'Estimated average daily intake over week (in mls)' is chosen as the equal distribution variable, then the average daily intake of alcohol over a week (in mls) is equally distributed across the ten groups, so that each of the ten groups created represents a 10% share of the total Estimated average daily intake over week (in mls).
The equal distribution of variable cannot contain negative values.
3. Optionally, you can choose a subpopulation for your quantiles by using the Filter By section.
- The left panel has the same variable structure as the Table view.
- Tick the categories to be included in the filter.
- Then click the Move button. The window on the right displays the filter, is updated to include the variables and categories moved.
- You can select more than one category across one or more variables at the same time, or go back to the first panel and add more categories.
- If you change your mind, you can select a category on the right panel and click the Move button to remove it.
Leave the filter empty if the quantile is to be applied to the whole population.
See Interpreting quantiles to interpret a quantile with a filter.
4. Click the Next button.
5. The quantiles screen shows the quantile boundaries along with their RSEs. You can:
- make further changes to the quantile by clicking Back
- download the displayed table in csv format
- create the quantile variable by clicking Create.
6. The quantile variable can be accessed from the Ranges folder in the left panel of the Table view. Quantiles can be added to a table like any other variable, by dragging and dropping, or using the Add buttons at the top of the left panel.
Copy, download and delete quantile ranges
1. To copy or delete a quantile variable, find the quantile in the left panel in the Ranges folder. Click the Manage button next to the variable.
2. The Quantiles management screen opens.
3. To copy a quantile range, click the Copy button. The Ranges and quantiles screen opens with the parameter values for the existing quantile variable entered. Change the parameters and rename the range, then clicking the Next button to continue to create the new range.
4. To download a quantile range in csv format, click the Download button.
5. To delete a quantile range, click Delete. A confirmation screen opens showing items you have created using this range:
- any groups you have created (using Custom data)
- any tables you have saved
Clicking OK deletes these groups and tables as well as the quantiles variable.
When using a quantile variable in a table, the ranges span all valid values for that variable. The table does not include records which did not provide a valid response for that variable. Even if all categories within a quantile variable are added to a table, the grand total of the table may therefore be less than the total population due to records without a valid value being excluded. See Interpreting sums, means and medians for more information about valid responses for continuous variables. ou should also read the entry for the continuous variable in the data item list for the dataset and check the population, and the 'special response' categories. Information about each variable's population is available in the dataset's data item list on the ABS website. To open the website dataset information, click the i link at the top left next to the dataset name when in Table view. This opens in a new tab so you can continue working in TableBuilder.
In the example, the estimates are quartiles of the variable Body mass index (BMI) - score measured weighted by Selected Persons level, for the subpopulation of persons with Sex of Male. The window on the right displays the quantiles, where the Range column shows the number of the quantile, the Max column shows the value of the quantile and the RSE column the estimate’s RSE. In the example, the first quartile (25th percentile) is 21.729 with RSE 0.43%, the second quartile (50th percentile) is 25.75 with RSE 0.29%, and the third quartile (75th percentile) is 29.39 with RSE 0.39%. The value for the final range is always shown with infinity, as this range has no maximum. Similarly, the first range has no minimum value.
In some situations, it is possible that an estimate of a quantile may be displayed, but the estimate of the RSE is displayed as *. This occurs when the RSE cannot be calculated reliably and the estimate should be treated with caution.
It is possible to use variables from different levels of the data in a filter. For example, it is possible to use a filter of State or Territory being NSW, a Household level variable, when requesting quantiles of a Person level variable such as Age of Person. If this is the case, the population is filtered by restricting to the appropriate collection of records. The population over which quantiles are estimated would be those persons belonging to a household in NSW.
Once the quantile variable has been created and is used in a table, it applies to the entire population, and not to the subpopulation that the filter refers to.
For example, if the quantile above was used in a table of estimated counts, the estimates would be estimated counts of the entire population, and not restricted to persons with particular values for Country of Birth and Sex. The quantile boundaries remain the same, however, calculated based on the filtered population.
Graphing your table data
TableBuilder includes a function to graph your table data. There are a number of ways to interact with and edit the graph.
Click the Graph view tab to generate a graph based on the table that is currently open.
If the table is currently set to use percentages, then the graph represents the values as percentages.
To maximise the amount of space available for viewing your graph, hide the graph options panel on the left by clicking the < arrow. Click the > arrow to open it again.
Hover your mouse over the graph to see more information about categories in the graph.
Change the graph type
Select a graph type from the list in the graph options panel. The graph updates automatically.
Graph by row or column
By default, TableBuilder places the variables from the table rows along one axis and shows the categories from the table on the other axis. To swap the headings on the axis, use the Graph by option.
For example, the following table shows age in five year groups.
The default for most graph types is that row headings are placed on the x axis.
The exception to this is bar charts and stacked bar charts, which have the row headings on the y axis by default.
Select Column from the Graph By option to display the column headings on the x axis, instead of the row headings.
For bar charts, select Column from the Graph By option to display the column headings on the y axis, instead of the row headings.
Select series for pie charts
Pie charts can only show a single row or column at a time. Use the Graph by option to choose whether to show a row or column from the table, and the Selected series drop-down to select which row or column. While pie charts can be created in TableBuilder they should be used with care as it can be difficult to make accurate comparisons about the relative size of each category.
For example, this pie chart is showing age in 5 year groups by state. Use the Selected series drop-down to change the range of states shown in the chart.
The key below the graph is interactive. Clicking any of the categories temporarily hides them from the graph. This can be particularly useful if you have outlying data that makes it hard to focus on the most relevant data.
In this graph, 30-34 years are much greater then 10-14 years.
Click on 10-14 years in the key to temporarily hide it from the graph. The graph automatically updates, and the scale of the y axis automatically adjusts to make best use of the available screen space.
Edit axis labels
The axis labels can be edited by double clicking on them and entering a new name. Clear the text to revert to the default label.
The edited labels are displayed for as long as you remain in Graph view. The labels are also included on PDF or PNG downloads. Changes the graph type and the graph keep the same edited labels. However, the labels are not be saved if you switch to one of the other views. For example, if you switch to Table view and then switch back to Graph view, the graph reverts to the default labels.
Graph size limits
If there are too many items in the table the graph cannot generate. TableBuilder displays a message indicating that the data is too big to be graphed if there are more than:
- 216 variables
- 1,000 cells
Go to Table view and make changes to reduce the table size. You may be able to reduce the table size by applying the Zero suppression options.
If the category labels have very long names, they may not be suitable to graph in TableBuilder. If the category labels are too long, they may be truncated with "..." in the key below the graph and in the text that appears when clicking on the graph. To best display your graph, download the table and use the graph options in your chosen application such as Excel.
Graphs cannot be saved within TableBuilder. Graphs are only available for the current session. However, saving the table used to create the graph allows you to reopen the saved table and then access the graph again via Graph view.
It is not recommended that graphs are printed directly from TableBuilder. Better formatting results can be obtained by downloading the graph or the table data into your chosen application such as Excel.
1. To download a graph (for example to use in a report or presentation), choose a download format from the drop-down list at the top right of the screen. Choose to download the graph as a PDF or PNG (image) format.
2. If there are too many categories in a graphed variable, only the first page of categories displays in the downloaded PDF or PNG. You may achieve better results by downloading the table instead, and use the graph options in your chosen application such as Excel.
Mapping your table data
Map functions are available for datasets that include geography variables with a green globe icon. If the table contains mappable geographical data, then Map view can be used to display the results on a map.
- The Map view tab is greyed out until you add a mappable geographical variable to your table.
- To create a map, your table must include one mappable geographic variable on an axis by itself (row or column), with your other variables on the opposite axis or in the wafer.
- The maximum number of geographies that can be included in a map is 1,000. However, it is recommended that fewer geographies are mapped for improved performance and usability.
Create a map
1. Create a table containing:
- a mappable geographical variable (indicated by the green globe icon) on either the row or column, for example, Area.
- other variables in the opposite axis (column or row) or the wafer
- Click Map view
2. Depending on the complexity of the table, the map may take some time to generate.
Customise the map
Once the map is generated, there are options to customise what is shown in the map and how it is displayed.
Selecting the categories to display
Select the category you want to map from the Field and Wafer drop-down menus to visualise on the map. The options available depend on the variables and categories that were included in the original table.
TableBuilder calculates the ranges automatically based on natural breaks in the data. The natural breaks are calculated using the Dalenious Hodges Algorithm. Select the data ranges to be displayed on the map.
Natural breaks is a good choice when the data is not evenly distributed. This algorithm groups data into classes that are themselves as separate as possible, but where the data values within each class are fairly close together. That is, it maximises the differences between the classes and minimises the differences within the classes. This classification can be used to discover spatial patterns within the data, but it can lead to some classes being populated by low numbers of observations.
Equal distribution puts the same number of records into each class. For example, a dataset containing 100 records is split so that approximately 20 records fall into each class of a five class classification. When using equal distribution it is important to watch out for any extreme data values (outliers) that might affect the thematic map. Outliers are incorporated into a class without regard to the distribution of the remaining values in the class. This method can give the most evenly coloured map but should only be considered for datasets with a nearly even distribution.
Quantiles divide records into class ranges of equal spread. For example, in a field of data values ranging from 1 to 100, the records would be assigned (in the 5 class case) into the ranges 1–20, 20–40, 40–60, 60–80 and 80–100. These ranges are set to 1 to less than 20, 20 to less than 40 etc., so the classes do not overlap.
With this method, classes with few or no data records can be created, depending on the distribution of your data. For example, the records 1, 4, 6, 10, 10, 89, 90, 92, 95, 100 (that is, highly skewed to either end of the overall data range) causes the middle three classes to have no records. In this case, only two colours appear on the map. To produce even colour representation on the map, the data would need to contain nearly evenly distributed values.
Use custom ranges to choose your own data ranges. Custom ranges should always be developed with reference to the distribution of the data being mapped. The custom range option can be particularly useful when developing a series of maps that are designed to be compared. Enter the start and end values for each range and then click Update Ranges to update the map.
Choose the colours used to highlight the different regions in the map.
Number of ranges
Select the number of different coloured ranges you want to display on the map. You can display between one and five ranges.
Use the slider to control the opacity of the coloured areas on the map.
- At 0% the areas highlighted on the map is completely transparent and only the outlines are visible.
- At 100% the areas highlighted on the map is completely solid and the map underneath is not visible.
Use the plus and minus buttons in the top left of the map to zoom in and out of the map.
Click and drag anywhere on the map to pan around the map.
Select an option from the drop-down list in the top right corner to change map types. You can select:
- street map
- aerial map (satellite)
- blank map
Click any region in the map to see the name and value for this region.
Edit what is displayed in the map
The buttons at the top of the map can be used to change the areas that are visualised on the map from within Map view.
Click one of the buttons to change the map to "edit mode". In this mode, all the areas currently included in the map visualisation are highlighted in a single colour. You can also see when you are in edit mode via the status message above the map.
You can then select areas you want to remove from the map, as well as add new areas to the map, even if they were not included in the table. You can only add areas to the map if there is data for those areas in the dataset. Adding areas to the map also adds them to the table (switch back to Table view to see this change).
There are three ways you can edit the map (and the underlying table):
- Click an area that is currently highlighted to remove it from the map.
- Click an area that is not currently highlighted to add it to the map.
Click and drag to draw a rectangle over the areas you want to include or exclude from your map.
- Areas underneath the rectangle that are currently included in the map are removed.
- Areas underneath the rectangle that are not currently included are added to the map.
Click to start drawing the first corner of a shape, then click again as many times as needed to add a point and continue drawing the shape. To complete the shape, either click again on the first point, or double-click.
- Areas underneath the shape that are currently included in the map are removed.
- Areas underneath the shape that are not currently included are added to the map.
Click Apply changes to accept your changes and return to the map.
Click on the selected button (single, rectangle or polygon) to cancel your changes and leave edit mode.
Changes you have made are also applied to the underlying table. You can also modify by switching back to Table view and modifying the table, then returning to Map view.
Download the map
1. In the top right corner, select the download format from the drop-down list:
- KMZ format (can be used in tools such as Google Earth)
The map downloads at the current zoom level, showing the same section of the map that is currently visible on screen.
Maps cannot be imported back into TableBuilder. To access the same map in future sessions, save the table used to create the map. You can then reopen the saved table and click Map view to recreate the map.
Using mesh blocks
Some Census TableBuilder Pro 2016 and 2021 databases include mesh block level detail, the smallest geographical unit used in TableBuilder. While you can map mesh blocks, they are more suitable to use to build your own custom geographic areas. If you want to display a geography in a table that is not already provided in TableBuilder, you can use mesh blocks to accurately approximate a large range of other statistical regions. If you combine categories within a mappable geography to create your own variable using custom data, the new variable can also be mapped. See:
Confidentiality and relative standard error
Perturbation and interpreting tables with small cells, sparsity and relative standard errors
To minimise the risk of identifying individuals in aggregate statistics, a technique has been developed to randomly adjust cell values. Random adjustment of the data, known as perturbation, is considered to be the most satisfactory technique for avoiding the release of identifiable data while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics.
Perturbation is applied across all non-zero cells in a table, including the totals cells. Perturbation may change the true cell value by either increasing or decreasing the value by a small amount. Within this context, although cells may appear to contain none, or all, of a relevant sub-population, this is not necessarily a reflection of the true value of the cell. These adjustments result in introduced random errors, but with almost no bias. The information value of the table as a whole is not significantly impaired.
Random perturbation can be a source of frustration to users, as it can result in inconsistencies in the data. Most tables reporting basic statistics do not show significant discrepancies due to random perturbation. However, as the degree of complexity of tables increases, the need for random perturbation remains and it will continue to be used in most TableBuilder datasets.
In TableBuilder, totals are not calculated by summing the interior values of the table. Instead, more accurate totals are provided by calculating the true total, and then perturbing this value. If you attempt to reconstruct a total on the basis of the perturbed interior cells, you are adding together the small changes made to each cell which may result in a large change relative to the perturbed total. It is recommended that totals are constructed in TableBuilder, rather than by summing the interior cells from an exported table.
When calculating proportions, percentages or ratios from cross-classified or small area tables, the introduced random error can be ignored except for small cells. The introduced random adjustments made to cells in a table are independent of the size of the original cell value, so perturbation has the greatest relative impact on small cell values. The information value of the table as a whole is not impaired as small cell values are also strongly affected by other factors, such as sampling error, respondent errors and processing errors.
Caution should be exercised when interpreting and using cells with small values or large percentage Relative standard error (RSE) values. RSEs are provided for survey-based datasets that are subject to sampling variability. Datasets including the full Census of Population and Housing are not weighted so RSEs are not applicable.
When analysing a table of means or sums for a continuous variable, it is recommended that the table be compared to the corresponding table of counts of records with a valid response for that continuous variable. No reliance on estimates of means or sums should be placed on cells with a large RSE or for which the corresponding cell count is small. For more information, see the Summation options for continuous variables section.
- General information about confidentiality and perturbation is provided in the Treating aggregate data in the Data confidentiality guide
- Learn more about Census data
- Census of Population and Housing: Community Profile, DataPack and TableBuilder Templates, Australia, 2016.
- You need to agree to Conditions of use when using TableBuilder. The ABS may impose a limit on the maximum number of tables per user.
Some datasets have an additional quality measure called sparsity applied to tables with too many small cells. Sparsity does not apply to most Census of Population and Housing datasets.
Small cells may not be reliable, as not enough records have been selected in the sample to accurately estimate the population for that combination of characteristics.
If a table has too many small cells the table may not be returned when you click the Retrieve data button. In this example table showing Country of Birth (using the most detailed level of this hierarchical variable) by Social marital status, an exclamation mark symbol displays at the top of the table. Click on the exclamation mark symbol to display an error message indicating that the table is too sparse and has been suppressed.
To continue working, you can try creating a variant of the original table. For example, removing a Not applicable category may reduce the number of small cells in the table and allow the data to be retrieved. Possible methods to reduce the size of the table include:
- removing one or more variables
- removing one or more categories
- using a less detailed level of a hierarchical variable
- creating a custom range to combine less relevant categories.
For this table, the Marital status categories of Not applicable and Married in a defacto marriage were removed. Then the full Country of birth variable was replaced with all categories within Oceania and Antarctica, still at the most detailed level of this hierarchical variable. This table was able to be retrieved.
Relative standard error
Some datasets, such as censuses of a population, are not weighted so the relative standard errors (RSE) do not apply and are not available in TableBuilder. RSEs are available for sample-based datasets that are subject to sampling variability. Refer to the TableBuilder section of each dataset's publication for information on reliability of estimates within these datasets. Publications for each TableBuilder dataset can be accessed from the Available microdata page, or within TableBuilder, click the i link at the top left next to the dataset name when in Table view. This opens in a new tab so you can continue working in TableBuilder.
To view RSEs in TableBuilder for a sampled dataset:
- retrieve the data for your table
- go to Options above the table
- select Relative standard error to display counts, RSEs or both
Sources of variability
There are two sources of uncertainty or variability associated with survey estimates that are released by TableBuilder. The first source of variability is due to sampling and the second is due to random adjustment of cell values.
Variability due to sampling
Since the estimates from surveys may be based on information obtained from a sub-sample of usual residents of a sample of dwellings, they are subject to sampling variability. They may differ from those that would have been produced if all usual residents of all dwellings had been included in the survey. Most weighted datasets in TableBuilder measure this component of variability using the group Jackknife method. These datasets use the Bootstrap method:
- Employee earnings and hours
- Motor vehicle use
- Road freight movements
Variability due to random adjustment
The random adjustment of totals and subtotals introduces another source of variability into the estimates. As these adjustments are generated in a predictable way the impact they have on estimates can be measured directly.
The variability due to sampling and random adjustment is combined into a single measure called the standard error (SE). The standard error indicates the extent to which an estimate might have varied by chance, because only a sample of dwellings was included, and by random adjustment.
There are about two chances in three that a sample estimate differs by less than one standard error from the number that would have been obtained if all dwellings had been included and there was no random adjustment. There are about 19 chances in 20 that the difference is less than two standard errors. Another measure of the likely difference is the relative standard error (RSE), which is obtained by expressing the standard error as a percentage of the estimate.
RSEs of proportions and percentages
Proportions and percentages formed from the ratio of two estimates are also subject to sampling errors. The size of the error depends of the accuracy of both the numerator and denominator. For proportions where the denominator is an estimate of the number of persons in a group and the numerator is the number of persons in a sub-group of the denominator group, the formula to approximate the RSE is given below. The formula is only valid when x is a subset of y.
For proportions where the denominator and numerator are independent estimates, for example a ratio of rates relating to two separate populations such as Indigenous and Non-Indigenous, the formula to approximate the RSE is given below. The formula is only valid when x and y are estimated from separate independent populations, and when the RSEs on x and y are small.
Standard errors may also be used to calculate standard errors for the difference between two survey estimates (numbers or percentages). The sampling error of the difference between the two estimates depends on their individual standard errors and the relationship (correlation) between them. An approximate standard error of the difference between two estimates (x-y) may be calculated by the following formula:
While this formula is only exact for differences between separate and uncorrelated characteristics of subpopulations, it is expected to provide a reasonable approximation for most differences likely to be of interest in relation to this survey.
In TableBuilder, it is the RSE of a percentage that is displayed, from which the standard error may be calculated. For example, if the estimated proportion is 30% with an RSE of 20%, then the standard error for the proportion is 6%.
In some cases, the formula for the approximation of the RSE of a proportion may be unsuitable to use because the RSE of the numerator is very close to, or below, the RSE of the denominator. In this case the RSE is suppressed. It is recommended to use the alternative formula below to calculate the RSE of the proportion if this occurs.
Standard errors of means and sums
The estimates of means and sums of continuous variables are subject to sampling variability and random adjustment. As for population estimates, the variability due to sampling and random adjustment is combined into the calculated Standard Error, and the relative standard error is reported. The component of variability arising from sampling is calculated using either the Jackknife or Bootstrap method, depending on the dataset.
Standard errors of quantiles
The estimates of quantiles such as medians, quartiles, quintiles and deciles are subject to sampling variability and random adjustment. As for population estimates, the variability due to sampling and random adjustment is combined into the calculated Standard Error, and the relative standard error is reported. The component of variability arising from sampling is calculated using the Woodruff method. This is also true for Equal Distribution Quantiles.
Reliability of estimates
Estimates with RSEs of 25% or more are not considered reliable for most purposes. Estimates with RSEs greater than 25% but less than or equal to 50% are annotated by an asterisk (*) to indicate they are subject to high standard errors and should be used with caution. Estimates with RSEs greater than 50% have their RSE suppressed in order to prevent the release of confidential data, and are annotated by a double asterisk (**). These estimates are considered too unreliable for general use. Occasionally an estimate of RSE may be suppressed and displayed as ‘np’ (not published). This occurs because the RSE cannot be estimated reliably, and in this case the RSE should be interpreted as being greater than 50%.
The imprecision due to sampling variability and random adjustment should not be confused with inaccuracies that may occur because of imperfections in reporting by respondents and recording by interviewers, and errors made in coding and processing data. Inaccuracies of this kind are referred to as non-sampling error, and they may occur in any enumeration, whether it be a full count or a sample. Every effort is made to reduce non-sampling error to a minimum by careful design of questionnaires, intensive training and supervision of interviewers, and efficient operating procedures.
Getting access, troubleshooting tables, graphs and maps, data and system performance
How do I access TableBuilder?
Register in the ABS Registration Centre to access datasets in TableBuilder.
- You automatically get access to basic datasets (free) by registering
- If you register with your organisation email address, and your organisation is already registered, you also automatically get access to Census TableBuilder Pro (free) and any other datasets your organisation has subscribed to (paid)
How much does TableBuilder cost?
- Basic datasets are free, including Census TableBuilder Basic and Businesses in Australia
- To access Census TableBuilder Pro (free) you need to join your organisation in the Registration Centre
- Other datasets can be accessed by purchasing a subscription
I have forgotten my password/user ID
Select the forgotten password or user ID link on the TableBuilder log in page and follow the prompts.
If you have forgotten which email you registered with or your secret question and answer, contact email@example.com.
I cannot log in with my email address
TableBuilder user ID is a number. If you have forgotten your user ID, click on forgotten user ID from the TableBuilder log in page.
How do I update my personal details
Log into the Registration Centre using the same user ID and password that you use for TableBuilder.
You can update:
- your address
- phone number
- secret question/answer
You can also see which organisation you are a member of and see all the data series that you have access to.
How do I update my email address?
Your email address must match your organisation, and this can only be updated by an ABS staff member.
If you have changed your email address because you have changed organisations, ABS will remove you from your old organisation and add to your new organisation. This will give you access to your new organisation's subscribed paid products.
Using your new email account, email firstname.lastname@example.org with:
- your name
- the names of your former and current organisations
- your old email address
- your user ID number
If you have changed your email address because you have changed your name, email email@example.com using your new email account with:
- your former and current names
- the name of your organisation
- your user ID number
Can I share my log in details with colleagues or friends so they can access ABS registered products?
- Each user needs to register individually in their own name
- You have agreed to Conditions of use that you will not share your access credentials with any other person, including other people in your organisation
- Additional organisation users can access your organisation's paid subscriptions for free
- If users or organisations are found to have breached the conditions of use, access may be revoked
Tables, maps and graphs
What are the largest tables, graphs or maps I can create in TableBuilder?
- Tables where you can retrieve data on screen: 10,000 cells.
- Large tables (need to be queued for retrieval): 40 million cells, including totals and wafers. Large tables may take several hours or days to produce depending on the size of the table and other large tables in the queue
- Graphs: 1,000 cells
- Maps: 1,000 cells
- Download tables:
- Excel 2007 has a limit of 16,384 columns x 65,000 rows and less than 100,000 cells.
- use CSV to download larger tables
How can I reduce the size of a large table?
Options to reduce the size of your table include:
- Remove categories that you may not be interested in, such as Not applicable categories.
- Group categories together that you want to include but do not need to view separately, by creating a Custom data group.
How can I display my table more effectively?
There are a number of options to improve your displayed table layout. These do not affect your total cell count for Large table mode.
- Hide totals, by clicking on the three dots menu beside each variable within your table headings and unticking Total.
- Select Zero suppression for rows and/or columns in the Options menu. This hides rows or columns where all cells are zeros. If you are using wafers, then this option hides rows or columns where all cells are zeros across all wafers, so rows or columns of zeros may appear in some wafers.
I can't add mesh blocks to my table
TableBuilder has a limit of adding 60,000 categories from any one variable to a table. As there are more than 60,000 mesh blocks in each of Australia, New South Wales, Victoria and Queensland you need to select fewer geographic categories when using mesh blocks. If you have already ticked too many mesh blocks, click untick all to start again.
Why do I have dashes in my table?
Tables that have not yet retrieved data are displayed with dashes instead of data, and only the table structure is displayed.
- for small to medium tables, click Retrieve data to view your table on screen
- if you are in large table mode, with over 10,000 cells, click Queue table in the top right corner. To view your table data, download it once it has completed.
Can I upload my table, graph or map back into TableBuilder?
No, you can only save tables in TableBuilder and then open them in a later session.
To re-open a map or graph in a later session you need to save the table used to create the map or graph. Then click on Graph view or Map view to view them again.
You can share and upload custom data variables that you have created either inside or outside TableBuilder.
After editing or sharing a custom group, upload is not working
There are a number of errors that can occur when Uploading custom data including:
- leading zeros have been dropped when editing in Excel
- reusing an existing custom data group name
- not having access to the right dataset, or not having that dataset open when uploading
- errors in the header row
- loading a file type other than CSV
- file is too large (greater than 20MB)
My table with nested variables on a row, column or wafer is causing problems
Nested variables (multiple variables nested on one row, column or wafer) can cause issues for some TableBuilder functions:
- Nesting up to 10 variables is possible for some variables but may cause performance issues. Nesting fewer variables is recommended, particularly for large classifications.
- Mapping is not available if a geographic field is nested. Mapping is only available if the mappable geographic variable (indicated by a green globe icon) is on a row or column axis by itself. Other variables may be nested on the opposite axis or in the wafers.
- Not all download formats are supported for nested variables.
I cannot download my table or my downloaded table does not include all of the table features
My classifications/map view are not displaying properly
You may need to upgrade your web browser.
Map view is only available for some datasets, where the geographic variables indicate they are mappable via the green globe icon.
KMZ downloaded files are missing areas when uploaded to Google Earth
Only use the online version of Google Earth in a Chrome browser. You need to save your downloaded KMZ file first and make sure settings are set to 'enable KML file import'.
The category labels in my graph do not display properly in Graph view
If the category labels are very long, they may not be suitable to graph in TableBuilder. If the category labels are too long, they may be truncated with "..." in the key below the graph and in the text that appears when clicking on the graph.
You can edit the category labels in the Graph view, however you cannot save graphs, so if you return to Table view and then back to Graph view, your changes are lost.
To best display your graph, download the table and use the graph options in another application such as Excel.
The category labels in my graph do not all display when I download my graph
If there are too many categories in a graphed variable, only the first page of categories displays in the downloaded PDF or PNG. Instead of graphing in TableBuilder, then downloading the graph, download the table instead.
To best display your graph, download the table and use the graph options in another application such as Excel.
Which geographic areas and variables are available in TableBuilder?
A list of geographic areas, variables and classifications is available for Census TableBuilder. The data item list is available on the Downloads tab.
In TableBuilder on the Table view, the i links next to each dataset name link to the associated web information and data item list.
Is Census data before 2006 available in TableBuilder?
No. TableBuilder includes Census data from 2006 onwards. See Historical Census Data for earlier data.
Can I create my own variables and classifications to use in a table?
- You can create a new category by collapsing an existing variable categories. For example, Age categories in single years can be collapsed to create a new category for 0-17 year olds. See Custom data.
- Multiple variables cannot be combined to create a new variable. For example, Age and Sex cannot be merged to create a single variable. However, filters can be used to display certain categories only. For example, Sex=Male and Age=17 can be added as filters to a table so that the data in a table applies only to male 17 year olds. See Add and remove a filter.
- You can also upload your own variable classifications. New classifications must use existing variable categories within TableBuilder. For example, a new geographic classification that has been constructed using mesh blocks can be uploaded to TableBuilder. See Custom data.
Why do I have only zeroes in my table?
There are several reasons this may happen:
- Sparsity settings may prevent your table from displaying data. Some datasets have an additional quality measure applied to tables with too many very small cells. This measure is particularly relevant to survey datasets and has not been applied to Census TableBuilder datasets. Very small cells of a table using survey data may not be reliable, as not enough records have been selected in the sample to accurately estimate the population for that combination of characteristics.
- The ABS sometimes releases 'shell tables' in advance of releasing a dataset, to allow you to become familiar with the variables and structure of the dataset and to set up and save tables for future use. If your table includes variables that have not been released yet in the dataset you are using, it shows zeros.
- There may be an outage with the TableBuilder system. If the issue is not caused by sparsity or shell tables, report the issue by emailing firstname.lastname@example.org.
How does perturbation affect my results?
Perturbation is applied across all non-zero cells in a table, including the totals cells. Perturbation may change the true cell value by either increasing or decreasing the value by a small amount. This introduces almost no bias. However, small cells may change by a large amount in proportion to the true value, and therefore should not be relied upon. Other factors also affect the reliability of small cells, such as sampling error, respondent errors and processing errors.
Why don't the interior cells in my table add up to the totals displayed?
All non-zero cells in tables are subject to perturbation, a small adjustment made to cell values, including totals, to protect the confidentiality of the data. In TableBuilder, totals are not calculated by summing the interior values of the table. Instead, more accurate totals are provided by calculating the true total, and then perturbing this value.
Some older TableBuilder datasets use the additivity technique to make further adjustments to the data to ensure that the interior cells add up to the totals. As additivity is not required for confidentiality purposes, most datasets in TableBuilder do not use the additivity technique. The Census of Population and Housing datasets used this technique until June 2017, when it was removed from all Census TableBuilder datasets.
Why is there sometimes such a large difference between the sum of the interior cells and totals displayed?
Perturbation makes small changes to all estimates including both the interior cells of the table and the totals. If you attempt to reconstruct a total on the basis of the perturbed interior cells, you are adding together the small changes made to each cell which may result in a large change relative to the perturbed total. It is recommended that totals are constructed in TableBuilder, rather than by summing the interior cells from an exported table.
Can I create medians and means in TableBuilder?
Summation options for continuous variables, such as sums, medians and means can be created in TableBuilder for continuous variables. Some datasets, such as Census TableBuilder, contain only categorical variables. To create medians and means for categorical variables, download the data into a spreadsheet to generate these formulas.
TableBuilder is timing out
TableBuilder times out when no action has been taken for 30 minutes. Log in again using your user ID and password.
I cannot retrieve my table, the Retrieve button is not working
If your table exceeds 10,000 cells it is in Large table mode. Use the Queue table button to run your table, and then download the table from the Large tables view (via the three vertical dots menu in the top right corner).
When I submit a large table, it is not returned
Large tables (over 10,000 cells) are sent to a queue for processing. The time it takes for the system to process and return your table depends on size of your table and the number of other tables in the queue. Large tables may take several hours or days to process. Check the Saved and large tables screen (via the three vertical dots menu at the top right) to see if your large table has finished processing. You can download it once it has completed. You can also go back into your large table outline to make further changes by clicking on View.
If your large table has still not returned after two days, contact email@example.com.
It takes a long time to add a new variable to my table
Check that you do not have the Automatically retrieve data option (looped arrow on the Retrieve data button) selected. When this option is activated, TableBuilder automatically updates the data whenever the table is changed, which can be slow for large tables or large datasets.
While in large table mode, it can be slow to drag variables between rows, columns and wafers. This may happen for:
- large datasets
- large variable classifications with hundreds or thousands of categories.
When I search all datasets my results are incomplete
The all datasets search (top right corner) returns a maximum of 2000 results per type of result:
- tables (saved or predefined)
If your search exceeds 2000 for one of these search types, TableBuilder displays (2000+) in red in the bottom left corner against that type. You can:
- refine your search to a more specific term to return complete results
- use the dataset specific search to view results for that dataset only - open the dataset you are interested in and use the dataset search in the bottom left corner
When I search all datasets TableBuilder is stuck at the loading screen
For some searches, your search may get stuck at the loading screen, and not return your results. To resolve this error, follow the steps to close the session and clear the cache.
In Custom data, is there a limit on the number of areas that can be included in my custom geographic area
There is no limit on the number of areas that can be included for your custom group. However, when you are editing very large number of areas the system may slow down.
I cannot retrieve a map, Map view is not working
- you have included a mappable geographic variable, indicated by a green globe icon
- your geographical field is not nested with another variable - it must be by itself on a row or column
- you have not mapped more than 1000 cells - you might need to create several tables or maps when using mesh blocks
- you are using an up to date browser
I have missing map areas in my KMZ download file
To fix this either:
- Upload your file using the online version of Google Earth in a Chrome browser. You need to save your downloaded KMZ file first and make sure settings are set to 'enable KML file import'.
- Extract your data from TableBuilder and download the relevant geographic boundaries from ASGS publication. Then join them together in MapInfo to create your map or do spatial analysis.
An error message box is displayed asking you to contact your administrator
If you get an error 'The requested URL was rejected. Please consult with your administrator.' you need to provide details of the actions you were performing in TableBuilder when the error occurred. Send the details to firstname.lastname@example.org.
TableBuilder takes a long time on the log in page or when I open TableBuilder
There is a known issue with some browsers where the 'processing' blue circle appears even though no action is underway. Move your cursor so that this disappears and you can continue working.
I am having a technical problem with TableBuilder, how do I report this
View video tutorials to get started and learn about basic TableBuilder features
Video tutorials are currently being updated. You can continue to use the earlier videos for help with most features while we are working on the new videos.
|YouTube TableBuilder tutorials||Transcripts|
\(\Large ⏯️\) TableBuilder basic tables
\(\Huge 🗎\) TableBuilder basic tables transcript
\(\Large ⏯️\) TableBuilder large tables
\(\Huge 🗎\) TableBuilder large tables transcript
\(\Large ⏯️\) TableBuilder custom groups
\(\Huge 🗎\) TableBuilder custom data transcript
\(\Large ⏯️\) TableBuilder graphs and maps
\(\Huge 🗎\) TableBuilder graphs and maps transcript