A global self-hosted location dataset containing all administrative divisions, cities, and zip codes for 247 countries. All geospatial data is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.
Use cases for the Global Zip Code Database (Geospatial data)
Address capture and validation
Map and visualization
Reporting and Business Intelligence (BI)
Master Data Mangement
Logistics and Supply Chain Management
Sales and Marketing
Data export methodology
Our location data packages are offered in variable formats, including .csv. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Product Features
Fully and accurately geocoded
Administrative areas with a level range of 0-4
Multi-language support including address names in local and foreign languages
Comprehensive city definitions across countries
For additional insights, you can combine the map data with:
UNLOCODE and IATA codes
Time zones and Daylight Saving Times
Why do companies choose our location databases
Enterprise-grade service
Reduce integration time and cost by 30%
Weekly updates for the highest quality
Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.
This annual study provides selected income and tax items classified by State, ZIP Code, and the size of adjusted gross income. These data include the number of returns, which approximates the number of households; the number of personal exemptions, which approximates the population; adjusted gross income; wages and salaries; dividends before exclusion; and interest received. Data are based who reported on U.S. Individual Income Tax Returns (Forms 1040) filed with the IRS. SOI collects these data as part of its Individual Income Tax Return (Form 1040) Statistics program, Data by Geographic Areas, ZIP Code Data.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
Our location data powers the most advanced address validation solutions for enterprise backend and frontend systems.
A global, standardized, self-hosted location dataset containing all administrative divisions, cities, and zip codes for 247 countries.
All geospatial data for address data validation is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.
Use cases for the Address Validation at Zip Code Level Database (Geospatial data)
Address capture and address validation
Address autocomplete
Address verification
Reporting and Business Intelligence (BI)
Master Data Mangement
Logistics and Supply Chain Management
Sales and Marketing
Product Features
Dedicated features to deliver best-in-class user experience
Multi-language support including address names in local and foreign languages
Comprehensive city definitions across countries
Data export methodology
Our location data packages are offered in variable formats, including .csv. All geospatial data for address validation are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Why do companies choose our location databases
Enterprise-grade service
Full control over security, speed, and latency
Reduce integration time and cost by 30%
Weekly updates for the highest quality
Seamlessly integrated into your software
Note: Custom address validation packages are available. Please submit a request via the above contact button for more details.
https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
This dataset is part of the Geographical repository maintained by Opendatasoft.This dataset contains data for zip codes 5 digits in United States of America.ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery.Processors and tools are using this data.EnhancementsAdd ISO 3166-3 codes.Simplify geometries to provide better performance across the services.Add administrative hierarchy.
A crosswalk dataset matching US ZIP codes to corresponding county codes
The denominators used to calculate the address ratios are the ZIP code totals. When a ZIP is split by any of the other geographies, that ZIP code is duplicated in the crosswalk file.
**Example: **ZIP code 03870 is split by two different Census tracts, 33015066000 and 33015071000, which appear in the tract column. The ratio of residential addresses in the first ZIP-Tract record to the total number of residential addresses in the ZIP code is .0042 (.42%). The remaining residential addresses in that ZIP (99.58%) fall into the second ZIP-Tract record.
So, for example, if one wanted to allocate data from ZIP code 03870 to each Census tract located in that ZIP code, one would multiply the number of observations in the ZIP code by the residential ratio for each tract associated with that ZIP code.
https://redivis.com/fileUploads/4ecb405e-f533-4a5b-8286-11e56bb93368%3E" alt="">(Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.)
County definition
In the United States, a county is an administrative or political subdivision of a state that consists of a geographic region with specific boundaries and usually some level of governmental authority. The term "county" is used in 48 U.S. states, while Louisiana and Alaska have functionally equivalent subdivisions called parishes and boroughs, respectively.
Further reading
The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.
Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294. URL: https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdf
Contact information
Questions regarding these crosswalk files can be directed to Alex Din with the subject line HUD-Crosswalks.
Acknowledgement
This dataset is taken from the U.S. Department of Housing and Urban Development (HUD) office: https://www.huduser.gov/portal/datasets/usps_crosswalk.html#codebook
A crosswalk table from US postal ZIP codes to geo-points (latitude, longitude)
Data source: public.opendatasoft.
The ZIP code database contained in 'zipcode.csv' contains 43204 ZIP codes for the continental United States, Alaska, Hawaii, Puerto Rico, and American Samoa. The database is in comma separated value format, with columns for ZIP code, city, state, latitude, longitude, timezone (offset from GMT), and daylight savings time flag (1 if DST is observed in this ZIP code and 0 if not).
This database was composed using ZIP code gazetteers from the US Census Bureau from 1999 and 2000, augmented with additional ZIP code information The database is believed to contain over 98% of the ZIP Codes in current use in the United States. The remaining ZIP Codes absent from this database are entirely PO Box or Firm ZIP codes added in the last five years, which are no longer published by the Census Bureau, but in any event serve a very small minority of the population (probably on the order of .1% or less). Although every attempt has been made to filter them out, this data set may contain up to .5% false positives, that is, ZIP codes that do not exist or are no longer in use but are included due to erroneous data sources. The latitude and longitude given for each ZIP code is typically (though not always) the geographic centroid of the ZIP code; in any event, the location given can generally be expected to lie somewhere within the ZIP code's "boundaries".The ZIP code database contained in 'zipcode.csv' contains 43204 ZIP codes for the continental United States, Alaska, Hawaii, Puerto Rico, and American Samoa. The database is in comma separated value format, with columns for ZIP code, city, state, latitude, longitude, timezone (offset from GMT), and daylight savings time flag (1 if DST is observed in this ZIP code and 0 if not). This database was composed using ZIP code gazetteers from the US Census Bureau from 1999 and 2000, augmented with additional ZIP code information The database is believed to contain over 98% of the ZIP Codes in current use in the United States. The remaining ZIP Codes absent from this database are entirely PO Box or Firm ZIP codes added in the last five years, which are no longer published by the Census Bureau, but in any event serve a very small minority of the population (probably on the order of .1% or less). Although every attempt has been made to filter them out, this data set may contain up to .5% false positives, that is, ZIP codes that do not exist or are no longer in use but are included due to erroneous data sources. The latitude and longitude given for each ZIP code is typically (though not always) the geographic centroid of the ZIP code; in any event, the location given can generally be expected to lie somewhere within the ZIP code's "boundaries".
The database and this README are copyright 2004 CivicSpace Labs, Inc., and are published under a Creative Commons Attribution-ShareAlike license, which requires that all updates must be released under the same license. See http://creativecommons.org/licenses/by-sa/2.0/ for more details. Please contact schuyler@geocoder.us if you are interested in receiving updates to this database as they become available.The database and this README are copyright 2004 CivicSpace Labs, Inc., and are published under a Creative Commons Attribution-ShareAlike license, which requires that all updates must be released under the same license. See http://creativecommons.org/licenses/by-sa/2.0/ for more details. Please contact schuyler@geocoder.us if you are interested in receiving updates to this database as they become available.
The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. These codes may contain leading zeros. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists. The ZCTA boundaries in this release are those delineated following the 2020 Census.
A crosswalk matching US ZIP codes to corresponding CBSA (core-based statistical area)
The denominators used to calculate the address ratios are the ZIP code totals. When a ZIP is split by any of the other geographies, that ZIP code is duplicated in the crosswalk file.
**Example: **ZIP code 03870 is split by two different Census tracts, 33015066000 and 33015071000, which appear in the tract column. The ratio of residential addresses in the first ZIP-Tract record to the total number of residential addresses in the ZIP code is .0042 (.42%). The remaining residential addresses in that ZIP (99.58%) fall into the second ZIP-Tract record.
So, for example, if one wanted to allocate data from ZIP code 03870 to each Census tract located in that ZIP code, one would multiply the number of observations in the ZIP code by the residential ratio for each tract associated with that ZIP code.
https://redivis.com/fileUploads/4ecb405e-f533-4a5b-8286-11e56bb93368%3E" alt="">(Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.)
CBSA definition
A core-based statistical area (CBSA) is a U.S. geographic area defined by the Office of Management and Budget (OMB) that consists of one or more counties (or equivalents) anchored by an urban center of at least 10,000 people plus adjacent counties that are socioeconomically tied to the urban center by commuting. Areas defined on the basis of these standards applied to Census 2000 data were announced by OMB in June 2003. These standards are used to replace the definitions of metropolitan areas that were defined in 1990. The OMB released new standards based on the 2010 Census on July 15, 2015.
Further reading
The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.
Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294. URL: https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdf
Contact authors
Questions regarding these crosswalk files can be directed to Alex Din with the subject line HUD-Crosswalks.
Acknowledgement
This dataset is taken from the U.S. Department of Housing and Urban Development (HUD) office: https://www.huduser.gov/portal/datasets/usps_crosswalk.html#codebook
A global self-hosted Market Research dataset containing all administrative divisions, cities, addresses, and zip codes for 247 countries. All geospatial data is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.
Use cases for the Global Zip Code Database (Market Research data)
Address capture and validation
Map and visualization
Reporting and Business Intelligence (BI)
Master Data Mangement
Logistics and Supply Chain Management
Sales and Marketing
Data export methodology
Our map data packages are offered in variable formats, including .csv. All geographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Product Features
Fully and accurately geocoded
Administrative areas with a level range of 0-4
Multi-language support including address names in local and foreign languages
Comprehensive city definitions across countries
For additional insights, you can combine the map data with:
UNLOCODE and IATA codes
Time zones and Daylight Saving Times
Why do companies choose our Market Research databases
Enterprise-grade service
Reduce integration time and cost by 30%
Weekly updates for the highest quality
Note: Custom geographic data packages are available. Please submit a request via the above contact button for more details.
https://www.geopostcodes.com/privacy-policy/https://www.geopostcodes.com/privacy-policy/
Comprehensive, weekly-updated postal and ZIP code datasets covering 247 countries...
The rural-urban commuting area codes (RUCA) classify U.S. census tracts using measures of urbanization, population density, and daily commuting from the decennial census. The most recent RUCA codes are based on data from the 2000 decennial census. The classification contains two levels. Whole numbers (1-10) delineate metropolitan, micropolitan, small town, and rural commuting areas based on the size and direction of the primary (largest) commuting flows. These 10 codes are further subdivided to permit stricter or looser delimitation of commuting areas, based on secondary (second largest) commuting flows. The approach errs in the direction of more codes, providing flexibility in combining levels to meet varying definitional needs and preferences. The 1990 codes are similarly defined. However, the Census Bureau's methods of defining urban cores and clusters changed between the two censuses. And, census tracts changed in number and shapes. The 2000 rural-urban commuting codes are not directly comparable with the 1990 codes because of these differences. An update of the Rural-Urban Commuting Area Codes is planned for late 2013.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is based on the data provided by the Central Bureau voor de Statistiek on different statistical metrics at the postcode level.Only the 4-digit postcodes (PC4) are available, the 5-digit and 6-digit are not freely available from the Dutch authorities.Enhancements- add administrative hierarchy: Gemeenten and Provincie.
The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.
A comprehensive self-hosted geospatial database of street names, coordinates, and address data ranges for Enterprise use. The address data are georeferenced with industry-standard WGS84 coordinates (geocoding).
All geospatial data are provided in the official local languages. Names and other data in non-Roman languages are also made available in English through translations and transliterations.
Use cases for the Global Address Database (Geospatial data)
Address capture and validation
Parcel delivery
Master Data Management
Logistics and Shipping
Sales and Marketing
Additional features
Fully and accurately geocoded
Multi-language support
Address ranges for streets covered by several zip codes
Comprehensive city definitions across countries
Administrative areas with a level range of 0-4
International Address Formats
For additional insights, you can combine the map data with:
UNLOCODE and IATA codes (geocoded)
Time zones and Daylight Saving Time (DST)
Population data: Past and future trends
Data export methodology
Our location data packages are offered in CSV format. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Why companies choose our location databases
Enterprise-grade service
Reduce integration time and cost by 30%
Frequent, consistent updates for the highest quality
Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.
By Homeland Infrastructure Foundation [source]
The UPS Facilities dataset is a comprehensive collection of information about UPS (United Parcel Service) facilities located across the United States. This dataset provides details on the location, placement, and contact information of each facility.
The dataset includes various columns such as X and Y coordinates, which indicate the longitude and latitude coordinates respectively. These coordinates pinpoint the exact geographic location of each UPS facility. Additionally, there are columns for the name of each facility, address including street address and additional information (ADDRESS2 and ADDRESS3), city, state, ZIP code, phone number for contact purposes.
Furthermore, this dataset provides insightful information about each facility's match status in terms of its address accuracy or completeness. It also includes details about the specific business associated with each UPS facility.
In addition to these data points, there are columns that provide census codes for each facility location. These codes offer additional contextual information related to demographic and socio-economic characteristics associated with each area where a UPS facility is situated.
Overall, this extensive dataset serves as a comprehensive resource for researchers or businesses looking to analyze or utilize information regarding UPS facilities across different states in the United States
Introduction:
Understanding the Dataset Structure: The dataset consists of several columns that provide relevant information about each UPS facility location. Here is a brief overview of the key columns:
NAME: The name of the UPS facility.
ADDRESS: The street address of the UPS facility.
ADDRESS2/ADDRESS3: Additional address information for the facility.
CITY/STATE/ZIP: The city, state, and ZIP code where the facility is located.
PHONE: The contact phone number for the facility.
Additionally, there are geographic coordinates (LATITUDE and LONGITUDE) representing each facility's precise location on a map. Other columns such as PLACEMENT, MATCHSTATU, CENSUSCODE, and BUSINESSNA provide further context regarding placement status, address matching status, census codes for locations, and associated business names.
- Potential Use Cases:
a) Visualizing Facility Distribution: Using latitude and longitude coordinates from this dataset with mapping tools like Python's Folium or Tableau can help create interactive maps that showcase spatial distributions across different regions.
b) Analyzing Facility Density: By aggregating data at regional levels (e.g., state-wise), you can analyze which areas have higher concentrations of UPS facilities compared to others. This analysis may offer insights into patterns related to population density or commercial activity.
c) Optimizing Transportation Routes: Understanding where these facilities are located can be beneficial for route optimization. By analyzing facility placements and their proximity to transportation networks, you can identify potential areas for streamlining logistics operations.
d) Market Research: The dataset's additional columns (such as BUSINESSNA) allow researchers to analyze UPS facilities within the context of associated businesses. This information can be useful for market research, identifying industry clusters, or studying supply chain dynamics.
Data Cleaning and Preprocessing: Before utilizing this dataset, it is recommended to perform standard data cleaning procedures, such as handling missing or incorrect values. Pay attention to any inconsistencies in column names or encoding formats that may require normalization.
Combining with Other Datasets: To
- Geospatial analysis: This dataset can be used for geospatial analysis to analyze the distribution and concentration of UPS facilities across different states or cities. It can help identify areas with high or low availability of UPS services and assist logistics planning and decision making.
- Customer segmentation: By combining this dataset with customer data, businesses can segment their customers based on proximity to UPS facilities. This can help companies optimize their delivery routes, improve customer service, and target marketing efforts more effectively.
- Benchmarking and competition analysis: The dataset can also be used for benchmarking purposes by comparing the number of UPS facilities in different regions or against competito...
Our World Administrative Boundaries Database offers comprehensive postal code data for spatial analysis, including postal and administrative areas. This dataset contains accurate and up-to-date information on all administrative divisions, cities, and zip codes, making it an invaluable resource for various applications such as address capture and validation, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including CSV, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Product features include fully and accurately geocoded data, multi-language support with address names in local and foreign languages, comprehensive city definitions, and the option to combine map data with UNLOCODE and IATA codes, time zones, and daylight saving times. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.
Address ranges describe a label given to a unique collection of addresses that fall along a road or path. Address ranges provide a way of locating homes and businesses based on their street addresses when no other location information is available.Using a house number, street name, street side and ZIP code, address ranges can locate the address to the geographic area associated to that side of the street. Once geocoded, the U.S. Census Bureau can assign the address to a field assignment area or tabulate the data for that address. In addition, academics, researchers, professionals and government agencies outside of the Census Bureau use MAF/TIGER address ranges to transform tabular addresses into geographical datasets for decision-making and analytical purposes.Address ranges must be unique to geocode addresses to the correct location and avoid geocoding conflicts. Multiple elements in MAF/TIGER are required to make an address range unique including street names, address house numbers and street feature geometries, such as street centerlines. The address range data model is designed to maximize geocoding matches with their correct geographic areas in MAF/TIGER by allowing an unlimited number of address range-to-street feature relationships.The Census Bureau’s Geography Division devises numerous operations and processes to build and maintain high quality address ranges so that:Address ranges accurately describe the location of addresses on the ground.Address All possible city-style addresses are geocoded.Address ranges can handle all known address and street name variations.Address ranges conform with current U.S. Postal Service ZIP codes.Address ranges are reliable and free from conflicts.Automated software continually updates existing address ranges, builds new address ranges and corrects errors. An automated operation links address location points and tabular address information to street feature edges with matching street names in the same block to build and modify address ranges.Many business rules and legal value checks ensure quality address range data in MAF/TIGER. For example, business rules prevent adding or modifying address ranges that overlap another house number range with the same street name and ZIP code. Legal value checks verify that address ranges include mandatory attribute information, valid data types and valid character values.Some of the TIGER/Line products for the public include address ranges and give the public the ability to geocode addresses to MAF/TIGER address ranges for the user’s own purpose. The address range files are available for the nation, Puerto Rico and the U.S. Island Areas at the county level. TIGER/Line files require geographic information system (GIS) software to use.The Census Bureau Geocoder Service is a web service provided to the public. The service accepts up to 1,000 input addresses and, based on Census address ranges, returns the interpolated geocoded location and census geographies. Users can access the service a web interface or a representational state transfer (REST) application program interface (API) web service. See the Census Geocoder for more information on this process. Directions on how to use the Census Geocoder available: Geocoding Services Web Application Programming Interface (API)Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_addr.gdb.zip
https://www.spotzi.com/en/about/terms-of-service/https://www.spotzi.com/en/about/terms-of-service/
Looking for a detailed 4-digit postal code map of Austria? With Spotzi, you can explore this Austrian ZIP code data in our dashboards for free. Create a free account and unlock access to our powerful postcode dashboard to analyze, segment, and target areas like never before.
Access the map instantly without payment or commitment. By registering a free Spotzi account, you also get access to advanced tools: radius filters, drivetime filters, build heatmaps, and even export postcode selections to use in your next marketing campaign. It's the easiest way to turn location data into action – no technical skills required.
No data experience needed – just results. Start using Austria ZIP code data to drive your next marketing move.
https://www.spotzi.com/en/about/terms-of-service/https://www.spotzi.com/en/about/terms-of-service/
Looking for a detailed 4-digit postal code map of Belgium? With Spotzi, you can explore this Belgian ZIP code data in our dashboards for free. Create a free account and unlock access to our powerful postcode dashboard to analyze, segment, and target areas like never before.
Access the map instantly without payment or commitment. By registering a free Spotzi account, you also get access to advanced tools: radius filters, drivetime filters, build heatmaps, and even export postcode selections to use in your next marketing campaign. It's the easiest way to turn location data into action – no technical skills required.
No data experience needed – just results. Start using Belgium ZIP code data to drive your next marketing move.
A global self-hosted location dataset containing all administrative divisions, cities, and zip codes for 247 countries. All geospatial data is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.
Use cases for the Global Zip Code Database (Geospatial data)
Address capture and validation
Map and visualization
Reporting and Business Intelligence (BI)
Master Data Mangement
Logistics and Supply Chain Management
Sales and Marketing
Data export methodology
Our location data packages are offered in variable formats, including .csv. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Product Features
Fully and accurately geocoded
Administrative areas with a level range of 0-4
Multi-language support including address names in local and foreign languages
Comprehensive city definitions across countries
For additional insights, you can combine the map data with:
UNLOCODE and IATA codes
Time zones and Daylight Saving Times
Why do companies choose our location databases
Enterprise-grade service
Reduce integration time and cost by 30%
Weekly updates for the highest quality
Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.