Understanding the Data

This guide explains the structure of the data served by the PrairieCloud API: what datasets are available, how vintages work, how geography is specified, and how to find the right variables for your query.

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Available Datasets

PrairieCloud serves data from the American Community Survey (ACS), the most comprehensive source of socioeconomic data about U.S. communities. The API contains 901.6 million observations across 392,435 geographies and 35 vintages.

Dataset Key	Full Name	Vintages	Geographies	Best For
acs5	ACS 5-Year Estimates	2009–2024 (16 vintages)	392,435 geographies across 7 levels	Most reliable estimates, small-area data
acs1	ACS 1-Year Estimates	2005–2024 (19 vintages, no 2020)	Areas with 65K+ population (~1,700–1,900 geographies)	Most current single-year data

ACS 5-Year vs. 1-Year: Which Should I Use?

• ACS 5-Year (acs5) combines five years of survey data. It covers every geography down to block groups and is the most statistically reliable. Use it when precision matters or when querying small areas.
• ACS 1-Year (acs1) reflects a single year's data. It's more current but has higher margins of error and only covers areas with 65,000+ population. Use it when you need the latest snapshot for larger areas.
• 2020 note: The ACS 1-Year was not released for 2020 due to COVID-19 data collection disruptions. The ACS 5-Year 2020 vintage is available.

Use dataset in your request

curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=pop_total&geo=state:48&dataset=acs5"

acs5 is the default — you can omit the dataset parameter if you want ACS 5-Year. To query ACS 1-Year, set dataset=acs1.

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Vintages

For ACS 5-Year, a vintage is the ending year of the 5-year survey period. For example, vintage 2023 covers survey years 2019–2023. For ACS 1-Year, the vintage is simply the survey year.

Available Vintages

Vintage	Survey Period	Status
2009	2005–2009	✅ Available
2010	2006–2010	✅ Available
2011	2007–2011	✅ Available
2012	2008–2012	✅ Available
2013	2009–2013	✅ Available
2014	2010–2014	✅ Available
2015	2011–2015	✅ Available
2016	2012–2016	✅ Available
2017	2013–2017	✅ Available
2018	2014–2018	✅ Available
2019	2015–2019	✅ Available
2020	2016–2020	✅ Available
2021	2017–2021	✅ Available
2022	2018–2022	✅ Available
2023	2019–2023	✅ Available
2024	2020–2024	✅ Available (default)

Up to 19 vintages of historical data

PrairieCloud serves every ACS 5-Year vintage since 2009 (16 vintages) and every ACS 1-Year vintage since 2005 (19 vintages, no 2020). Not all variables are available in every vintage — the Census Bureau restructures table definitions between releases. Use the variable detail endpoint to check availability for a specific variable, or let the /v1/timeseries endpoint return null for vintages where a variable doesn't exist.

The API defaults to the most recent loaded vintage when you omit the vintage parameter.

Specifying a Vintage

# Get 2022 vintage data
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=income_median_household&geo=state:48&vintage=2022"

Checking Variable Availability

Not all variables are available for every vintage. Use the variable detail endpoint to check:

curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/variables/income_median_household"

The response includes an availability array listing which dataset/vintage combinations carry that variable.

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Geography Types

PrairieCloud uses a consistent {type}:{fips} format for all geography specifiers. The API covers 392,435 geographies across 7 levels, from the entire nation down to individual block groups.

Supported Geography Types

Type	Key Format	Example	Count	Direct data lookup
Nation	nation:us	nation:us	1	Free
State	state:{2-digit FIPS}	state:48	52	Free
County	county:{5-digit FIPS}	county:48201	3,222	Free
Metro	metro:{CBSA code}	metro:12420	935	Free
Congressional District	cd:{4-digit code}	cd:4801	436	Free
Tract	tract:{11-digit FIPS}	tract:48201311100	85,396	Free
Block Group	block_group:{12-digit FIPS}	block_group:482013111001	242,297	Free

What tiers control

Every tier can query an individual geography directly by FIPS code or resolved name, including tracts and block groups. Tiering controls higher-scale workflows:

• Wildcard expansion: Pro adds tract wildcard expansion; Business adds block group wildcard expansion.
• Boundary and centroid access: Free includes nation/state, Pioneer adds county/metro/CD, Pro adds tract, and Business adds block group.
• Inline geometry: Pro+ can request include_geometry=true; block group inline geometry starts at Business.
• Enterprise: Adds 500k cartographic boundary resolution where available plus custom boundary delivery options.

Requesting a gated workflow above your tier returns a 403 error with an upgrade URL.

FIPS Codes Explained

FIPS (Federal Information Processing Standards) codes are the standardized identifiers for U.S. geographies:

• State FIPS — 2 digits: 01 (Alabama), 06 (California), 48 (Texas)
• County FIPS — 5 digits: state FIPS + 3-digit county code. Example: 48201 = Harris County, Texas (state 48 + county 201)
• CBSA codes — 5 digits identifying metropolitan and micropolitan statistical areas. Example: 12420 = Austin-Round Rock-Georgetown, TX
• Tract FIPS — 11 digits: state FIPS + county FIPS + 6-digit tract code. Example: 48201311100 = a tract in Harris County, Texas (state 48 + county 201 + tract 311100)
• Block Group FIPS — 12 digits: tract FIPS + 1-digit block group number. Example: 482013111001 = block group 1 within tract 48201311100

Leading zeros matter. state:6 will fail; use state:06.

Browsing Geographies

Use the geography catalog endpoint to search for geographies by name:

# Search for all counties in Texas
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies?type=county&parent=state:48"

# Search by name
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies?search=harris"

# List tracts within a county
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies?type=tract&parent=county:48201"

Wildcard Geography Queries

Pro tier and above

Wildcard geography queries require a Pro plan or higher.

Use a * suffix to expand a geography pattern to all matching FIPS codes. This is useful when you want data for all counties in a state without listing every FIPS code individually.

Syntax: geo={type}:{prefix}*

# All counties in Texas (FIPS 48)
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=pop_total&geo=county:48*"

# All tracts in Harris County, Texas
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=pop_total&geo=tract:48201*"

The wildcard expands server-side to all matching geographies and returns one result per match. Tier limits apply to the number of expanded geographies:

Plan	Max Expanded Geographies
Free	25 (no wildcard feature)
Pioneer	500 (no wildcard feature)
Pro	5,000
Business	25,000
Enterprise	50,000

If the expansion exceeds your tier limit, the API returns a 403 error with an upgrade URL. See Tier-Gated Features for details.

Wildcard queries cost more

Wildcard queries consume additional rate limit units based on the number of expanded geographies: ceil(expanded_geos / 10) units. See Rate Limiting for details.

Smart Geography Resolution

You don't need to memorize FIPS codes to query sub-geography data. The API can resolve parent geography names into the correct FIPS prefix automatically.

Instead of looking up that Harris County, Texas is FIPS 48201, just write:

# All tracts in Harris County, Texas — resolved automatically
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=pop_total&geo=tract:Harris County, Texas"

# Equivalent FIPS-based wildcard (what the API expands it to internally)
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=pop_total&geo=tract:48201*"

The resolver detects the mismatch between the requested geography type (tract) and the value type (a county name), resolves the parent to its FIPS code, and wildcards to match all children.

Supported patterns:

Query	Resolves To	Description
tract:Travis County, Texas	tract:48453*	All tracts in Travis County
tract:TX or tract:Texas	tract:48*	All tracts in Texas
block_group:Harris County, TX	block_group:48201*	All block groups in Harris County
county:Texas	county:48*	All 254 counties in Texas
county:TX	county:48*	Same — state abbreviations work
tract:Dallas-Fort Worth	Resolves metro → looks up 11 component counties → expands tracts across all	Pro+ wildcard limits apply
block_group:Austin	Same pattern for block groups via metro crosswalk	Business+ wildcard expansion
county:Dallas-Fort Worth	Returns all component counties of the metro	Pro+ wildcard expansion
tract:TX-7	tract:4807* (crosswalk)	All tracts in Texas Congressional District 7
tract:Texas-7	Same as above	Full state name works too
tract:Congressional District 7, Texas	Same as above	Fuzzy name lookup
block_group:TX-7	All block groups in TX CD 7 via crosswalk	Business+ wildcard expansion
county:TX-7	Counties that overlap with TX CD 7	Pro+ wildcard expansion

Works for all 7 geography types

Smart resolution works for any geography type where FIPS codes encode a parent-child hierarchy: tract, block_group, and county with state or county parent names. It also works with metro area names (the resolver matches the name to a CBSA, looks up the component counties via a crosswalk table, and expands to all child geographies across those counties — all 935 CBSAs supported) and congressional district names (the resolver matches the district, looks up component tracts via a CD-to-tract crosswalk table, and expands accordingly — all 444 congressional districts supported, 118th Congress).

Congressional district shorthand format: Use the state abbreviation + dash + district number — e.g., TX-7 for Texas's 7th Congressional District. Full state names (Texas-7) and fuzzy name lookup (Congressional District 7, Texas) also work.

Metro and CD resolution use crosswalk tables

Unlike state and county resolution (which uses FIPS prefix matching), metro resolution uses a CBSA-to-county crosswalk table and congressional district resolution uses a CD-to-tract crosswalk table. This is necessary because these geography types span non-contiguous areas that don't share a common FIPS prefix. For example, the Dallas-Fort Worth metro (CBSA 19100) includes 11 counties across multiple FIPS ranges, and congressional districts can include tracts from multiple counties. The CD crosswalk contains 90,467 mappings across all 444 districts (118th Congress). Note that 4,868 tracts straddle two congressional districts and are included in both.

Wildcard limits still apply

Smart geo resolution expands to a wildcard query under the hood, so the same tier-based expansion limits apply. See the wildcard limits table above.

Children Endpoint

Use the children endpoint to discover what geographies exist within a parent — without needing to know FIPS codes or hierarchy rules in advance.

GET /v1/geographies/{geo_key}/children?type=tract&limit=50&offset=0

# List all counties in Texas
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies/state:48/children?type=county"

# List all tracts in Harris County
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies/county:48201/children?type=tract&limit=50"

# Works with names too — list tracts in Travis County, Texas
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies/state:TX/children?type=county"

The response uses the standard APIResponse envelope with paginated results:

{
  "data": [
    {
      "geo_key": "county:48001",
      "name": "Anderson County, Texas",
      "geo_type": "county",
      "fips_code": "48001"
    }
  ],
  "meta": {
    "total_count": 254,
    "limit": 50,
    "offset": 0
  }
}

Metros as parents:

# List all counties in the Dallas-Fort Worth metro
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies/metro:19100/children?type=county"

# List all tracts in the Dallas-Fort Worth metro (deep)
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies/metro:19100/children?type=tract&limit=50"

Congressional districts as parents:

# List all tracts in Texas Congressional District 7
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies/cd:4807/children?type=tract"

# List all block groups in TX CD 7
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies/cd:4807/children?type=block_group&limit=50"

# List counties that overlap with TX CD 7
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/geographies/cd:4807/children?type=county"

Valid parent → child combinations:

Parent	Allowed Child Types
nation	state
state	county, cd, tract (deep), block_group (deep)
metro	county, tract (deep), block_group (deep)
cd	county, tract, block_group (deep)
county	tract, block_group (deep)
tract	block_group

Tier-aware pagination

The children endpoint respects your plan's geography tier access. You'll only see child types your tier can access. Pagination defaults: limit=50, offset=0.

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Variable Naming Conventions

Variable names (api_name) in PrairieCloud use topic-prefixed, human-readable names that are concise and consistent:

{topic}_{measure}

Examples:
  pop_total
  pop_male
  income_median_household
  tenure_owner_occupied
  edu_bachelors_degree
  poverty_below
  employ_unemployed

The naming is designed to be:

• Concise — short enough to use comfortably in code and URLs
• Self-describing — the topic prefix groups related variables together
• Stable — api_name values do not change between vintages

Census Code Aliases

Every variable also has a census_code (e.g., B01001_001E) that you can use interchangeably with the api_name. This makes migration from the Census Bureau API seamless:

# These two requests return the same data:
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=pop_total&geo=state:48"

curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=B01001_001E&geo=state:48"

The variable list and detail endpoints include a census_code field so you can always find the mapping.

Units

Unit	Description
count	An integer count of people, housing units, etc.
dollar	A monetary value in nominal U.S. dollars
percent	A percentage (0–100 scale)
year	A year value (e.g., median year structure built)
minutes	A duration in minutes (e.g., commute time)

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Variable Catalog Overview

PrairieCloud serves 392 curated variables across 53 Detailed Tables (B/C-tables) from the Census Bureau. These variables are specifically chosen to support composite index computation — Social Vulnerability Index (SVI), Area Deprivation Index (ADI), EJScreen, and similar indicators used in research, public health, and policy analysis.

Variables by Topic

Topic	Variables	What's Covered
Core	238	Population, age, sex, race, ethnicity, education, income, poverty, employment
Housing	85	Occupancy, tenure, home values, rent, mortgage costs, units in structure
Transport	26	Commuting mode, travel time, vehicles available
Equity	19	Disability, language barriers, nativity, veteran status
Health	14	Health insurance coverage, uninsured rates
Environment	10	Housing age, heating fuel, plumbing/kitchen facilities

392 focused variables, not 1,861 scattered ones

The v2 catalog replaces the previous 1,861-variable catalog (Data Profile DP02–DP05 + 30 B-tables) with 392 curated variables from 53 B/C-tables. The focus is on variables that matter for composite indices, spatial analysis, and equity research — not exhaustive Census coverage. Every variable in the catalog pulls from stable Detailed Tables (B/C-tables), which don't renumber between releases like Data Profile tables did.

Key Variables

These are the most commonly requested variables. Use the exact api_name values in your API calls.

Population & Demographics

Variable	api_name	Census Code	Unit
Total population	pop_total	B01001_001E	count
Male population	pop_male	B01001_002E	count
Female population	pop_female	B01001_026E	count
Male: Under 5 years	pop_male_under_5	B01001_003E	count
Female: Under 5 years	pop_female_under_5	B01001_027E	count
Total population under 18	child_pop_total_under_18	B09001_001E	count
White alone	race_white_alone	B02001_002E	count
Black or African American alone	race_black_alone	B02001_003E	count
Asian alone	race_asian_alone	B02001_005E	count
Hispanic or Latino	hispanic_latino	B03002_003E	count

Education & Income

Variable	api_name	Census Code	Unit
High school diploma	edu_hs_diploma	B15003_017E	count
Bachelor's degree	edu_bachelors_degree	B15003_022E	count
Median household income	income_median_household	B19013_001E	dollar

Employment

Variable	api_name	Census Code	Unit
In labor force (16+)	employ_in_labor_force	B23025_002E	count
Unemployed	employ_unemployed	B23025_005E	count

Health Insurance

Variable	api_name	Census Code	Unit
Total civilian noninstitutionalized pop	health_ins_total_civilian	B27001_001E	count

Housing

Variable	api_name	Census Code	Unit
Total housing units	housing_total_units	B25001_001E	count
Occupied housing units	housing_occupied	B25002_002E	count
Owner-occupied units	tenure_owner_occupied	B25003_002E	count
Renter-occupied units	tenure_renter_occupied	B25003_003E	count
Median home value	housing_median_value	B25077_001E	dollar
Median gross rent	rent_median_gross	B25064_001E	dollar

Poverty & Transportation

Variable	api_name	Census Code	Unit
Population below poverty level	poverty_below	B17001_002E	count
Commute mode total	commute_mode_total	B08301_001E	count

Variable Coverage by Vintage

The v2 catalog uses stable Detailed Tables (B/C-tables) rather than Data Profile tables. B-table Census codes don't renumber between releases the way DP-table codes did, which means coverage is more consistent across vintages.

However, the Census Bureau does occasionally restructure tables — adding new variables, splitting table groups, or retiring categories. This means not all 392 variables are available in every vintage. Coverage is highest for recent vintages and drops off for older ones.

Check the variable detail endpoint

Use GET /v1/variables/{api_name} to see the exact vintage availability for any variable. When querying a variable that doesn't exist for a given vintage, the API returns null for that value rather than an error.

Tract and block group data is available for ACS 5-Year vintages 2017–2024. Older vintages cover nation, state, county, metro, and congressional district geographies.

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Discovering Variables

Browse the Full Catalog

curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/variables?limit=50&offset=0"

Search by Keyword

# Search for variables related to income
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/variables?search=income"

# Filter by topic
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/variables?topic=core"

# Filter by unit
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/variables?unit=dollar"

Search by Census Bureau Code

If you already know the Census Bureau variable code (e.g., B01001_001E), you can use it directly in data queries or search for the PrairieCloud api_name:

# Use the Census code directly in a data query
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=B01001_001E&geo=state:48"

# Or search to find the api_name mapping
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/variables?search=B01001_001E"

The response includes a census_code field showing the Census Bureau code for each variable:

{
  "data": [
    {
      "api_name": "pop_total",
      "census_code": "B01001_001E",
      "label": "Total population",
      "topic": "core",
      "unit": "count"
    }
  ]
}

This makes migration from the Census Bureau API seamless — search by the codes you already use, or pass them directly to the data endpoint.

Topics Endpoint

Use GET /v1/topics to list all variable topics with counts of active variables:

curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/topics"

{
  "data": [
    { "topic_key": "core", "label": "Core Demographics", "variable_count": 98 },
    { "topic_key": "demographics", "label": "Demographics", "variable_count": 52 },
    { "topic_key": "economics", "label": "Economics", "variable_count": 48 },
    { "topic_key": "housing", "label": "Housing", "variable_count": 85 },
    { "topic_key": "transport", "label": "Transportation", "variable_count": 26 },
    { "topic_key": "equity", "label": "Equity & Vulnerability", "variable_count": 19 },
    { "topic_key": "health", "label": "Health", "variable_count": 14 },
    { "topic_key": "environment", "label": "Environment", "variable_count": 10 },
    { "topic_key": "social", "label": "Social Characteristics", "variable_count": 40 }
  ]
}

Use the topic_key values to filter the variable catalog: ?topic=core.

Static Codebook

Download the complete variable catalog as a single file for offline reference or integration into your own tools:

Format	URL	Cache
JSON	/v1/codebook.json	24 hours
CSV	/v1/codebook.csv	24 hours

# Download the full catalog as JSON
curl -o codebook.json \
  "https://api.prairiecloud.io/v1/codebook.json"

# Download as CSV
curl -o codebook.csv \
  "https://api.prairiecloud.io/v1/codebook.csv"

These are static files — no API key required, no rate limit cost. They're regenerated when the variable catalog changes and served with a 24-hour cache header.

Get Full Variable Detail

curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/variables/income_median_household"

The detail response includes:

• Full label and description
• Census code (e.g., B19013_001E)
• Topic category
• Vintage availability matrix
• Original Census table reference

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CSV Export

Pro tier and above

CSV export requires a Pro plan or higher.

Add format=csv to any data endpoint to receive the response as a CSV file instead of JSON. Supported on /v1/data, /v1/compare, and /v1/timeseries.

# Export data as CSV
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/data?variables=pop_total&geo=state:48&format=csv"

# Export comparison as CSV
curl -H "X-API-Key: YOUR_KEY" \
  "https://api.prairiecloud.io/v1/compare?variables=pop_total&geo=state:48,state:06&format=csv"

The response has Content-Type: text/csv and includes a Content-Disposition header for download. Key details:

• Row cap: CSV responses are capped at 10,000 rows. If your query produces more rows, the response is truncated and includes an X-CSV-Truncated: true header.
• Formula injection protection: Cell values that start with =, +, -, or @ are prefixed with a single quote to prevent spreadsheet formula injection.
• Free/Pioneer users who request format=csv receive a 403 error with an upgrade URL.

---

Suppressed Values

Some observations are suppressed by the Census Bureau because of small sample sizes or confidentiality protections. When a value is suppressed:

{
  "estimate": null,
  "suppressed": true,
  "null_reason": "Census Bureau suppression: sample size too small"
}

This is not an API error — it reflects the underlying Census data. Suppression is more common at smaller geographic levels (tracts and block groups) than at state or county level.

---

PrairieCloud vs. Census Bureau API

PrairieCloud wraps the same underlying Census data but provides a significantly better developer experience.

Side-by-Side Comparison

Feature	Census Bureau API	PrairieCloud API
Variable names	Cryptic codes: B01001_001E	Human-readable: pop_total
Census code support	Native codes only	Both api_name and Census codes work
Variable stability	Table restructuring across years	api_name is stable across all vintages
Authentication	Free API key (no dashboard)	API key with usage dashboard and tiered plans
Geography format	Inconsistent: for=state:48, in=state:48	Consistent: geo=state:48 always
Geography depth	Tract and block group available	7 levels: nation → block group
Response format	2D array (headers + rows)	Structured JSON with labeled fields
Margins of error	Separate API call or variable suffix	Included alongside estimates
Rate limiting	Undocumented, inconsistent	Documented tiers with headers (see pricing)
Documentation	PhD-level domain knowledge assumed	Code examples in Python, R, JavaScript, cURL
Multi-vintage queries	One vintage per request	/v1/timeseries spans all vintages
Boundaries	Separate download from TIGER/Line	Integrated /v1/boundaries + include_geometry=true

What PrairieCloud Adds

• Stable variable identifiers — pop_total means the same thing in 2009 and 2024. The Census Bureau reassigns code numbers between releases; PrairieCloud handles the crosswalk so you don't have to.
• Census code aliases — Use familiar Census codes like B01001_001E directly in queries. The API resolves them to the corresponding PrairieCloud variable automatically.
• Time series endpoint — Query a variable across all available vintages in a single request. The Census API requires one call per vintage.
• Unified schema — All variables follow the same request/response pattern regardless of topic. The Census API has different URL structures per dataset.
• Integrated boundaries — GeoJSON boundary shapes for all 7 geography levels, including tract and block group. Add include_geometry=true to get data and shapes in one call.
• Usage tracking — See your API consumption, manage keys, and upgrade plans through the developer dashboard.

What PrairieCloud Doesn't Currently Include

• Non-ACS datasets — BLS, BEA, USDA, and other federal datasets are under evaluation, but are not part of the currently available product surface.
• Custom cross-tabulations — The Census API supports some cross-tabulation queries that PrairieCloud doesn't replicate.
• Full B/C table universe — PrairieCloud serves 53 core table groups (392 variables). The Census Bureau publishes thousands of additional tables with even finer breakdowns. Additional tables may be added based on usage demand.

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Next Steps

• Comparing Geographies — Use /v1/compare to query side-by-side data across multiple places
• Tracking Change Over Time — Use /v1/timeseries to see how variables shift across vintages
• Geographic Boundaries — Download GeoJSON shapes for mapping and spatial analysis
• Core Concepts — The mental model behind datasets, vintages, and variables
• API Reference — Full interactive endpoint documentation