Sold by: Rearc
Deployed on AWS
This product contains a historical time-series data of the Federal Debt: Total Public Debt (GFDEBTN) retrieved from the Federal Reserve Bank of St. Louis Economic Data (FRED) at https://fred.stlouisfed.org/series/GFDEBTN. Data coverage starts from 1966-01-01. The unit of data column is Millions of Dollars and the values are not seasonally adjusted. The update frequency is quarterly, end of period.
Overview
Federal Debt: Total Public Debt (GFDEBTN) | FRED
The source code outlining how this product gathers, transforms, revises and publishes its datasets is available at https://github.com/rearc-data/fred-data-products .
Main Overview
The dataset file included with this product is provided in CSV format. The included dataset contains the following columns: DATE, GFDEBTN
This dataset contains a historical time-series data of Federal Debt: Total Public Debt (GFDEBTN) starting from 1966-01-01.
The values within the data field labeled GFDEBTN represent the total debt of the US federal government in Millions of Dollars at the time of the corresponding DATE field. Values are not seasonally adjusted.
Data Source
This dataset is provided by the Federal Reserve Bank of St. Louis Economic Data (FRED).
More Information
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Source:
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Dataset Page: Federal Debt: Total Public Debt (GFDEBTN) | FRED
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License: FRED Terms Of Use FAQ
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Frequency: Quarterly, end of period
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Format: 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 :heart:.
- 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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Pricing
This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
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Dimensions summary
This product is offered at no cost. You subscribe through a single dimension, Product Access (Units), which grants you access to the dataset. There are no tiers, usage add-ons, or size-based options to choose from. Because pricing is free, there is nothing that scales up or down based on usage or quantity. The vendor publishes free, publicly available datasets so you can consume them in a consistent way. Your one subscription action gives you access to the full listing.
Top-of-mind questions for buyers
One unit of Product Access is the single subscription that grants you access to the dataset. It is not tied to a number of users, records, or downloads. Subscribing once gives you access to the listing at no cost.
No. The product is offered at no cost through a single access dimension. There are no tiers, usage add-ons, or size-based charges. Consuming more data does not trigger any cost change, and there is no threshold that shifts you into a paid amount.
You get access to a publicly available dataset that the vendor sources, transforms, and publishes so you can consume it in a consistent way. The vendor manages the data life cycle, which removes the work of acquiring and processing the source data yourself.
www.rearc.io
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Refunds Not Applicable
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
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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 |
|---|---|---|---|---|---|---|
Federal Debt: Total Public Debt (GFDEBTN) | FRED | All historical revisions | All future revisions | Not included | Not included |
Resources
Vendor resources
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