Residential Registry

Test Account

We have a free test account that you may use to access our api.
If you want to use it please send an e-mail to info@valueguard.se

Import the whole registry to MySQL-database

The code below gives an example of how to use the client to fetch the whole registry.

import mysql.connector 
import valueguard

vgClient = valueguard.Client()
vgClient.authenticate("<username>", "<password>")

mydb = mysql.connector.connect(
   host="<db_host>",
   user="<db_username>",
   passwd="<db_password>",
   database="<db_name>"
)

mycursor = mydb.cursor()

limit = 20000
i = 0
while True:
    data = vgClient.residential_registry(offset=i, limit=limit)
    for residence in data['residences']:
        sql = "INSERT INTO `<table_name>` (`id`, `street`, " \
              "`number`, `letter`, `apartment_nr`,`rooms`, `home_type`, `ownership_type`, `deleted`," \
              "`probability_deleted`, `updated_at`, `updated_from`) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, " \
              "%s, %s); "
        val = (residence['id'],
               residence['street'],
               residence['number'],
               residence['letter'],
               residence['apartment_nr'],
               residence['rooms'],
               residence['home_type'],
               residence['ownership_type'],
               residence['deleted'],
               residence['probability_deleted'],
               residence['updated_at'],
               residence['updated_from'])

        mycursor.execute(sql, val)
        mydb.commit()
    fetched_data = data['meta_data']['offset'] + data['meta_data']['response_rows']
    if data['meta_data']['total_nr_records'] <= data['meta_data']['offset'] + data['meta_data']['response_rows']:
        break
    i += data['meta_data']['response_rows']

Search in the registry

Example:

import valueguard

vgClient = valueguard.Client()
vgClient.authenticate("<username>", "<password>")

limit=5

print (vgClient.residential_registry(offset=0, limit=limit, search_criteria={
    "address":"Vangsbyvägen"
}))

print (vgClient.residential_registry(offset=0, limit=limit, search_criteria={
    "address":"Vangsbyvägen 16"
}))

Field list

OBS! You will only be able to fetch the fields that you have access to.

Field name	Type	Example	Description
id	varchar(255)	481515	unique id (serial number) for all residences source: Valueguard
property_key	int(8)	170053749	unique id for all properties source: Fastighetsregistret LMV
address	varchar(60)	1:a villagatan 1, 65341	address of the residence (street, nr, letter, postal code, postal area) source: Fastighetsregistret LMV
street	varchar(60)	1:a villagatan	street name in address
number	list	[1,3,None]	number of the street in address
letter	char(5)	A	letter of the street in address
entrance	varchar(5)	U1	entance of the address, empty string (i.e. "") if not specified
is_meter_address	tinyint(1)	1	1 = the address is a meter address (i.e. the number of the address is of type "302-12") 0 = the address is not a meter address
postal_code	varchar(7)	65341	postal code
postal_area	varchar(40)	Karlstad	postal area
house_nr	mediumint(5)	1	unique number on every house belonging to the same property
apartment_nr	smallint(4)	1101	unique number on every apartment at the same address
living_space	double	137	area of residence in sqm source: Lägenhetsregistret washed with Fastighetsregistret LMV
apartment_area	smallint(4)	137	area of residence in sqm (all home types) source: Lägenhetsregistret LMV
rooms	double	5	number of rooms for areas above 7sqm, excluding kitchen and bathroom (not available for houses)
floor	double	2	the floor of the residence
floors	double	2	the highest floor on the address
apartment_category	tinyint(2)	1	1 = ordinary apartment 2 = special apartment customized for elderly or disabled 3 = student residence 4 = other special residence 9 = missing
kitchen_type	tinyint(2)	1	1 = kitchen 2 = kitchenette 3 = kitchen cabinet 4 = no kitchen equipment 9 = unknown
building_purpose	tinyint(2)	1	1 = home 2 = industry 3 = society 4 = organization 5 = business building 6 = complement buildning 7 = other buildning
sweref99x	int(7)	6583373	X-coordinate (latitude) from SWEREF. a Swedish positioning system by LMV used from 2007 (note: according to usual standard for sweref-coordinates, the X-coordinate should denote longitude but we have chosen to use the previous standard from the rt90 system in which the x-coordinate denotes latitude)
sweref99y	int(7)	413689	Y-coordinate (longitude) from SWEREF. a Swedish positioning system by LMV used from 2007 (note: see the note for sweref99x)
rt90x	double	6586700	X-coordinate (latitude) from RT90. a Swedish positioning system by LMV used before 2007
rt90y	double	1367905	Y-coordinate (longitude) from RT90. a Swedish positioning system by LMV used before 2007
wgs84lat	double	59.3801951334688	Y-coordinate (latitude) from WGS84. a global positioning system
wgs84lon	double	13.4808053113366	X-coordinate (longitude) from WGS84. a global positioning system
construction_year	smallint(4)	1920	building year The construction_year = 1909 for houses and 1929 for flats/apartments are in some cases used by Lantmäteriet when the true year of construction is unknown. For more info see detailed explanation
owner_id	char(11)	769613-3375	organizational number, for example of a housing cooperative
building_type	tinyint(2)	33	-1 = missing 1 = bathhouse 2 = fire station 3 = bus station 4 = distribution building 5 = veterinary 6 = army 7 = health care center 8 = university 9 = ice rink 10 = railway station 11 = municipality building 12 = correctional institution 13 = cultural building 14 = police station 15 = treatment plant 16 = riding area 17 = community 18 = hospital 19 = school 20 = sports area 21 = university 22 = water treatment plant 24 = multi arena 30 = detached house 31 = terraced house 32 = townhouse 33 = block of apartments 35 = house with several apartments 40 = other production industry 41 = gas turbine facility 42 = hotel for industries 43 = chemical industry 44 = condensing plant 45 = nuclear plant 46 = food industry 47 = metal- or machine industry 48 = textile industry 49 = wood industry 50 = hydroelectric plant 51 = windmills 52 = heating plant 53 = other industry building 99 = unspecified
type_code	smallint(3)	320	113 = farm unit (building value < 50000 SEK) 120 = farm unit (built-up) 213 = house (building value < 50000 SEK) 220 = house (built-up) 221* = house (cottege) 222* = house (3 or more residence buildnings) 320 = rental (residences) 321 = rental (residences & local places) 325 = rental (local places) 823 = special unit. * = type code ended in 2015 but is in the register. These are the codes for number of residences of 10000 or more. Complete list can be found at the Swedish Tax Agency.
home_type	varchar(20)	lägenhet	the different types of residence are divided into: radhus (townhouse) lägenhet (apartment) kedjehus (terraced house) villa (house) lantbruk (farm) småhus övriga (other houses) lantbruk övriga (other farms) okänd (unknown)
ownership_type	varchar(30)	bostadsrätt	the different types of ownership are divided into: äganderätt (property rights) bostadsrätt (co-operative apartment) hyresrätt (rented apartment) tomträtt (site leasehold) okänd (unknown), vast majority rentals
living_area	smallint(5)	130	area of residence in sqm source: Fastighetsregistret LMV
ancillary_area	smallint(5)	40	ancillary area in sqm, not part of the primary building area
standard_points	tinyint(2)	32	a number between 0-59 based on assessed value measuring the condition of the residence, higher number represents better condition (not available for co-operative apartments)
plot_area	int(9)	896	area of the plot belonging to the residence in sqm
error_code	tinyint(1)	0	1 = suspected error in data 0 = no suspected error in data Variable explanation
deleted	tinyint(1)	0	0 = not deleted 1 = deleted 2 = maybe deleted OBS! This registry only contains objects with deleted 0 or 2. For deleted objects, see markups Variable explanation
probability_deleted	decimal(3,2)	0.00	sometimes we know 3/4 out of a group of homes are deleted, but we do not know which 3. Then all get 0.75 here
area_id	int(9)	7850	id for area_name
area_name	varchar(60)	Karlstad_Romstad/Strand	Valueguard's own neighbourhood definitions
updated_at	varchar(10)	2016-06-19	latest date of update from the sources. ads: ad date commercial_site: update date with bank-id private_user: date for register in system public_data: date for delivery from LM sales: contract date
updated_from	varchar(60)	public_data	designates the source of an update OBS! Only public_data in this registry! For other sources, see markups.
county_code	varchar(2)	05	County code
municipality_code	varchar(2)	13	Municipality code
parish_code	varchar(2)	02	Parish code
vacation_like_home	tinyiny(1)	1	1 = Estimated to be a vacation home 0 = Estimated to not be a vacation home
person_registered	tinyiny(1)	0	1 = Someone is registered at the address 0 = No one is registered at the address, or we have not been able to match the address.
person_registered_date	varchar(10)	2016-06-19	Update date for person_registered. Objects that never have had someone registered will have the date of our first information of person_registerd(2020-11-16)
first_person_registered_date	varchar(10)	2019-03-12	The date when the first person currently living there was registered

Search Criteria fields

OBS! Searching for parameters that you do not have access to will be ignored in the API!

Field name	Description	Example
id	The id of the object	481515
address	address with postal code NOTE this is treated as a "like", so 'Torgatan' will return both Torgatan and Storgatan	1:a villagatan 1, 65341
apartment_area_max	Maximum apartment area	200
apartment_area_min	Minimum apartment area	80
apartment_category	Category of apartment	4
apartment_nr	Appartment number	901
area_id	Area’s id	5920
building_purpose	Building purpose	1
construction_year_max	Maximum construction year	2000
construction_year_min	Minimum construction year	1960
floor_max	Maximum floor	3
floor_min	Minimum floor	2
floors_max	Maximum number of floors	8
floors_min	Minimum number of floors	6
kitchen_type	Kitchen type	3
living_space_max	Maximum living space	210
living_space_min	Minimum living space	85
owner_id	Owner’s id	782600-0312
postal_area	Postal area	Borlänge
postal_code	Postal code	78436
rooms_max	Maximum number of rooms	5
rooms_min	Minimum number of rooms	2
updated_at_min	Minimum update date	2016-08-10
street	Street name	villagatan
letter	House's address letter	A
number	House's address number	34
entrance	Entrance to the residence	U1
is_meter_address	1 = the address is a meter address (i.e. the number of the address is of type "302-12") 0 = the address is not a meter address	1
property_key	Property's unique id	170053749
ownership_type	Type of ownership	bostadsrätt
building_type	Type of building	21
county_code	County code	05
municipality_code	Municipality code	13
parish_code	Type of building	02
residence_per_building	How many residences in the building	1
residence_per_building_min	Minimum amount of residences in the building	1
residence_per_building_max	Maximum amount of residences in the building	10

Special search criteria fields

Requires special access.

Field name	Description	Example
SSN	Send in social security number and get the home where he/she is registered	202005302399
sensitive_data	Signals that a home might be sensitive, for GDPR reasons 0 = Exclude sensitive data, and get only non-sensitive data 1 = Get only sensitive data For all data, just skip this parameter	0

Raw request

GET

curl https://api.valueguard.se/v1/residential/registry?access_token={ACCESS_TOKEN}&offset={OFFSET}&limit={LIMIT}&{SEARCH_CRITERA AS VALUE-KEY PAIR &address="Vangsbyvägen"...}

Normal use case in Jupyter notebook

• Residential_registry (Full download)