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This release contains information on the amount of employees in the United States, excluding proprietors, private household employees, unpaid volunteers, farm employees, and the unincorporated self-employed. The employees in the provided data contribute to about 80 percent of the United States Gross Domestic Product (GDP).
Overview
The source code outlining how this product gathers, transforms, revises and publishes its datasets is available at https://github.com/rearc-data/fred-employees-total-nonfarm .
Main Overview
This release contains information on the amount of employees in the United States, excluding proprietors, private household employees, unpaid volunteers, farm employees, and the unincorporated self-employed. The employees in the provided data contribute to about 80 percent of the United States Gross Domestic Product (GDP).
The included data is provided by the Federal Reserve Bank of St. Louis' FRED (Federal Reserve Economic Data) platform, which contains information on over 700,000+ series related to historical economic data. If you are interested in learning more or want to explore other datasets maintained on FRED, visit the FRED homepage .
Data Source
This resource is presented in both the XLS and CSV formats. The included dataset contains the following columns:
DATE, PAYEMS
The PAYEMS column represents the amount of employees in the U.S. at the time of the corresponding date.
More Information
- Source: Federal Reserve Economic Data (FRED)
- FRED | Federal Reserve Bank of St. Louis
- Federal Reserve Bank of St. Louis | Homepage
- Terms of Use FAQ
- Frequency: Monthly
- Formats: XLS, CSV
Contact Details
- If you find any issues with or have enhancement ideas for this product, open up a GitHub issue and we will gladly take a look at it. Better yet, submit a pull request. Any contributions you make are greatly appreciated ❤️.
- If you are looking for specific open datasets currently not available on ADX, please submit a request on our project board here .
- If you have questions about the source data, please contact FRED .
- If you have any other questions or feedback, send us an email at data@rearc.io .
About Rearc
Rearc is a cloud, software and services company. We believe that empowering engineers drives innovation. Cloud-native architectures, modern software and data practices, and the ability to safely experiment can enable engineers to realize their full potential. We have partnered with several enterprises and startups to help them achieve agility. Our approach is simple — empower engineers with the best tools possible to make an impact within their industry.
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Dimensions summary
This listing is free. It has one dimension, Product Access (Units), which grants you access to the dataset as a subscriber. There are no tiers, usage add-ons, or instance sizes to choose from. You subscribe once to consume the data, with no charge tied to volume or time. The publisher sources this public dataset and delivers it in a consistent format through AWS Data Exchange, so you can pull it into your data pipeline without acquiring or processing it yourself.
Top-of-mind questions for buyers
It grants you subscriber access to consume the dataset through AWS Data Exchange. One subscription covers your access to the data. There are no per-record, per-query, or per-user counts. You are not billed by volume or time. The unit simply enables entitlement to pull the data.
No. This listing is free and has no usage-based charges. Pulling more records, running more queries, or accessing the data more often does not add cost. There are no tiers or included-amount thresholds to exceed. Your entitlement stays the same regardless of how much you consume.
No. The publisher sources this public dataset and delivers it in a consistent format through AWS Data Exchange. You subscribe and pull the data into your pipeline without acquiring or transforming it yourself. The subscription handles the delivery, so no separate processing setup is required on your side.
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Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Additional details
You will receive access to the following data sets.
Data set name | Type | Historical revisions | Future revisions | Sensitive information | Data dictionaries | Data samples |
|---|---|---|---|---|---|---|
All Employees: Total Nonfarm | FRED | All historical revisions | All future revisions | Not included | Not included |
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