Mailing Addresses

This dataset provides standardized, validated mailing addresses from around the world, including detailed street, city, state/province, postal code, country, and geolocation information. It supports address validation tracking and is ideal for logistics, e-commerce, and customer management applications requiring accurate and up-to-date postal data.

  • last updated 29 Oct 2025
  • by GoMask
The brief that made it

Shipping and delivery address verification

Sample rows

preview · 8 of 200 rows · all 12 columns
address_idstringis_validatedbooleanvalidation_sourcestringstreet_addressstringaddress_line_2stringcitystringstate_province_regionstringpostal_codestringcountrystringvalidation_datedatelatitudefloatlongitudefloat
B2F8Z1K9QVtrueUSPS4012 Main StApt 7BSpringfieldIL62704US2023-11-0239.7817-89.6501
F8K3T9D2LWtrueCanada Post55 Queen StSuite 210TorontoONM5G 2C3CA2024-01-1843.6532-79.3832
V1J2P8R5SDfalseblank8-14 Shibuya 2-chomeblankShibuyablank150-0002JPblank35.6581139.7017
M9N2W6C3QKfalseblank12 Oxford RdFlat 6ManchesterblankM13 9PLGBblank53.4668-2.2339
R5T7B6G4XMtrueAustralia Post19 George StLevel 3SydneyNSW2000AU2022-08-20-33.8688151.2093
K2L9X4J8SDtrueCorreios17 Avenida PaulistaBloco BSao PauloSP01311-200BR2023-07-12-23.5617-46.6558
P1W8B7Q6XZtrueUSPS305 Park AveSuite 300New YorkNY10022US2024-03-2940.7505-73.9716
D6G3Z8V4MPfalseblank22 Rue de RivoliblankParisblank75001FRblank48.85562.3418

What the 200 rows show

from the 200-row sample
  • 57%is_validated = true
  • 33countries
validation_source114 rows with a value · 86 left blank
  1. USPS30
  2. Canada Post15
  3. Australia Post7
  4. La Poste7
  5. PostNord6
  6. Correios5
  7. Royal Mail5
  8. Correos3
  9. PostNet3
  10. Posti3
12 columns by typefrom the column list below
  • string 8
  • float 2
  • date 1
  • boolean 1

Columns

12 columns in four groups
blueprint · 12 columns
columntypedescriptionexample
Text 8 columns
address_idstringUnique identifier for each mailing address recorduniqueB2F8Z1K9QV
street_addressstringPrimary street address including house/building number and street nameup to 2554012 Main St
address_line_2stringSecondary address information (e.g., apartment, suite, unit, floor)up to 255 · optionalApt 7B
citystringCity or locality for the mailing addressup to 100Springfield
state_province_regionstringState, province, or region for the mailing addressup to 100 · optionalIL
postal_codestringPostal or ZIP code for the mailing addressup to 2062704
countrystringCountry name (ISO 3166-1 alpha-2 or full name)up to 100US
validation_sourcestringSource or service used for address validation (e.g., USPS, Royal Mail, third-party API)up to 100 · optionalUSPS
Numbers 2 columns
latitudefloatLatitude coordinate for geolocation of the address-90 to 90 · optional39.7817
longitudefloatLongitude coordinate for geolocation of the address-180 to 180 · optional-89.6501
Dates and times 1 column
validation_datedateDate when the address was last validatedoptional2023-11-02
True or false 1 column
is_validatedbooleanIndicates if the address has been validated through postal or third-party servicestrue

Use it for

  • is validated57%114 of 200 rows

    A logistics dashboard

    The is_validated rate and a breakdown of validation_source. Excel, Power BI or Tableau.

  • Why do 114 of 200 rows have is_validated = true?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 200 rows.

  • A software demo

    Believable addresses with street_address, address_line_2 and city to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 12 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows12 columns
Yours1,000 rows12 columnsaddress_id: UK only

blueprint · mailing-addresses

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 12 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
  • Postal code format matches country standards
  • State/province valid for given country
  • City and state combination is valid
  • Address type: residential or commercial
  • Delivery instructions for special cases
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
mailing-addresses

What should your data show?

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