Congressional Districts By Zip Code Spreadsheet
Queila Neubecker
Hello, I downloaded a total population table 2000-present. I selected options to have it by zip code, county, and congressional district. I received a few separate files, each one exclusive of another. I was hoping to have congressional district, zip code, and county all in one spreadsheet. Is there a way to do this? I am not sure how to join them. Would greatly appreciate your guidance. Thank you.
Do you want to have the data structured so that each record is a unique combination of ZIP code, county and CD? We do not have a data file that provides information for that combination of geographic units.
It is possible to generate a dataset like that from the decennial census data. Census blocks will have codes for ZIP codes, counties and congressional districts. You can then collapse the data on those variables to create a file where each record is a unique combination of ZIP, county, and congressional district.
Hello Dave, thank you for the reply. Yes, I was hoping to obtain that unique combination. A combination of zip codes-congressional district would work just as well. However, I know that a single zip code can, at times, map to several congressional districts. Also, from tables that I did download, it referenced the 106th and 107th congressional districts. If I wanted the data (zip code-congressional district combinations) based on those congressional districts, how would I go about that? The redistricting based on the 1990 census started in a subsequent congress with different states enacting redistricting during different congresses. Your guidance for how to proceed would be much appreciated.
If you then download the population count for each census block, you can merge the population count on the output of the overlay operation. Then you can roll up the block file by ZIP code and CD code to generate counts for each combination of ZIP and CD.
Hello Dave, thank you for your response. I believe that the first congressional districts drawn based on the 2000 census did not roll out until the 108th congress. So I believe that the 106th and 107th congressional districts were still based on the 1990 census, but there is a lag to how the CDs are updated given that there is between state heterogeneity in enacting them. So it would have to be data that gave me the 106-107th congress CDs.
Also, I am not familiar with any geosoftware. I am aware that Arcgis is commonly used. Perhaps this is unanswerable, but how straight forward is loading the maps and conducting the process you describe to combine the data?
When the Census Bureau delineated 2000 census blocks, the blocks will follow the congressional districts that were in existence at the time (e.g., the 106th CD). They would also then nest within the 107th CDs (although as far as I am aware, the 106th and 107th CDs are exactly the same). Thus, the 2000 blocks will align perfectly with the 106th and 107th CDs.
We also have the 1990 census blocks (which would have been used as the building blocks for the 106th and 107th CDs). You will need to use those if you want to generate 1990 census-based population counts for the unique intersections.
One option is to determine the spatial relationships using 2020 TIGER/Line files, which should provide boundaries for both 2010 blocks and 117th CDs. We aim to provide the NHGIS version of the 117th CD boundary file in the next week or two, but it may be a while longer before we provide updated 2020-TIGER-based versions of 2010 blocks.
In addition to data matching, Geocodio makes it easier to work with address data by automatically standardizing, parsing, and completing addresses. If you're working with data compiled from multiple sources, running it through Geocodio can make it easier to work with.
Vote.org is the largest non-profit, non-partisan voting information platform. It makes it easy for people to find their polling place, the candidates on their local ballot, and other election information. In 2018, they helped over 5 million people find their polling places and get information about the candidates in their races.
Behind the scenes, Vote.org used Geocodio as part of their stack to connect voter addresses to Congressional districts. They then used this data to help voters get ready for the election through ballot information, registration deadlines, and polling place information. Ahead of Election Day, they emailed reminders to over 5 million people and text-message reminders to 2 million people.
Before Geocodio, they were using a tool that provided Congressional districts based on ZIP codes, which was 95% accurate. But that 5% error rate was too high, as people might get the wrong information about the election. That led them to look for a new solution, and led them to Geocodio.
The Workforce Development Institute makes linkages between policy makers, businesses, educational institutions, and other organizations across New York State to drive workforce and economic growth. They use Geocodio to normalize their address data and quickly gather key additional insights that help them tailor their analysis to each audience.
For example, a high school may want to know which businesses in their area are hiring CNC machinists or a Legislator may request data on job openings, in-demand skills, and workforce training in their district. From a data perspective, this means marrying address data to school districts, state legislative districts, Congressional districts, and Census data.
This article shows you how to add Congressional districts to addresses using Geocodio. The Congressional district data returned includes Congressional district number, Congress number, and Congress years, with the option to append legislator data. You can use our API to integrate it into a website, or upload Excel, CSV, and TSV files.
The first step will be to organize the addresses into a spreadsheet. Your spreadsheet will need to have headers (street, city, state or street + zip). The addresses can all be in one column or in multiple columns, as shown below, as long as it is consistent for the entire spreadsheet.
You can also download an example spreadsheet here. The addresses can be missing information as long as they are all consistently formatted. For example, you can have street + zip for some addresses and street + city + state for others.
Results are billed as geocode + Congressional district info (i.e., two lookups). For example, if you have 100 addresses that you want Congressional districts for, that would count as 200 lookups. You can calculate how much this will cost you and how long it will take here.
**There was a 60-day transition from the Emergency Broadband Benefit Program to the Affordable Connectivity Program in January 2022 and February 2022. Households that were enrolled in the EBB Program as of December 31, 2021 continued to receive a monthly benefit of up to $50 during the transition period.
ACP Funding Summary by GeographyThe ACP Funding Summary by Geography file shows a summary of total ACP support claimed by state, county, ZIP code, and congressional district. USAC will continue to update the data on a monthly basis. Monthly totals may adjust as new claims are submitted or as past claims are revised.
The following files include EBB and ACP households and claims by zip code and county. USAC will continue to update the data on a monthly basis. Previously, these files included both enrollment and claims data. However, starting on November 1, enrollment and claims data are published in separate files.
Providers begin certifying claims on the 1st of the month for the prior data month (i.e., for example, on May 1 providers can begin to certify claims for the April 2022 data month). To be reimbursed within the current month, providers must certify the claims by the 15th of that month.
ACP providers have up to two months to submit original claims or upward revisions of previous claims. ACP providers must fully pass through ACP support to eligible households each month in the form of a discount regardless of when they file a claim for reimbursement. Each month, we will update the data to reflect claims certified during the two-month window.
The Zip Code files allow users to view the total enrolled households by zip code and data month with a breakout by verification method. The columns that represent new enrollments for each category reflect the change in subscribers from the prior month, which include all newly enrolled subscribers net of subscribers who may have been de-enrolled. The file also includes claims by zip code and data month with breakout between monthly broadband service and connected devices. A small number of claims may occur via manual processes outside of the system due to FCC-issued waivers or other ad-hoc processes. Those claims are not reflected in this table.
The County files allow users to view the total enrolled households by county and data month with a breakout by verification method. The columns that represent new enrollments for each category reflect the change in subscribers from the prior month, which include all newly enrolled subscribers net of subscribers who may have been de-enrolled. The file also includes claims by county and data month with breakout between monthly broadband service and connected devices. A small number of claims may occur via manual processes outside of the system due to FCC-issued waivers or other ad-hoc processes. Those claims are not reflected in this table.
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