Government
20 columns
201 rows
8 formats

Family Households

This dataset provides detailed demographic, socioeconomic, and geographic information for family households, including family composition, income levels, housing characteristics, and access to resources. It is ideal for social research, policy analysis, and community planning, enabling in-depth studies of household structure and living conditions across regions.

last updated 29 Oct 2025
by GoMask

The brief that made it

Social research and demographic studies

Sample rows

preview · 8 of 201 rows · all 20 columns

household_idstring	income_bracketstring	head_of_household_ageinteger	has_access_internetboolean	address_countrystring	address_streetstring	address_citystring	address_statestring	address_postal_codestring	num_family_membersinteger	num_childreninteger	num_adultsinteger	household_incomefloat	housing_typestring	ownership_statusstring	year_builtinteger	has_access_vehicleboolean	primary_languagestring	head_of_household_genderstring	last_updateddatetime
A82H3LQJ	middle	36	true	Canada	152 Maple Crescent	Toronto	ON	M4V 2X9	3	1	2	94000.5	apartment	mortgaged	2005	true	English	female	2024-06-04T11:32:15
L5K7T8PW	middle	29	true	France	87 Rue de Lyon	Paris	Île-de-France	75012	2	0	2	58000	apartment	rented	1912	false	French	male	2024-06-06T09:21:45
B3HS9KLM	low	33	false	UK	25 Windmill Close	Manchester	Greater Manchester	M21 7GH	5	3	2	42000	townhouse	subsidized	1978	false	English	female	2024-06-02T14:05:22
E7JQ3VZT	upper-middle	54	true	USA	3405 Oak Ridge Dr	Austin	TX	78744	4	2	2	150000	detached	owned	2016	true	English	male	2024-06-12T08:45:11
M8P2X5QW	low	41	false	Brazil	10 Rua do Sol	Rio de Janeiro	RJ	22041-010	6	4	2	35000	other	subsidized	1952	false	Portuguese	male	2024-06-10T13:27:35
N6T1Q7VX	middle	28	true	Germany	19 Friedrichstrasse	Berlin	Berlin	10117	2	0	2	79000	apartment	rented	1984	false	German	female	2024-06-09T10:19:53
X9Q4F2DS	high	39	true	USA	204 Main Street	Boston	MA	02118	1	0	1	320000	condo	owned	2020	true	English	non-binary	2024-06-07T16:04:28
H5Z1K8LM	upper-middle	42	true	Australia	87 Greville Street	Melbourne	VIC	3000	4	1	3	112000	townhouse	mortgaged	2010	true	English	female	2024-06-15T19:32:46
D9S2J7ZT	middle	31	true	Italy	23 Via Roma	Rome	Lazio	00185	2	0	2	54000	apartment	rented	1929	false	Italian	male	2024-06-20T12:54:09
F2L6M8PX	low	29	false	South Africa	5 Nelson Mandela Ave	Cape Town	Western Cape	8001	7	5	2	21000	other	subsidized	1946	false	Xhosa	male	2024-06-03T08:11:36
J8Q3T6VZ	high	44	true	UK	129 Abbey Road	London	Greater London	NW8 9AY	1	0	1	290000	apartment	owned	2001	false	English	male	2024-06-13T15:41:27
P7K4F2SD	low	38	false	Malaysia	88 Jalan Bukit	Kuala Lumpur	Wilayah Persekutuan	50450	5	3	2	41000	semi-detached	rented	1995	false	Malay	female	2024-06-12T17:14:55
Q2W8E5RT	upper-middle	47	true	Australia	42 Market Lane	Sydney	NSW	2000	2	0	2	115400	condo	mortgaged	2018	true	English	female	2024-06-05T21:04:13
T9S6D4WQ	middle	32	true	France	31 Rue du Jardin	Lyon	Auvergne-Rhône-Alpes	69003	3	1	2	70000	apartment	rented	1950	false	French	female	2024-06-17T07:52:49
U3E5F9RN	upper-middle	41	true	Canada	9 King Street West	Hamilton	ON	L8P 1A4	4	2	2	103700	semi-detached	mortgaged	2013	true	English	male	2024-06-09T06:48:21
V5G8K2LP	upper-middle	57	true	USA	1725 Cherry Avenue	San Jose	CA	95128	3	1	2	156000	detached	owned	2008	true	English	female	2024-06-21T13:19:58
Y4R3K7WS	upper-middle	53	true	France	8 Rue des Roses	Marseille	Provence-Alpes-Côte d'Azur	13008	1	0	1	98000	condo	owned	2015	true	French	prefer not to say	2024-06-18T18:47:32
Z2N6J1MR	middle	35	true	Brazil	67 Avenida Paulista	São Paulo	SP	01311-000	5	3	2	54000	apartment	rented	1989	false	Portuguese	female	2024-06-03T07:59:57
C8V2M6LK	middle	30	true	UK	22 Queen Street	Edinburgh	Scotland	EH2 1JX	2	0	2	64000	apartment	rented	1865	false	English	male	2024-06-14T17:59:04
S4Q9W7VP	middle	38	true	Belgium	8 Avenue du Midi	Brussels	Brussels-Capital	1060	3	1	2	72000	apartment	rented	1932	false	French	female	2024-06-05T13:32:29

What the 201 rows show

from the 201-row sample

High (income bracket) stands out: mean head_of_household_age is 54.9, against 35.3 for the rest.

76%has_access_internet = true
36median head_of_household_age
4ownership statuses
4head of household genders
6housing types
18primary languages

Mean head_of_household_age by income_bracket201 rows

head_of_household_age201 rows, in bands of 10

Median 36, from 21 to 81.

address_country201 rows · top 10 of 23 values

France38
UK35
USA20
Canada18
Australia13
South Africa13
Italy11
New Zealand9
Brazil7
Germany6

20 columns by typefrom the column list below

string 11
integer 5
float 1
datetime 1
boolean 2

Columns

20 columns in four groups

blueprint · 20 columns
column	type	description	example
Text 11 columns
`household_id`	string	Unique identifier for each household recordunique	A82H3LQJ
`address_street`	string	Street address of the household	152 Maple Crescent
`address_city`	string	City where the household is located	Toronto
`address_state`	string	State or region of the household	ON
`address_postal_code`	string	Postal code for the household address	M4V 2X9
`address_country`	string	Country where the household is located	Canada
`income_bracket`	string	Categorical income bracket for the householdlow · middle · upper-middle · high	middle
`housing_type`	string	Type of housing occupied by the household6 values	apartment
`ownership_status`	string	Ownership status of the household's residenceowned · rented · mortgaged · subsidized · other	mortgaged
`primary_language`	string	Primary language spoken in the household	English
`head_of_household_gender`	string	Gender of the head of householdmale · female · non-binary · prefer not to say	female
Numbers 6 columns
`num_family_members`	integer	Total number of family members in the household1 or more	3
`num_children`	integer	Number of children (under 18) in the household0 or more	1
`num_adults`	integer	Number of adults (18 and over) in the household1 or more	2
`household_income`	float	Total annual household income in local currency0 or more	94000.5
`year_built`	integer	Year the residence was built1,800 to 2,024 · optional	2005
`head_of_household_age`	integer	Age of the head of household18 to 120	36
Dates and times 1 column
`last_updated`	datetime	Timestamp of the last update to this household record	2024-06-04T11:32:15
True or false 2 columns
`has_access_internet`	boolean	Indicates if the household has internet access	true
`has_access_vehicle`	boolean	Indicates if the household has access to a vehicle	true

Use it for

A government dashboard
The has_access_internet rate, head_of_household_age by income_bracket and a breakdown of address_country. Excel, Power BI or Tableau.
Why do the 20 high rows have a mean head_of_household_age of 54.9?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Households201
A82H3LQJ36middle
L5K7T8PW29middle
B3HS9KLM33low
A software demo
Believable households with address_street, address_city and address_state to fill a screen in front of a buyer.

This dataset201 rows20 columns

Yours1,000 rows20 columnsaddress_street: UK only

blueprint · family-households

Behind this dataset

Same schema. As many rows as you need.

These 201 rows came out of a blueprint — 20 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Household ID groups family members
Head of household designated
Combined household income from all members
Number of dependents affects tax calculations
Housing type correlates with income level

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: family-households

What should your data show?

No signup. No card.

Sample rows

What the 201 rows show

Columns

Use it for

A government dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Government

What should your data show?