Census Variables Reference¶

This page provides a complete reference of all census variables available in SocialMapper. These variables can be used with the variables parameter in the get_census_data() function.

Variable Usage¶

Census variables can be specified using either their human-readable names or their official U.S. Census Bureau variable codes:

from socialmapper import create_isochrone, get_census_data

# Create an isochrone
iso = create_isochrone((45.5152, -122.6784), travel_time=15)

# Using human-readable names
census_data = get_census_data(iso, ["population", "median_income"])

# Using census codes
census_data = get_census_data(iso, ["B01003_001E", "B19013_001E"])

# Mixing both formats
census_data = get_census_data(iso, ["total_population", "B19013_001E"])

Available Variables¶

Population Metrics¶

Human-Readable Name	Census Code	Description
`population`	B01003_001E	Total population count
`total_population`	B01003_001E	Total population count (alias)

Economic Indicators¶

Human-Readable Name	Census Code	Description
`median_income`	B19013_001E	Median household income in the past 12 months (in inflation-adjusted dollars)
`median_household_income`	B19013_001E	Median household income (alias)
`percent_poverty`	B17001_002E	Population for whom poverty status is determined

Housing Characteristics¶

Human-Readable Name	Census Code	Description
`households`	B11001_001E	Total number of households
`housing_units`	B25001_001E	Total housing units
`median_home_value`	B25077_001E	Median value of owner-occupied housing units

Demographic Characteristics¶

Human-Readable Name	Census Code	Description
`median_age`	B01002_001E	Median age of the population
`white_population`	B02001_002E	White alone population
`black_population`	B02001_003E	Black or African American alone population
`hispanic_population`	B03003_003E	Hispanic or Latino population

Education¶

Human-Readable Name	Census Code	Description
`education_bachelors_plus`	B15003_022E	Population 25 years and over with a bachelor's degree or higher

Transportation¶

Human-Readable Name	Census Code	Description
`percent_without_vehicle`	B25044_003E + B25044_010E	Households without a vehicle available (calculated)
`households_no_vehicle`	B25044_003E + B25044_010E	Households without a vehicle available (alias)

Calculated Variables¶

Some variables are calculated from multiple census codes:

percent_without_vehicle / households_no_vehicle: Sum of owner-occupied households with no vehicle (B25044_003E) and renter-occupied households with no vehicle (B25044_010E)

Data Source¶

All census data comes from the American Community Survey (ACS) 5-Year Estimates, which provides the most reliable data for small geographic areas. The default year is 2021, but data from 2019-2023 is available.

Geographic Levels¶

Census variables can be retrieved at different geographic levels:

Block Group (default): The smallest geographic unit, typically containing 600-3,000 people
ZCTA: ZIP Code Tabulation Areas can be queried directly using get_census_blocks() with specific parameters

Note: The current API returns block group level data by default when using isochrones.

Examples¶

Basic demographic analysis¶

from socialmapper import create_isochrone, get_census_data

iso = create_isochrone((30.2672, -97.7431), travel_time=15)  # Austin, TX
data = get_census_data(iso, ["population", "median_age", "median_income"])

Equity-focused analysis¶

from socialmapper import create_isochrone, get_census_data

iso = create_isochrone((41.8781, -87.6298), travel_time=15)  # Chicago, IL
data = get_census_data(iso, ["percent_poverty", "median_income"])

Housing market analysis¶

from socialmapper import create_isochrone, get_census_data

iso = create_isochrone((47.6062, -122.3321), travel_time=15)  # Seattle, WA
data = get_census_data(iso, ["median_home_value", "median_income", "households"])

Comprehensive community profile¶

from socialmapper import create_isochrone, get_census_data

iso = create_isochrone((42.3601, -71.0589), travel_time=15)  # Boston, MA
data = get_census_data(
    iso,
    ["population", "median_age", "median_income", "percent_poverty"]
)

Advanced Usage¶

When using the Python API, you can use census variable names or codes:

from socialmapper import create_isochrone, get_census_data

# Create an isochrone
iso = create_isochrone(
    location=(45.5152, -122.6784),  # Portland, OR
    travel_time=15,
    travel_mode="drive"
)

# Get census data with mixed formats
census_data = get_census_data(
    location=iso,
    variables=["population", "median_income", "B01002_001E"],  # Mix of formats
    year=2023
)

Notes¶

Variable names are case-insensitive (population and POPULATION are equivalent)
The system automatically handles both human-readable names and census codes
All monetary values are in inflation-adjusted dollars for the survey year
Some variables may have null values for certain geographic areas due to data suppression or small sample sizes