Established in 1972 as Infogroup, Data Axle is a big data, analytics, and marketing services provider. Data Axle provides both digital and traditional marketing channel expertise drawing on proprietary data collected on millions of U.S. businesses.
Formerly named Infogroup Residential USA, this dataset provides household-level information on residences in the United States, at national, state, county, census tract, and ZIP code levels. Estimates of household income, wealth, purchasing power, and home value by residences are segmented by household and dwelling characteristics, allowing users to analyze community growth and declines in population and economic levels over time across geographies.
The many indicators included in Data Axle Historical US Residential can be viewed as stand-alone trends, charts, or maps in Data Planet. View the listing of indicators opening the Data Axle Reference Solutions: Historical US Residential entries in the Browse by Source or Browse by Subject - Population and Income. For example, the chart below ranks Cook County (Illinois) households by percentage renting or owning their residence.
Note that you can learn more about the indicator, dataset, and source by viewing the statistical abstract that appears below the chart, as below. These summaries can be exported with the graph by clicking on the Export link in the menu bar above the chart. The Create DOI link allows you to create a DOI that ensures that each time you reference the data in a paper or elsewhere that the reader can view the exact view of the DataSheet at the time you created it. For more information on DOIs, click here.
The unique implementation of Data Axle Historical US Residential allows you to compare indicators across industries, states, counties, and zip codes, and to create trends, rankings, and more - so be sure to explore the many options available to do so. To select multiple indicators, use the Compare Datasets option at the top of the Dataset list:
See the examples below and try it yourself with other indicators and geographies. Keep in mind that the graphs you create do not necessarily imply causality: the results may suggest a potential relationship between the variables you select, which may be an interesting line of inquiry for your own research.
Use Data Planet to compare and contrast Data Axle Historical US Residential data across geographies. For example, the chart below compares counts of residences with home values in the $900,000 - $999,999 range in four Southern states:
The trend below compares households by length of residence in two Pennsylvania counties:
You can also create maps showing locations of households by household and dwelling characteristics. For example, the infographic below maps New York ZIP codes by counts of households with estimated wealth between $1 million and $2,499,999.