Compare Markets

curl --request POST \
  --url https://data.apartmentiq.io/apartmentiq/api/v1/explore_markets \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "account_id": 9919347,
  "filters": {
    "geo_boundary_id": [
      "94121",
      "94012"
    ],
    "geo_type": "MSA"
  },
  "property_filters": {
    "year_built_gte": 2015,
    "total_units_gte": 200
  },
  "sort_by": "population_total",
  "sort_order": "desc",
  "limit": 50
}
'

{
  "data": [
    {
      "id": "94012",
      "type": "compare_market",
      "attributes": {
        "id": 94012,
        "name": "Los Angeles-Long Beach-Anaheim, CA Metro Area",
        "short_name": "Los Angeles-Long Beach-Anaheim, CA Metro Area",
        "description": "Los Angeles-Long Beach-Anaheim, CA",
        "geo_type": "MSA",
        "geo_states": [
          "CA"
        ],
        "place_type": "<string>",
        "centroid": [
          34.1087033,
          -118.1827533
        ],
        "property_count_total": 392,
        "rent_avg_t30": 3261.04,
        "rent_0_bed_avg_t30": 2514.37,
        "rent_1_bed_avg_t30": 2937.87,
        "rent_2_bed_avg_t30": 3891.46,
        "rent_3_bed_avg_t30": 5318.09,
        "ner_avg_t30": 3038.13,
        "ner_0_bed_avg_t30": 2330.1,
        "ner_1_bed_avg_t30": 2738.23,
        "ner_2_bed_avg_t30": 3623.31,
        "ner_3_bed_avg_t30": 4891.74,
        "rent_psf_avg_t30": 3.85,
        "rent_0_bed_psf_avg_t30": 4.48,
        "rent_1_bed_psf_avg_t30": 3.95,
        "rent_2_bed_psf_avg_t30": 3.51,
        "rent_3_bed_psf_avg_t30": 3.54,
        "ner_psf_avg_t30": 3.59,
        "ner_0_bed_psf_avg_t30": 4.14,
        "ner_1_bed_psf_avg_t30": 3.68,
        "ner_2_bed_psf_avg_t30": 3.28,
        "ner_3_bed_psf_avg_t30": 3.26,
        "ner_psf_p88_t30": 4.31,
        "ner_psf_p68_t30": 3.76,
        "ner_psf_p18_t30": 3.02,
        "rent_growth_rate_yoy_avg": -0.0073,
        "ner_growth_rate_yoy_avg": -0.0101,
        "forecasted_rent_growth_rate_yoy": 0.0257,
        "rent_growth_rate_yoy_by_quarter_avg": -0.0064,
        "ner_growth_rate_yoy_by_quarter_avg": -0.0061,
        "rent_growth_rate_t90_avg": -0.0185,
        "ner_growth_rate_t90_avg": -0.0277,
        "concession_value_avg_t30": 4175.48,
        "concession_percent_avg_t30": 0.1036,
        "exposure_percent_avg_t30": 0.0749,
        "leased_percent_avg_t30": 0.9325,
        "advertised_occupancy_percent_avg_t30": 0.9274,
        "days_on_market_avg_t30": 50.64,
        "total_unit_count": 142374,
        "existing_unit_count_total": 125696,
        "new_supply_unit_count_total": 16678,
        "under_construction_unit_count_total": 7308,
        "planned_unit_count_total": 2403,
        "delivered_unit_count_total_mtd": 0,
        "delivered_unit_count_total_t365": 8777,
        "available_unit_count_new_to_market_total_mtd": 3066,
        "leased_unit_count_total_mtd": 2707,
        "available_unit_count_total_t30": 14176,
        "leased_unit_count_total_t30": 3308,
        "absorption_rate_avg_t30": 123,
        "unit_sq_ft_avg": 879,
        "amenity_count_p50": 30,
        "year_built_p50": 2021,
        "year_renovated_p50": 2020,
        "building_square_feet_avg": 123,
        "rentable_building_area_sq_ft_avg": 333893,
        "rentable_building_area_sq_ft_per_floor_avg": 55864,
        "land_area_sq_ft_avg": 213385,
        "land_area_acres_avg": 4.9,
        "units_per_acre_avg": 157.78,
        "units_per_building_avg": 291.74,
        "units_per_floor_avg": 66.5,
        "number_of_stories_avg": 8.71,
        "building_count_avg": 1.77,
        "walk_score_avg": 74,
        "transit_score_avg": 61,
        "bike_score_avg": 64,
        "population_growth_last_5_years_total": -0.0353,
        "population_growth_last_5_years_20_29": -0.1159,
        "population_growth_last_5_years_30_39": -0.0074,
        "population_growth_last_5_years_40_54": -0.0319,
        "population_growth_last_5_years_55_up": 0.039,
        "population_total": 12866598,
        "population_20_29": 1741263,
        "population_30_39": 1950682,
        "population_40_54": 2553323,
        "population_55_up": 3689869,
        "median_income": 94295,
        "median_income_growth_yoy": -0.0125,
        "employed_labor_force_percent": 0.9392,
        "employed_labor_force_growth_rate_yoy": 0.006,
        "sold_property_count_total_t365": 12,
        "sold_unit_count_total_t365": 4101,
        "sold_unit_count_avg_t365": 341,
        "sale_price_avg_t365": 135230561.33,
        "sale_price_total_t365": 1622766736,
        "sale_price_avg_t365_per_unit": 396925.04,
        "sale_cap_rate_avg_t365": 0.0476,
        "sale_price_per_unit_growth_yoy": -0.0141,
        "cap_rate_avg": 123,
        "asset_value_total": 45284183238,
        "asset_value_per_unit_avg": 123
      }
    }
  ]
}

POST

explore_markets

curl --request POST \
  --url https://data.apartmentiq.io/apartmentiq/api/v1/explore_markets \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "account_id": 9919347,
  "filters": {
    "geo_boundary_id": [
      "94121",
      "94012"
    ],
    "geo_type": "MSA"
  },
  "property_filters": {
    "year_built_gte": 2015,
    "total_units_gte": 200
  },
  "sort_by": "population_total",
  "sort_order": "desc",
  "limit": 50
}
'

{
  "data": [
    {
      "id": "94012",
      "type": "compare_market",
      "attributes": {
        "id": 94012,
        "name": "Los Angeles-Long Beach-Anaheim, CA Metro Area",
        "short_name": "Los Angeles-Long Beach-Anaheim, CA Metro Area",
        "description": "Los Angeles-Long Beach-Anaheim, CA",
        "geo_type": "MSA",
        "geo_states": [
          "CA"
        ],
        "place_type": "<string>",
        "centroid": [
          34.1087033,
          -118.1827533
        ],
        "property_count_total": 392,
        "rent_avg_t30": 3261.04,
        "rent_0_bed_avg_t30": 2514.37,
        "rent_1_bed_avg_t30": 2937.87,
        "rent_2_bed_avg_t30": 3891.46,
        "rent_3_bed_avg_t30": 5318.09,
        "ner_avg_t30": 3038.13,
        "ner_0_bed_avg_t30": 2330.1,
        "ner_1_bed_avg_t30": 2738.23,
        "ner_2_bed_avg_t30": 3623.31,
        "ner_3_bed_avg_t30": 4891.74,
        "rent_psf_avg_t30": 3.85,
        "rent_0_bed_psf_avg_t30": 4.48,
        "rent_1_bed_psf_avg_t30": 3.95,
        "rent_2_bed_psf_avg_t30": 3.51,
        "rent_3_bed_psf_avg_t30": 3.54,
        "ner_psf_avg_t30": 3.59,
        "ner_0_bed_psf_avg_t30": 4.14,
        "ner_1_bed_psf_avg_t30": 3.68,
        "ner_2_bed_psf_avg_t30": 3.28,
        "ner_3_bed_psf_avg_t30": 3.26,
        "ner_psf_p88_t30": 4.31,
        "ner_psf_p68_t30": 3.76,
        "ner_psf_p18_t30": 3.02,
        "rent_growth_rate_yoy_avg": -0.0073,
        "ner_growth_rate_yoy_avg": -0.0101,
        "forecasted_rent_growth_rate_yoy": 0.0257,
        "rent_growth_rate_yoy_by_quarter_avg": -0.0064,
        "ner_growth_rate_yoy_by_quarter_avg": -0.0061,
        "rent_growth_rate_t90_avg": -0.0185,
        "ner_growth_rate_t90_avg": -0.0277,
        "concession_value_avg_t30": 4175.48,
        "concession_percent_avg_t30": 0.1036,
        "exposure_percent_avg_t30": 0.0749,
        "leased_percent_avg_t30": 0.9325,
        "advertised_occupancy_percent_avg_t30": 0.9274,
        "days_on_market_avg_t30": 50.64,
        "total_unit_count": 142374,
        "existing_unit_count_total": 125696,
        "new_supply_unit_count_total": 16678,
        "under_construction_unit_count_total": 7308,
        "planned_unit_count_total": 2403,
        "delivered_unit_count_total_mtd": 0,
        "delivered_unit_count_total_t365": 8777,
        "available_unit_count_new_to_market_total_mtd": 3066,
        "leased_unit_count_total_mtd": 2707,
        "available_unit_count_total_t30": 14176,
        "leased_unit_count_total_t30": 3308,
        "absorption_rate_avg_t30": 123,
        "unit_sq_ft_avg": 879,
        "amenity_count_p50": 30,
        "year_built_p50": 2021,
        "year_renovated_p50": 2020,
        "building_square_feet_avg": 123,
        "rentable_building_area_sq_ft_avg": 333893,
        "rentable_building_area_sq_ft_per_floor_avg": 55864,
        "land_area_sq_ft_avg": 213385,
        "land_area_acres_avg": 4.9,
        "units_per_acre_avg": 157.78,
        "units_per_building_avg": 291.74,
        "units_per_floor_avg": 66.5,
        "number_of_stories_avg": 8.71,
        "building_count_avg": 1.77,
        "walk_score_avg": 74,
        "transit_score_avg": 61,
        "bike_score_avg": 64,
        "population_growth_last_5_years_total": -0.0353,
        "population_growth_last_5_years_20_29": -0.1159,
        "population_growth_last_5_years_30_39": -0.0074,
        "population_growth_last_5_years_40_54": -0.0319,
        "population_growth_last_5_years_55_up": 0.039,
        "population_total": 12866598,
        "population_20_29": 1741263,
        "population_30_39": 1950682,
        "population_40_54": 2553323,
        "population_55_up": 3689869,
        "median_income": 94295,
        "median_income_growth_yoy": -0.0125,
        "employed_labor_force_percent": 0.9392,
        "employed_labor_force_growth_rate_yoy": 0.006,
        "sold_property_count_total_t365": 12,
        "sold_unit_count_total_t365": 4101,
        "sold_unit_count_avg_t365": 341,
        "sale_price_avg_t365": 135230561.33,
        "sale_price_total_t365": 1622766736,
        "sale_price_avg_t365_per_unit": 396925.04,
        "sale_cap_rate_avg_t365": 0.0476,
        "sale_price_per_unit_growth_yoy": -0.0141,
        "cap_rate_avg": 123,
        "asset_value_total": 45284183238,
        "asset_value_per_unit_avg": 123
      }
    }
  ]
}

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

account_id

integer

required

The ID of the account you're requesting data for.

Example:

9919347

filters

object

Market-level filters to narrow results by geography or market performance metrics.

Show child attributes

filters.geo_boundary_id

string[]

Array of geo boundary IDs to retrieve market data for. Find these IDs using the Search Geo Boundaries endpoint.

Example:

["94121", "94012"]

filters.geo_type

enum<string>

Filter results by geo boundary type. Use in combination with geo_states to retrieve all markets of a given type.

Available options:

MSA,

BespokeSubmarket

Example:

"MSA"

filters.geo_states

string[]

Filter by US state(s). Use two-letter state abbreviations.

Example:

["CA", "NY"]

filters.rent_avg_t30_gte

number

Minimum 30-day average rent.

Example:

2000

filters.rent_avg_t30_lte

number

Maximum 30-day average rent.

Example:

5000

filters.ner_avg_t30_gte

number

Minimum 30-day average net effective rent.

Example:

1800

filters.ner_avg_t30_lte

number

Maximum 30-day average net effective rent.

Example:

4500

filters.rent_growth_rate_yoy_avg_gte

number

Minimum year-over-year rent growth rate (decimal, e.g., 0.05 for 5%).

Example:

-0.05

filters.rent_growth_rate_yoy_avg_lte

number

Maximum year-over-year rent growth rate (decimal, e.g., 0.10 for 10%).

Example:

0.1

filters.population_total_gte

number

Minimum total population in the market.

Example:

1000000

filters.population_total_lte

number

Maximum total population in the market.

Example:

20000000

filters.property_count_total_gte

number

Minimum number of properties in the market.

Example:

100

filters.property_count_total_lte

number

Maximum number of properties in the market.

Example:

1000

filters.advertised_occupancy_percent_avg_t30_gte

number

Minimum 30-day average advertised occupancy percentage (decimal, e.g., 0.90 for 90%).

Example:

0.85

filters.advertised_occupancy_percent_avg_t30_lte

number

Maximum 30-day average advertised occupancy percentage (decimal, e.g., 0.99 for 99%).

Example:

0.99

property_filters

object

Filters applied to properties before aggregating market metrics. Only properties matching these filters will contribute to the market-level calculations.

Show child attributes

property_filters.year_built_gte

number

Minimum year the property was built.

Example:

2015

property_filters.year_built_lte

number

Maximum year the property was built.

Example:

2024

property_filters.total_units_gte

number

Minimum total number of units in the property.

Example:

200

property_filters.total_units_lte

number

Maximum total number of units in the property.

Example:

1000

property_filters.collected_at_gte

string<date-time>

Only include data collected on or after this date. ISO 8601 format.

Example:

"2025-11-01T00:00:00.000Z"

property_filters.collected_at_lte

string<date-time>

Only include data collected on or before this date. ISO 8601 format.

Example:

"2025-11-25T00:00:00.000Z"

property_filters.number_of_stories_gte

number

Minimum number of stories/floors in the property buildings.

Example:

3

property_filters.number_of_stories_lte

number

Maximum number of stories/floors in the property buildings.

Example:

50

property_filters.property_class

enum<string>[]

Filter by property classification grade.

Available options:

A,

B,

C

Example:

["A", "B"]

property_filters.property_type

enum<string>[]

Filter by property type/category.

Available options:

conventional,

income_restricted,

section8,

senior_living,

student_housing,

build_to_rent

Example:

["conventional"]

property_filters.construction_state

enum<string>[]

Filter by current construction state/status.

Available options:

existing,

new_supply

Example:

["existing"]

sort_by

string

Field to sort results by. Can be any numeric response attribute.

Example:

"population_total"

sort_order

enum<string>

default:desc

Sort direction.

Available options:

asc,

desc

Example:

"desc"

limit

integer

default:50

Maximum number of markets to return.

Required range: 1 <= x <= 100

Example:

50

Response

Successfully retrieved market data. Returns markets in JSON:API format with comprehensive market-level metrics.

data

object[]

required

Array of market data in JSON:API format.

Show child attributes

data.id

string

required

The geo boundary ID as a string

Example:

"94012"

data.type

enum<string>

required

Resource type, always 'compare_market'

Available options:

compare_market

Example:

"compare_market"

data.attributes

object

required

Market attributes including geographic info, performance metrics, inventory, demographics, and sales data

Show child attributes

data.attributes.id

integer

Unique geo boundary identifier

Example:

94012

data.attributes.name

string

Full name of the market

Example:

"Los Angeles-Long Beach-Anaheim, CA Metro Area"

data.attributes.short_name

string

Shortened name of the market

Example:

"Los Angeles-Long Beach-Anaheim, CA Metro Area"

data.attributes.description

string

Description of the market geography

Example:

"Los Angeles-Long Beach-Anaheim, CA"

data.attributes.geo_type

enum<string>

Type of geographic boundary

Available options:

MSA,

BespokeSubmarket

Example:

"MSA"

data.attributes.geo_states

string[]

US states that the market spans

Example:

["CA"]

data.attributes.place_type

string | null

Type of place (if applicable)

data.attributes.centroid

number[]

Geographic center of the market as [latitude, longitude]

Example:

[34.1087033, -118.1827533]

data.attributes.property_count_total

integer

Total number of properties in the market matching filters

Example:

392

data.attributes.rent_avg_t30

number

Average asking rent across all unit types (last 30 days)

Example:

3261.04

data.attributes.rent_0_bed_avg_t30

number

Average asking rent for studio units (last 30 days)

Example:

2514.37

data.attributes.rent_1_bed_avg_t30

number

Average asking rent for 1-bedroom units (last 30 days)

Example:

2937.87

data.attributes.rent_2_bed_avg_t30

number

Average asking rent for 2-bedroom units (last 30 days)

Example:

3891.46

data.attributes.rent_3_bed_avg_t30

number

Average asking rent for 3-bedroom units (last 30 days)

Example:

5318.09

data.attributes.ner_avg_t30

number

Average net effective rent across all unit types (last 30 days)

Example:

3038.13

data.attributes.ner_0_bed_avg_t30

number

Average net effective rent for studio units (last 30 days)

Example:

2330.1

data.attributes.ner_1_bed_avg_t30

number

Average net effective rent for 1-bedroom units (last 30 days)

Example:

2738.23

data.attributes.ner_2_bed_avg_t30

number

Average net effective rent for 2-bedroom units (last 30 days)

Example:

3623.31

data.attributes.ner_3_bed_avg_t30

number

Average net effective rent for 3-bedroom units (last 30 days)

Example:

4891.74

data.attributes.rent_psf_avg_t30

number

Average asking rent per square foot across all unit types (last 30 days)

Example:

3.85

data.attributes.rent_0_bed_psf_avg_t30

number

Average asking rent per square foot for studio units (last 30 days)

Example:

4.48

data.attributes.rent_1_bed_psf_avg_t30

number

Average asking rent per square foot for 1-bedroom units (last 30 days)

Example:

3.95

data.attributes.rent_2_bed_psf_avg_t30

number

Average asking rent per square foot for 2-bedroom units (last 30 days)

Example:

3.51

data.attributes.rent_3_bed_psf_avg_t30

number

Average asking rent per square foot for 3-bedroom units (last 30 days)

Example:

3.54

data.attributes.ner_psf_avg_t30

number

Average net effective rent per square foot across all unit types (last 30 days)

Example:

3.59

data.attributes.ner_0_bed_psf_avg_t30

number

Average net effective rent per square foot for studio units (last 30 days)

Example:

4.14

data.attributes.ner_1_bed_psf_avg_t30

number

Average net effective rent per square foot for 1-bedroom units (last 30 days)

Example:

3.68

data.attributes.ner_2_bed_psf_avg_t30

number

Average net effective rent per square foot for 2-bedroom units (last 30 days)

Example:

3.28

data.attributes.ner_3_bed_psf_avg_t30

number

Average net effective rent per square foot for 3-bedroom units (last 30 days)

Example:

3.26

data.attributes.ner_psf_p88_t30

number

88th percentile net effective rent per square foot (last 30 days)

Example:

4.31

data.attributes.ner_psf_p68_t30

number

68th percentile net effective rent per square foot (last 30 days)

Example:

3.76

data.attributes.ner_psf_p18_t30

number

18th percentile net effective rent per square foot (last 30 days)

Example:

3.02

data.attributes.rent_growth_rate_yoy_avg

number

Average year-over-year rent growth rate (decimal)

Example:

-0.0073

data.attributes.ner_growth_rate_yoy_avg

number

Average year-over-year net effective rent growth rate (decimal)

Example:

-0.0101

data.attributes.forecasted_rent_growth_rate_yoy

number

Forecasted year-over-year rent growth rate (decimal)

Example:

0.0257

data.attributes.rent_growth_rate_yoy_by_quarter_avg

number

Average year-over-year rent growth rate by quarter (decimal)

Example:

-0.0064

data.attributes.ner_growth_rate_yoy_by_quarter_avg

number

Average year-over-year net effective rent growth rate by quarter (decimal)

Example:

-0.0061

data.attributes.rent_growth_rate_t90_avg

number

Average rent growth rate over the last 90 days (decimal)

Example:

-0.0185

data.attributes.ner_growth_rate_t90_avg

number

Average net effective rent growth rate over the last 90 days (decimal)

Example:

-0.0277

data.attributes.concession_value_avg_t30

number

Average concession value in dollars (last 30 days)

Example:

4175.48

data.attributes.concession_percent_avg_t30

number

Average concession as percentage of rent (last 30 days, decimal)

Example:

0.1036

data.attributes.exposure_percent_avg_t30

number

Average exposure percentage - units available for lease (last 30 days, decimal)

Example:

0.0749

data.attributes.leased_percent_avg_t30

number

Average percentage of units leased (last 30 days, decimal)

Example:

0.9325

data.attributes.advertised_occupancy_percent_avg_t30

number

Average advertised occupancy percentage (last 30 days, decimal)

Example:

0.9274

data.attributes.days_on_market_avg_t30

number

Average days on market (last 30 days)

Example:

50.64

data.attributes.total_unit_count

integer

Total number of units across all properties in the market

Example:

142374

data.attributes.existing_unit_count_total

integer

Total units in existing (non-new supply) properties

Example:

125696

data.attributes.new_supply_unit_count_total

integer

Total units in new supply properties

Example:

16678

data.attributes.under_construction_unit_count_total

integer

Total units currently under construction

Example:

7308

data.attributes.planned_unit_count_total

integer

Total units in planned developments

Example:

2403

data.attributes.delivered_unit_count_total_mtd

integer

Units delivered month-to-date

Example:

0

data.attributes.delivered_unit_count_total_t365

integer

Units delivered in the last 365 days

Example:

8777

data.attributes.available_unit_count_new_to_market_total_mtd

integer

New-to-market available units month-to-date

Example:

3066

data.attributes.leased_unit_count_total_mtd

integer

Units leased month-to-date

Example:

2707

data.attributes.available_unit_count_total_t30

integer

Total available units (last 30 days)

Example:

14176

data.attributes.leased_unit_count_total_t30

integer

Total units leased (last 30 days)

Example:

3308

data.attributes.absorption_rate_avg_t30

number | null

Average absorption rate (last 30 days)

data.attributes.unit_sq_ft_avg

integer

Average unit square footage

Example:

879

data.attributes.amenity_count_p50

integer

Median amenity count across properties

Example:

30

data.attributes.year_built_p50

integer

Median year built across properties

Example:

2021

data.attributes.year_renovated_p50

integer

Median year renovated across properties

Example:

2020

data.attributes.building_square_feet_avg

number | null

Average building square footage

data.attributes.rentable_building_area_sq_ft_avg

number

Average rentable building area in square feet

Example:

333893

data.attributes.rentable_building_area_sq_ft_per_floor_avg

number

Average rentable area per floor in square feet

Example:

55864

data.attributes.land_area_sq_ft_avg

number

Average land area in square feet

Example:

213385

data.attributes.land_area_acres_avg

number

Average land area in acres

Example:

4.9

data.attributes.units_per_acre_avg

number

Average units per acre

Example:

157.78

data.attributes.units_per_building_avg

number

Average units per building

Example:

291.74

data.attributes.units_per_floor_avg

number

Average units per floor

Example:

66.5

data.attributes.number_of_stories_avg

number

Average number of stories

Example:

8.71

data.attributes.building_count_avg

number

Average number of buildings per property

Example:

1.77

data.attributes.walk_score_avg

integer

Average Walk Score across properties

Example:

74

data.attributes.transit_score_avg

integer

Average Transit Score across properties

Example:

61

data.attributes.bike_score_avg

integer

Average Bike Score across properties

Example:

64

data.attributes.population_growth_last_5_years_total

number

Total population growth rate over the last 5 years (decimal)

Example:

-0.0353

data.attributes.population_growth_last_5_years_20_29

number

Population growth rate for ages 20-29 over the last 5 years (decimal)

Example:

-0.1159

data.attributes.population_growth_last_5_years_30_39

number

Population growth rate for ages 30-39 over the last 5 years (decimal)

Example:

-0.0074

data.attributes.population_growth_last_5_years_40_54

number

Population growth rate for ages 40-54 over the last 5 years (decimal)

Example:

-0.0319

data.attributes.population_growth_last_5_years_55_up

number

Population growth rate for ages 55+ over the last 5 years (decimal)

Example:

0.039

data.attributes.population_total

integer

Total population in the market

Example:

12866598

data.attributes.population_20_29

integer

Population aged 20-29

Example:

1741263

data.attributes.population_30_39

integer

Population aged 30-39

Example:

1950682

data.attributes.population_40_54

integer

Population aged 40-54

Example:

2553323

data.attributes.population_55_up

integer

Population aged 55 and older

Example:

3689869

data.attributes.median_income

integer

Median household income in dollars

Example:

94295

data.attributes.median_income_growth_yoy

number

Year-over-year median income growth rate (decimal)

Example:

-0.0125

data.attributes.employed_labor_force_percent

number

Percentage of labor force that is employed (decimal)

Example:

0.9392

data.attributes.employed_labor_force_growth_rate_yoy

number

Year-over-year employment growth rate (decimal)

Example:

0.006

data.attributes.sold_property_count_total_t365

integer

Number of properties sold in the last 365 days

Example:

12

data.attributes.sold_unit_count_total_t365

integer

Total units in properties sold in the last 365 days

Example:

4101

data.attributes.sold_unit_count_avg_t365

integer

Average units per property sold in the last 365 days

Example:

341

data.attributes.sale_price_avg_t365

number

Average sale price in the last 365 days

Example:

135230561.33

data.attributes.sale_price_total_t365

number

Total sales volume in the last 365 days

Example:

1622766736

data.attributes.sale_price_avg_t365_per_unit

number

Average sale price per unit in the last 365 days

Example:

396925.04

data.attributes.sale_cap_rate_avg_t365

number

Average cap rate for sales in the last 365 days (decimal)

Example:

0.0476

data.attributes.sale_price_per_unit_growth_yoy

number

Year-over-year sale price per unit growth rate (decimal)

Example:

-0.0141

data.attributes.cap_rate_avg

number | null

Average cap rate

data.attributes.asset_value_total

number

Total estimated asset value in the market

Example:

45284183238

data.attributes.asset_value_per_unit_avg

number | null

Average asset value per unit

Search Properties

⌘I

Overview

Use Cases

API Reference

Authorizations

Body

Response