Census Variables

Census variables provide demographic, economic, and social data that you can use to enrich your datasets. This reference covers the kinds of variables available and how to use them.

Variable codes are country-specific and depend on the source dataset loaded for each country. The codes below are illustrative examples of the categories you'll find — the exact set of codes available for a given country is what you select from when configuring a Geo Profiling node.

Variable Categories

Population Variables

Basic population counts and demographics.

Age Distribution

Age-based breakdowns of the population.

Household Variables

Information about housing and households.

Economic Variables

Income, employment, and economic indicators.

Education Variables

Educational attainment statistics.

Statistical Measures

For each variable, you can access multiple statistical representations.

Raw Values

The actual count or amount for the area.

Population of Area X = 15,234 people

Use raw values when you need:

• Absolute numbers for reporting
• Input for your own calculations
• Data for external systems

Z-Scores

Standard deviations from the national mean. Shows how an area compares to the overall distribution.

Use Z-scores when you need:

• Identify outliers
• Compare areas of different sizes
• Statistical analysis

Deciles

Distribution position from 1 (lowest) to 10 (highest), where decile 1 is the bottom 10% of areas and decile 10 is the top 10%. Deciles roll up into three tiers:

Use deciles when you need:

• Simple ranking comparisons
• Non-technical reporting
• Visualization categories

Using Variables in Automations

Adding Census Variables

1. Add a Geo Profiling node to your automation
2. Connect your data source (records must have latitude and longitude columns)
3. Configure the node:
   • Set the latitude and longitude columns
   • Choose the country and aggregation level
   • Choose which census variables to add

The node looks up the census area containing each record's coordinates and appends the selected variables as new columns (prefixed with census_ by default).

Example Configuration

Input columns: [customer_id, lat, lng, name]
                        ↓
            Geo Profiling node configuration:
            - Latitude column: lat
            - Longitude column: lng
            - Country: SWE
            - Level: municipality
            - Variables: P_PERS, E_INCOME_MEDIAN
                        ↓
Output columns: [customer_id, lat, lng, name,
                 census_P_PERS, census_E_INCOME_MEDIAN]

See the Geo Profiling node reference for the full field list.

Querying Variables

Variable Availability

Not all variables are available at every geographic level — coverage depends on the source dataset for each country. In general, core population counts are available at every level, while more detailed breakdowns (household, economic, education) may only be published down to coarser levels. The Geo Profiling node only offers variables that exist for the country and level you select, so configure those first and choose from the available list.

Data Currency

Census data is updated periodically:

• Annual updates: Population, household counts
• Census years: Detailed demographics (every 5-10 years)
• Economic data: Annual or quarterly depending on source

The lastUpdated field indicates when data was last refreshed.

Best Practices

Selecting Variables

• Start focused: Select only variables relevant to your analysis
• Consider correlation: Related variables may provide redundant information
• Check coverage: Ensure variables are available at your target geographic level

Interpreting Results

• Context matters: A Z-score of 1.5 means different things for income vs. age
• Sample sizes: Small areas may have less reliable statistics
• Time sensitivity: Economic data changes faster than demographic data

Combining with Your Data

• Match granularity: Use the most detailed geographic level that your data supports
• Aggregate carefully: When combining areas, weight by population
• Document assumptions: Note which variables were used and why

Troubleshooting

Variable Not Found

• Verify the variable code is correct (case-sensitive)
• Check if the variable is available for your geographic level
• Ensure the country has this data available

Missing Values

• Some areas may lack data for certain variables
• Check if the area is too small for reliable statistics
• Missing values are represented as null

Unexpected Values

• Verify your geographic codes are correct
• Check if boundaries have changed recently
• Compare against official statistics to validate