Demographic statistics broken down by zip code

Our United States zip code 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.

The 2020 Zip Code Boundaries dataset contains boundary information for Zip Code Tabulation Areas (ZCTAs) as of the 2020 Census, sourced from the United States Census Bureau. ZCTAs are statistical representations of USPS ZIP Code service areas and are used for demographic analysis, data aggregation, and geographic reference purposes. This dataset includes boundary polygons for each ZCTA, allowing users to visualize and analyze ZIP Code boundaries within Montgomery County, Texas.Data Fields Included:ZCTA CodeAreaThis dataset is sourced from the United States Census Bureau.Data source: United States Census Bureau TIGER Data

Our Poland zip code 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.

Overview

Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

Our self-hosted geospatial data cover postal divisions for the whole world. The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

Use cases for the Global Boundaries Database (Geospatial data, Map data, Polygon daa)

• In-depth spatial analysis

• Clustering

• Geofencing

• Reverse Geocoding

• Reporting and Business Intelligence (BI)

Product Features

• Coherence and precision at every level

• Edge-matched polygons

• High-precision shapes for spatial analysis

• Fast-loading polygons for reporting and BI

• Multi-language support

For additional insights, you can combine the map data with:

• Population data: Historical and future trends

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Time (DST)

Data export methodology

Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our map data

• Precision at every level

• Coverage of difficult geographies

• No gaps, nor overlaps

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

This Zipcode GIS Layer is a spatial dataset that outlines the boundaries of ZIP code areas across York County, Pennsylvania. This layer is used in Geographic Information Systems (GIS) to support mapping, analysis, and decision-making based on location. Each ZIP code area is represented as a shape on the map and includes basic information such as the ZIP code, city, and state. This data is useful for a wide range of applications including business planning, public services, marketing, transportation, and emergency response. The Zipcode GIS Layer allows users to visualize and analyze geographic patterns, such as population distribution, service coverage, and regional trends. It can be used on its own or combined with other spatial data for more detailed studies.

The 2010 Zip Code Boundaries dataset contains boundary information for Zip Code Tabulation Areas (ZCTAs) as of the 2010 Census, sourced from the United States Census Bureau. ZCTAs are statistical representations of USPS ZIP Code service areas and are used for demographic analysis, data aggregation, and geographic reference purposes. This dataset includes boundary polygons for each ZCTA, allowing users to visualize and analyze ZIP Code boundaries within Montgomery County, Texas.Data Fields Included:ZCTA CodeAreaThis dataset is sourced from the United States Census Bureau.Data source: United States Census Bureau TIGER Data

Our New Caledonia zip code 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.

Our Greece zip code 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.

This Zipcode GIS Layer is a spatial dataset that outlines the boundaries of ZIP code areas across York County, Pennsylvania. This layer is used in Geographic Information Systems (GIS) to support mapping, analysis, and decision-making based on location. Each ZIP code area is represented as a shape on the map and includes basic information such as the ZIP code, city, and state. This data is useful for a wide range of applications including business planning, public services, marketing, transportation, and emergency response. The Zipcode GIS Layer allows users to visualize and analyze geographic patterns, such as population distribution, service coverage, and regional trends. It can be used on its own or combined with other spatial data for more detailed studies.

Our Reunion zip code 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.

The Geospatial Imagery Analytics Marketsize was valued at USD 11.88 USD Billion in 2023 and is projected to reach USD 83.39 USD Billion by 2032, exhibiting a CAGR of 32.1 % during the forecast period.Geospatial analytics gathers, manipulates, and displays geographic information system (GIS) data and imagery including GPS and satellite photographs. Geospatial data analytics rely on geographic coordinates and specific identifiers such as street address and zip code. geospatial visualization enables businesses to better understand complex information and make informed decisions. They can quickly see patterns and trends and assess the impact of different variables by visualizing data in a spatial context. The field encompasses several techniques and algorithms, such as spatial interpolation, spatial regression, spatial clustering, and spatial autocorrelation analysis, which help extract insights from various geospatial data sources. The growing adoption of location-based services in various industries, including agriculture, defense, and urban planning, is driving the demand for geospatial imagery analytics. Recent developments include: August 2023: onX, a digital navigation company, partnered with Planet Labs PBC, a satellite imagery provider, to introduce a new feature called ‘Recent Imagery’. This feature offers onX app users updated satellite imagery maps every two weeks, enhancing the user experience across onX Hunt, onX Offroad, and onX Backcountry apps. This frequent data update helps outdoor enthusiasts access real-time information for safer and more informed outdoor activities., August 2023: Quant Data & Analytics, a provider of data products and enterprise solutions for real estate and retail, partnered with Satellogic Inc. to utilize Satellogic’s high-resolution satellite imagery to enhance property technology in Saudi Arabia and the Gulf region., April 2023: Astraea, a spatiotemporal data and analytics platform, introduced a new ordering service that grants customers scalable access to top-tier commercial satellite imagery from providers such as Planet Labs PBC and others., May 2022: Satellogic Inc. established a partnership with UP42. This geospatial developer platform enables direct access to Satellogic’s satellite tasking capabilities, including high-resolution multispectral and wide-area hyperspectral imagery, through the UP42 API-based platform., April 2022: TomTom International BV, a geolocation tech company, broadened its partnership with Maxar Technologies, a space solution provider. This expansion involves integrating high-resolution global satellite imagery from Maxar’s Vivid imagery base maps into TomTom’s product lineup, enhancing their visualization solutions for customers.. Key drivers for this market are: Growing Demand for Location-based Insights across Diverse Industries to Fuel Market Growth. Potential restraints include: Complexity and Cost Associated with Data Acquisition and Processing May Hamper Market Growth. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

Our Russia zip code 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.

Spotzi’s premium 3-digit postal code data for Europe (EUR) gives marketers, retailers, and OOH professionals everything they need to understand and reach their audience more effectively. Our high-quality boundary data lets you visualize every postal code area, build precise targeting strategies, create sales territories, and uncover valuable demographic and campaign insights—all in one easy-to-use dashboard.

With a Spotzi Premium account, you can explore, customize, and export European postal code boundaries for activation across your channels. Whether you're planning a national campaign or analyzing store visitors by location, Spotzi eliminates the hassle of complex data management so you can focus on driving results.

Spotzi’s premium 6-digit postal code data for Switzerland (CHE) gives marketers, retailers, and OOH professionals everything they need to understand and reach their audience more effectively. Our high-quality boundary data lets you visualize every postal code area, build precise targeting strategies, create sales territories, and uncover valuable demographic and campaign insights—all in one easy-to-use dashboard.

With a Spotzi Premium account, you can explore, customize, and export Swiss postal code boundaries for activation across your channels. Whether you're planning a national campaign or analyzing store visitors by location, Spotzi eliminates the hassle of complex data management so you can focus on driving results.

Wealth Segmentation of U.S. ZIP Codes Based on IRS Data

This dataset provides a wealth-tier classification of U.S. ZIP codes for high income brackets using IRS income data and multivariate KMeans clustering. It can help with regional targeting, CRM enrichment, market analysis, or any data science task that benefits from understanding high income distribution across the U.S.

💡 Source

• IRS SOI ZIP Code Data (open source)
• Aggregated across AGI brackets (stub 3–6)

🧠 What’s Inside

Each row represents a ZIP code with:

• AGI (A00100), Total Income (A00200)
• Capital Gains, Business Income, Tax Paid
• Cluster assignment (0–2)
• Wealth Tier label: Low, Medium, or High

The cluster assignments are refined using distance to cluster centroids in normalized feature space to improve accuracy.

💼 Use Cases

• Segmenting markets for B2B/B2C outreach
• CRM lead enrichment
• Territory planning and resource allocation
• Visualization and dashboard overlays

📬 Contact

Created by Namrata Nyamagoudar(LinkedIn) for open-source analysis and enrichment use cases.

Spotzi’s premium 4-digit postal code data for Hungary (HUN) gives marketers, retailers, and OOH professionals everything they need to understand and reach their audience more effectively. Our high-quality boundary data lets you visualize every postal code area, build precise targeting strategies, create sales territories, and uncover valuable demographic and campaign insights—all in one easy-to-use dashboard.

With a Spotzi Premium account, you can explore, customize, and export Hungarian postal code boundaries for activation across your channels. Whether you're planning a national campaign or analyzing store visitors by location, Spotzi eliminates the hassle of complex data management so you can focus on driving results.

The most complete and up-to-date Canadian postal code database for accurate customer profiling, direct marketing optimization, precise territory management, and serviceability insights. Postal Code Suite offers six digit postal code polygons so you can visualize postal code boundaries on a map. Each zip package includes Multiple Enhanced Postal Codes, Forward Sortation Areas, Local Delivery Units and topographic layers, for the province/territory, as well as Canada wide layers for area codes, capital cities, provincial boundaries, municipal boundaries, topographic boundaries, time zones and water layers.

Our India zip code 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.

Exploring Potential Tax and Water Liens in NYC

Investigating Geographic Distribution and Effects of Local Policies

By data.world's Admin [source]

About this dataset

This dataset captures properties in New York City that have tax and/or water liens potentially eligible to be included in the next lien sale. Explore the city's fiscal landscape with information about borough, lot, tax class code, building classes, community board, council district, house number street name and zip code. This data is updated monthly with new liens being added from the most current month back to 12 months prior. By analyzing this data you can gain greater insight into New York City’s financial conditions over time as well as how this affects individual properties throughout the city. This data is provided by the New York City open data portal is subject to terms of use outlined on its website so please refer to it for any additional information regarding usage rights

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How to use the dataset

This data is sourced from New York City's Open Data portal. By exploring this dataset you can search for properties with possible tax and/or water liens located in a particular area or neighborhood or by a specific attribute such as the house number or street name. You can also take a look at particular subsections of potential eligible lien sale records over time – for example you could look at all potential water debt liens only during a certain month – to get some more specific insights into what tax and water liens may be available at certain points in time. To use this dataset please note the following important tips: • Start by familiarizing yourself with each column’s field meaning (using our table above); • When searching for records use quotation marks if you are looking up something which is two words (e.g “construction”) ;
• Use an underscore _for replacing spaces if necessary e.g “west_village”;
• Be aware that Boroughs are referenced by their full names (e.g Manhattan, Queens, etc);
• If using wild cards (*) make sure not to put them on either side of your query - e.g instead of Lastname * use Lastname*.
We hope this guide was helpful and good luck exploring!

Research Ideas

• Real Estate Investment Analysis: Create a platform or tool using this dataset to assist individuals looking to invest in properties with potential tax and water liens. The platform/tool should provide insights into the best locations for purchasing real estate based on location, tax class code, building class and council district data points from this dataset.
• Tax Foreclosure Notifications: Use this dataset to create an automated notification system which informs registered users when a property they are interested in is coming up for sale with a lien in the next sale date.
• Local Planning Solutions: Leverage data from this dataset to identify areas where there might be concentration of properties with tax liens that could potentially benefit from local planning solutions such as community grants, affordable housing initiatives etc.. This could help municipalities deploy resources more effectively towards restoring distressed properties instead of letting them slip out of their control via foreclosure at lien sales

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: tax-lien-sale-lists-1.csv | Column name | Description | |:---------------------|:-----------------------------------------------------------------| | Month | The month in which the lien sale is eligible. (String) | | Borough | The borough in which the property is located. (String) | | Lot | The lot number of the property. (Integer) | | Tax Class Code | The tax class code of the property. (Integer) | | Building Class | The building class of the property. (String) | | Community Board | The community board in which the property is located. (Integer) | | Council District | The council district in which the property is located. (Integer) | | House Number | The house number of the property. (Integer) | | Street Name | The street name of the property. (String) | | Zip Code | The zip code of the p...