This API returns a search for the demographic information for a particular geography type and geography ID

This API returns a search for the demographic information for the whole nation.

This archive reproduces a table titled "Table 3.1 Boone county population size, 1990 and 2000" from Wang and vom Hofe (2007, p.58). The archive provides a Jupyter Notebook that uses Python and can be run in Google Colaboratory. The workflow uses Census API to retrieve data, reproduce the table, and ensure reproducibility for anyone accessing this archive.The Python code was developed in Google Colaboratory, or Google Colab for short, which is an Integrated Development Environment (IDE) of JupyterLab and streamlines package installation, code collaboration and management. The Census API is used to obtain population counts from the 1990 and 2000 Decennial Census (Summary File 1, 100% data). All downloaded data are maintained in the notebook's temporary working directory while in use. The data are also stored separately with this archive.The notebook features extensive explanations, comments, code snippets, and code output. The notebook can be viewed in a PDF format or downloaded and opened in Google Colab. References to external resources are also provided for the various functional components. The notebook features code to perform the following functions:install/import necessary Python packagesintroduce a Census API Querydownload Census data via CensusAPI manipulate Census tabular data calculate absolute change and percent changeformatting numbersexport the table to csvThe notebook can be modified to perform the same operations for any county in the United States by changing the State and County FIPS code parameters for the Census API downloads. The notebook could be adapted for use in other environments (i.e., Jupyter Notebook) as well as reading and writing files to a local or shared drive, or cloud drive (i.e., Google Drive).

Demografy is a privacy by design customer demographics prediction AI platform.

Core features: - Demographic segmentation - Demographic analytics - API integration - Data export

Key advantages: - 100% coverage of lists - Accuracy estimate before purchase - GDPR-compliance as no sensitive data is required. Demografy can work with only first names or masked last names

Use cases: - Actionable analytics about your customers to get demographic insights - Appending missing demographic data to your records for customer segmentation and targeted marketing campaigns - Enhanced personalization knowing you customer better

Unlike traditional solutions, you don’t need to know and disclose your customer or prospect addresses, emails or other sensitive information. You can provide even masked last names keeping personal data in-house. This makes Demografy privacy by design and enables you to get 100% coverage of your audience since all you need to know is names.

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This method returns Census 2021 estimates on the number of households in England and Wales.

The estimates are as at Census Day, 21 March 2021.

Analysis of ‘Demographic indicators. ADRH (API identifier: 30886)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-507-30886 on 19 January 2022.

--- Dataset description provided by original source is as follows ---

Table of Experimental Statistics. Demographic indicators. Annual. Municipalities. Household Income Distribution Atlas

--- Original source retains full ownership of the source dataset ---

Table of INEBase Demographic indicators. Annual. Municipalities. Household Income Distribution Atlas

This API returns the demographics data from the coordinates.

This layer shows total population count by sex and age group. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent and count of the dependent population (ages 65+ and <18). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B01001Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

This dataset contains information about the demographics of all US cities and census-designated places with a population greater or equal to 65,000. This data comes from the US Census Bureau's 2015 American Community Survey. This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.

Table of INEBase Population by gender and country of birth (main countries). Annual. Municipalities. Censo de Población

This API returns the US Census Block geography ID information given a passed Latitude and Longitude.

Source: U.S. Census Bureau; 2011-2015 American Community Survey 5-Year Estimates, Table B02015, B02016.

Colorado Department of Local Affairs has created an API for all states and all years of Census Data back to 1980. Discover the uses of this API and more by exploring the dedicated GitHub page (link in metadata).

Table of INEBase Population by sex, municipalities and age (five-year groups). Annual. Continuous Register Statistics

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Table of Experimental Statistics. Demographic indicators. Annual. Municipalities. Household Income Distribution Atlas

Unlock powerful insights with our BatchService Homeowner and Household Demographic Data. Access 35+ data points across 107M+ properties, perfect for targeted marketing, research, and analysis. Dive into detailed homeowner profiles and household characteristics with ease.

BatchData offers cutting-edge API and dataset solutions designed to empower businesses with comprehensive data insights. BatchData provides access to a vast array of information, including detailed homeowner and household demographic across millions of properties. With seamless integration via our API, you can effortlessly incorporate rich data into your websites, applications, and analytics tools. This enables precise lead generation, targeted marketing, and in-depth market analysis, helping you make informed decisions and drive growth.

Explore the extensive data we points we have below to understand the diverse and detailed information included in our dataset: - The property owner's age - Primary occupant is a business owner? - The primary occupant's child count - The household discretionary income - The primary occupant's gender - Primary occupant has children? - Occupants are owners or renters? - Household size - Household income - Primary occupant's individual education - Primary occupant's occupation - Primary occupant's investments - Primary occupant's marital status - Primary occupant is a millionaire? - Household net worth - Primary occupant is a pet owner? - Primary occupant recently divorced? - Primary occupant recently moved? Month? Year? - Property owner's religious affiliation - Primary occupant single parent? - Primary occupant smoker?

This indicator shows the number of persons in each of the API races. *Note: These numbers may include Hispanic and Non-Hispanic Asian/Pacific Islanders.

Source: U.S. Census Bureau; 2013-2017 American Community Survey 5-Year Estimates, Table B02015, B02016.