The data are the most current income statistics from the US Census Bureau. At the bottom of all of zip code pages, there's a section called "About the Data" that has the full citations.
Check out the Income in the Past 12 Months section in the Census’ Subject Definitions document here: https://www2.census.gov/programs-surveys/acs/tech_docs/subject_definitions/2018_ACSSubjectDefinitions.pdf
First, check out the details about Census Bureau income data (question above).
One great feature of this Census data is that margins of error are included, so you'll know how confident you can be in the income estimates. Margins of error are + or - the estimate value. For example, Carbondale city, Illinois has a 2010 poverty percent estimate of 44.5% +/- 3.3%. That means, that the US Census Bureau is 90% confident that the poverty percent for Carbondale city, Illinois is between 41.2% and 47.8%.
You can find the margins of error in the "About the Data" section at the bottom of each zip code page, and they are included in the zip code lists.
Since the demographic data on this website and in the reports is from the US Census Bureau, we’re using the US Census Bureau’s ZIP Code Tabulation Areas (ZCTAs), which are generalized areal representations of United States Postal Service ZIP Code service areas.
A zip code is technically a linear postal route. I like to imagine zips codes as a postman driving in a line up and down streets delivering mail. Here’s a fun animation about how the Census Bureau turns linear routes into polygons: https://web.archive.org/web/20161209173248/https://www.census.gov/geo/reference/zcta/zcta_delin_anim.html
Sometimes, there isn’t a ZCTA for a "weird" zip code. The most common example of "weird" zips are PO Box zips (so zips of only businesses and no residents, and you need residents for demographic estimates). Other weird zips that we’ve run into in the past include a zip only for the IRS or a post office. And sometimes there aren't enough samples in a zip/ZCTA to produce an estimate (aka too few people living in the zip).
On this website, we use the terms ZCTA, zip code or zip interchangeably, because most people who we work with don’t know what a ZCTA is and the difference between a zip code and ZCTA doesn’t impact how they need to use the data. But theoretical problems could arise with using ZCTAs if you are doing a mailing list or mass mail project.
Check out this handy zip to ZCTA crosswalk.
Let’s say you were asked to rank a list of addresses from most likely to buy to least likely to buy. Since this is a quick test to see if using demographic data will improve your close rate, you are going to simply associate each lead with some basic demographics for the zip like median household income. 90% of your addresses have zips that match ZCTAs, so it’s easy to match these leads with their ZCTA demographics. But the remaining 10% of your addresses don’t have a matching ZCTA. You could then use the above crosswalk to associate the “weird” zips with a ZCTA and thus pull demographics for the rest of your addresses.Got more zip/ZCTA questions? Contact us.
For the 2018 dataset, there are 33,120 ZCTAs. A handful of these ZCTAs do not have estimates (null) or have estimates of $0.
Let’s say you had the following simplified population & income numbers.
The average income for this population is $360,000. The outlier data point ($1,000,000) skews the average up. Also, the average would be skewed down if there was a person with $0 in income.
The median income for the same population above is $50,000. The outlier data point ($1,000,000) doesn’t skew the median.
If the data are equally distributed (i.e. $30K, $40K, $50K), then the average number won’t be skewed by outliers. But if the data are unequally distributed, as in the case of income, then the median is the better statistic.
Most folks are familiar with the US Census Bureau's Decennial Census (2010) that sends a survey out to all (ideally!) US households. But what's not as well known is that the US Census Bureau also collects data each year from a much smaller sample of US households, and they use this annual data to produce a dataset called the American Community Survey. Now because the sample size of the American Community Survey is small, the Census Bureau can only produce annual demographic estimates for large geographies like New York City or Harris County, Texas. For small geographies like zip codes/ZCTAs, they have to sum the survey data that's collected in multiple years to produce estimates with reasonable margins of error.
The most current data available from the US Census Bureau for zip codes/ZCTAs is from a dataset called the 2014-2018 American Community Survey. The US Census Bureau has taken American Community Survey data collected in 2014, 2015, 2016, 2017 and 2018 and uses this data to produce demographic estimates for zip codes/ZCTAs for 2018. When the Census Bureau collects income data in 2014 and then they use the 2014 data to estimate the 2018 income, they need to adjust the income reported in 2014 to 2018 dollars to account for inflation.
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These instructions are optimized for Excel, but function much the same in other spreadsheet programs like LibreOffice Calc and Google Sheets. First, set up sorting and filtering
From the "Editing" group on the Home Ribbon, select Filter from the 'Sort & Filter' menu.
Click on the arrow next to the field you want to sort, and click on "Sort Smallest to Largest" or Sort Largest to Smallest".
Click on the arrow next to state
Either select/deselect the check boxes next to the states…
…or type a state in the search box
You can first narrow down the results by filtering first if you know which state your city or county is in.
Then click on the arrow next to the City or County and type the name of the geography you want to search for.
In some cases, you may get geographies with the same name, but are located in different parts of a state. You can further refine your search results using the County field.
Yes. We pull demographic data from over 60 government databases as well as from a handful of private data companies. We’ve pulled data for over 6,000 clients since 2009 and love finding unusual data that answers your questions. You can learn more about Custom Data pulls here: https://www.cubitplanning.com/data/buy-census-data
We have the income and demographic data for zips/ZCTAs in the US from the US Census Bureau for:
We can calculate an average adjusted gross income for all zips in the US from the IRS for:
Usually, we charge $100 per year for historic income data pulls. Either call Kristen at 1.800.939.2130 to discuss what you need, or complete the Custom Data pull form here: https://www.cubitplanning.com/data/buy-census-data
We and the US Census Bureau recommend against comparing across the Census’ American Community Survey 5 year datasets (2011, 2012, 2013, 2014, 2015, 2016, 2017 and 2018) with overlapping years. Here's why.
The 2011 demographics are based on American Community Survey data that were collected in the years 2007, 2008, 2009, 2010 and 2011.
The 2015 demographics are based on the American Community Survey data that were collected in the years 2011, 2012, 2013, 2014 and 2015.
The 2016 demographics are based on the American Community Survey data that were collected in the years 2012, 2013, 2014, 2015 and 2016.
So there's 1 year of overlapping data between these 2 datasets (2011). In a perfect world, it would be better to compare 2011 data to 2016 data, because 2016 will be the first year that the 5 year datasets don't contain overlapping collection years for zip codes. Other geographies, like Census tracts, county subdivisions, or places were available in the 2010 5-year ACS, and are therefore comparable to 2015 5-year ACS estimates assuming their geographic boundaries remained the same or any changes are accounted for.
Now you know the challenges of comparing Census data between years. All of that said, folks still make these comparisons all of the time, and say "well, this is the best we can do with the data, time & budget limitations that we have for this particular project."
There aren’t monthly median household income data for zips/ZCTAs from a US government data source. There may be monthly, historic income data in a private database for sale out there that we don’t know about, but the private data vendors that we work with don’t provide monthly income data for zip codes. See also the question above about available historic income data.
Yes. Check out a sample map & learn more here: https://www.cubitplanning.com/data/buy-custom-maps
Probably. Either call Kristen at 1.800.939.2130 to discuss what you need, or complete the Custom Data pull form here: https://www.cubitplanning.com/data/buy-census-data
Yes, you can get data for Census tracts, block groups and blocks – all of which tend to be smaller than zip codes.
No. We only provide data for geographies, not for individuals. For example, we’ll let you know that there are 1,234 households who make over $200,000 in a zip code but not that the Smith family who lives on 987 Main Street make over $200,000.
Usually, we provide the data in an Excel file (.xlsx), but we can also provide it as in .csv and .txt formats if you prefer. If you'd prefer a .csv or .txt, add a note like "please provide as .csv." in the field on the order form named "Any other notes or thoughts about your data needs?" If you need .sql or a database file, please call Kristen at 1.800.939.2130 or Contact Us.
It's actually more work for us to provide a file with data for X number of zips/ZCTAs than to provide data for all zips, because we have to delete all of the zips that you don't need data for. So no, there’s no lower price available for fewer zips.
For 99% of our clients, we charge by the data pull. For 1% of our clients, we set up a custom subscription. The price of each subscription depends on how much data you need and how often you need data. Call Kristen at 1.800.939.2130 if you’d like to talk about setting up a custom subscription.
No. Whenever we’ve talked to clients about building APIs in the past, it’s always been a better deal for them to get annual data dumps rather than for us to build an API.
As a small company with a tight budget for projects, we completely understand your desire for a discount. That said, we don't have discounts or different prices for different types of customers, because it's important to us that everyone can purchase data at our best possible price.
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