Total outstanding debt of the U.S. government reported daily. Includes a breakout of intragovernmental holdings (federal debt held by U.S. government) and debt held by the public (federal debt held by entities outside the U.S. government).

Government Debt Indicators (OECD)

Country-level Measurements of General Government Debt

By OECD [source]

About this dataset

This dataset provides key indicators regarding the general government debt of OECD countries. These figures reflect the fact that an unfortunate portion of a country’s annual budget is allocated to repaying debt, and suggest different levels of financial stability across nations. By examining this data, we can observe fluctuations in public debt levels over time, as well as how various countries compare in terms of their general government debt buckets. Featuring monthly measurements for multiple years, these data points provide valuable insight into how borrowing affects the overall financial landscapes of the countries captured. Additionally, a convenient flag code system separately gauges the data’s accuracy and credibility to ensure that only reliable readings are observed

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How to use the dataset

• This dataset contains indicators on general government debt for OECD members and selected non-members. The indicators included in this dataset are useful in measuring country-level financial stability and understanding the sources of government financing. This dataset is a great resource for researchers, policy makers, and data journalists who are interested in analyzing trends in public finances across countries.

• The data is organized by twelve columns, which include LOCATION, INDICATOR, SUBJECT, MEASURE, FREQUENCY (annual or quarterly), TIME (year), Value (in national currency units where applicable) and Flag Codes which denote the accuracy of a given value’s measurement. To access specific information from this dataset such as a values or locations associated with particular indicators such as “Gross Debt of General Government” one can use the filtering options available to select specific regions that they want to compare against each other. The results page will show multiple graphs where users can export individual numbers or view/download all datasets related to particular subgroups based on their selection criteria. Additionally users can choose to generate tables if they wish to compare numerical results rather than graphical ones since each entry shows details up until 2018 along with values published over various years when available.

• It is important that users take note of any flag codes pertaining these datasets as this indicates why data may have been missing from specific points series entries under certain conditions thus providing additional context that should be good practice for comparative analysis purposes between different countries' results for instance. Finally we recommend that advanced users download directly and read through raw csv files provided at the link contained within this description so as to better understand how variables were recorded upon original entry though always keep current standards corresponding filtering column filter selection into account prior making any graphical comparison output interpretations without confirmation further details from more authoritative sources including national treasuries departments themselves if possible beforehand nature needed since all fields contained were originally filled out just once during collection process associated source year indicated at time entry only after has been approved management group curation following validation our accuracy protocols chosen site lastly once all said taken care creating memorable finalized looks report visualizations done easier all via software programs compatible kaggle now let's get started analyzing!

Research Ideas

• Computing gender-disaggregated government debt levels to reveal systemic imbalances such as gender inequality in government spending.
• Estimating the amount of money spent on infrastructure projects by specific OECD countries over a certain period of time.
• Modeling and predicting future macroeconomic trends in terms of general government debt, for use in investment and financial planning activities

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - **Give appropriate cr...

The United States recorded a Government Debt to GDP of 124.30 percent of the country's Gross Domestic Product in 2024. This dataset provides - United States Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Federal Debt: Total Public Debt (GFDEBTN) from Q1 1966 to Q2 2025 about public, debt, federal, government, and USA.

This dataset provides the monthly total of gift contributions received by the U.S. Treasury that were donated to reduce the public debt. These donations can include money, outstanding government obligations, and property that is sold for cash.

Households Debt in the United States decreased to 68.30 percent of GDP in the first quarter of 2025 from 69.40 percent of GDP in the fourth quarter of 2024. This dataset provides - United States Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Private Debt to GDP in the United States decreased to 142 percent in 2024 from 147.50 percent in 2023. United States Private Debt to GDP - values, historical data, forecasts and news - updated on December of 2025.

College Scorecard

The College Scorecard dataset is provided by the U.S. Department of Education and contains information on nearly every college and university in the United States. The dataset includes data on student loan repayment rates, graduation rates, affordability, earnings after graduation, and more. The goal of this dataset is to help students make informed decisions about their college choice by providing them with clear and concise information about each school's performance

How to use the dataset

This dataset can help understand the cost of attending college in the United States, as well as the average debt load for students. It can also be used to compare different schools in terms of their graduation rates and repayment rates

Columns

• UNITID: Unit ID for institution
• INSTNM: Institution name
• CITY: City
• STABBR: State
• ZIP: Zip code
• OPEID: OPE ID for institution
• OPEID6: OPE ID for institution (6-digit)
• ACCREDAGENCY: Accrediting Agency
• INSTURL: Institution URL
• NPCURL: Net Price Calculator URL
• SCH_DEG: Highest degree awarded
• HCM2: Carnegie Classification 2010:** Basic
• MAIN: Carnegie Classification 2010:** Main
• NUMBRANCH: Number of branch campuses
• PREDDEG: Predominant degree awarded
• HIGHDEG: Highest degree awarded
• CONTROL: Control of institution
• ST_FIPS: State FIPS code
• REGION: Region
• LOCALE: Locale code
• LOCALE2: Locale code (multiple categories per state)
• CCBASIC: Carnegie Classification 2010:** Basic
• CCMAIN: Carnegie Classification 2010:** Main
• CCUGPROF: Carnegie Classification 2010:** Undergraduate Profile
• CCSIZSET: Carnegie Classification 2010:** Size and Setting
• HBCU: Historically Black College or University
• PBI: Predominantly Black Institution
• ANNHI: Tribal College or University
• TRIBAL: Tribal College or University (Public)
• AANAPII: Asian American and Native American Pacific Islander-Serving Institution
• HSIP: Hispanic-Serving Institution (HSI)
• NANTI: Native American-Serving Nontribal Institution
• MENONLY: Men only
• WOMENONLY: Women only
• RELAFFIL: Religious affiliation
• DISTANCEONLY: Distance-only
• CURROPER: Currently operating
• VETERAN: Veteran-supportive
• LIMDEP: Limited-degree-granting
• HIGHDEG_GRANTED: Highest degree granted
• PS: Predominantly two-year public
• UGRD_ENRL_TOTAL: Undergraduate total enrollment
• GRAD_ENRL_TOTAL: Graduate total enrollment
• UGRD_ENRL_ORIG_YR2_RT: Undergraduate, first-time, first-year retention rate (%)

Acknowledgements

This data was originally collected by the US Department of Education and made available on their website. Thank you to the US Department of Education for making this data available!

Government Debt in Canada increased to 1223.62 CAD Billion in 2024 from 1173.01 CAD Billion in 2023. This dataset provides - Canada Government Debt- actual values, historical data, forecast, chart, statistics, economic calendar and news.

I downloaded this dataset from Wikipedia. I was startled when I came across a video to realise that the United States has the highest external debt among world countries. India and Brazil lie at around 20th positions. United Kingdom's external debt is a staggering 273% of their GDP while India's is 19.20 %. Brazil's external debt is 38% of their GDP. The United States' external debt is 96.40 % of their GDP while Japan has 101 % of its GDP as its external debt.

The dataset contains the country names, their external debt, their per capita external debt, the date of entering the data and the external debt as a percentage of their GDP.

The data can be cleaned and can form an excellent use case for LLM based data analytics. The data must be cleaned. The data can be combined with other financial data of the respective countries to form a complete database of financial metrics.

India recorded a Government Debt to GDP of 81.92 percent of the country's Gross Domestic Product in 2024. This dataset provides - India Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

this graph was created in fred.stlouisfed, Canva, R :

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Your Guide to America's Finances is an overview of U.S. government finances where you’ll find information on money coming in (revenue), money going out (spending), the deficit, and debt. Your Guide presents a series of pages exploring each topic through educational content and interactive visualizations, providing a comprehensive overview of the trillions of dollars collected and spent by the federal government each year. Where does federal revenue come from? If you lived or worked in the United States in 2024, your tax contributions are likely part of the $4.92 trillion collected in revenue. The federal government also collects revenue from services like admission to national parks and customs duties on foreign imports and exports. The majority of this revenue is used to pay for government activities (employee salaries, infrastructure maintenance), as well as to pay for goods and services provided to United States citizens and businesses.

In FY 2024, the federal government spent $6.75 trillion. Since the government spent more than it collected, the deficit for 2024 was $1.83 trillion. Visit our Spending and Deficit pages for more information on these activities.

This dataset provides values for GOVERNMENT DEBT TO GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset contains quarterly data on the public debt in the United States, starting from 1996 and running up to 2023. Public debt, also known as government debt, represents the total outstanding debt (bonds and other securities) of a country’s central government. Public debt as a percentage of GDP is often used by investors to measure a country's ability to make future payments on its debt, thus affecting the country's borrowing costs and government bond yields.

Content: The dataset comprises two columns:

Date: The end date of the respective quarter (MM/DD/YYYY format). Value: The total US public debt at the end of the respective quarter (in billions of USD). Acknowledgements: Data for this set is sourced from the US Department of the Treasury.

Inspiration: The US Public Debt is a critical economic indicator. Analysis of this data can offer insights into the fiscal health of the US government, its fiscal policy, and its ability to meet future obligations.

This dataset could be of interest to economists, financial analysts, data scientists, students, and anyone interested in the US economy or government finance.

Usability: The Public Debt data can be used for a variety of purposes:

Economic Analysis: It can be used for macroeconomic analysis and forecasting.

Government Finance Analysis: It can serve as a key indicator of the fiscal health of the US government.

Investment Analysis: Public debt levels can impact interest rates, inflation, and financial markets. Analysts can use this data to better understand these dynamics.

Policy Understanding: It can help understand the fiscal policy of the US government.

Education: It can be used in classrooms for teaching economics, finance, and related disciplines.

This dataset is about countries per year in Costa Rica. It has 64 rows. It features 4 columns: country, central government debt, and internally displaced persons, by conflict and violence.

The schools that create the most student debt

The top 10 schools for student loan debt in the United States

By Andy Kriebel [source]

About this dataset

This dataset contains information on the amount of student loan debt originated by schools in the United States for the 2020-2021 academic year. The data includes the school name, city, state, zip code, school type, loan type, number of recipients, number of loans originated, amount of money loaned, and number of disbursements

How to use the dataset

There are a few things to keep in mind when using this dataset:

• The data is for the 2020-2021 academic year.
• The data is for student loan debt originated by schools in the United States.
• The data is sorted by school.
• The columns of interest are: School, City, State, Zip Code, School Type, Loan Type, Recipients, # of Loans Originated, $ of Loans Originated, # of Disbursements, and $ of Disbursements

Research Ideas

• The dataset can be used to calculate the amount of loan debt originated by each type of school.
• The dataset can be used to calculate the amount of loan debt originated by each state.
• The dataset can be used to help students estimate their future student loan debt

Acknowledgements

The data for this visualization comes from the Common Origination and Disbursement (COD) System through the Department of Education

Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Student Loan Debt by School 2020-2021.csv | Column name | Description | |:--------------------------|:-------------------------------------------------| | School | The name of the school. (String) | | City | The city where the school is located. (String) | | State | The state where the school is located. (String) | | Zip Code | The zip code of the school. (String) | | School Type | The type of school. (String) | | Loan Type | The type of loan. (String) | | Recipients | The number of recipients of the loan. (Integer) | | # of Loans Originated | The number of loans originated. (Integer) | | $ of Loans Originated | The amount of money originated in loans. (Float) | | # of Disbursements | The number of disbursements. (Integer) | | $ of Disbursements | The amount of money disbursed. (Float) |

Acknowledgements

If you use this dataset in your research, please credit Andy Kriebel.

This dataset is about countries per year in Brunei. It has 64 rows. It features 4 columns: country, central government debt, and internally displaced persons, by conflict and violence.

This dataset includes various economic indicators such as stock market performance, inflation rates, GDP, interest rates, employment data, and housing index, all of which are crucial for understanding the state of the economy. By analysing this dataset, one can gain insights into the causes and effects of past recessions in the US, which can inform investment decisions and policy-making.

There are 20 columns and 343 rows spanning 1990-04 to 2022-10

The columns are:

1. Price: Price column refers to the S&P 500 lot price over the years. The S&P 500 is a stock market index that measures the performance of 500 large companies listed on stock exchanges in the United States. This variable represents the value of the S&P 500 index from 1980 to present. Industrial Production: This variable measures the output of industrial establishments in the manufacturing, mining, and utilities sectors. It reflects the overall health of the manufacturing industry, which is a key component of the US economy.

2. INDPRO: Industrial production measures the output of the manufacturing, mining, and utility sectors of the economy. It provides insights into the overall health of the economy, as a decline in industrial production can indicate a slowdown in economic activity. This data can be used by policymakers and investors to assess the state of the economy and make informed decisions.

3. CPI: CPI stands for Consumer Price Index, which measures the change in the prices of a basket of goods and services that consumers purchase. CPI inflation represents the rate at which the prices of goods and services in the economy are increasing.

4. Treasure Bill rate (3 month to 30 Years): Treasury bills (T-bills) are short-term debt securities issued by the US government. This variable represents the interest rates on T-bills with maturities ranging from 3 months to 30 years. It reflects the cost of borrowing money for the government and provides an indication of the overall level of interest rates in the economy.

5. GDP: GDP stands for Gross Domestic Product, which is the value of all goods and services produced in a country. This dataset is taking into account only the Nominal GDP values. Nominal GDP represents the total value of goods and services produced in the US economy without accounting for inflation.

6. Rate: The Federal Funds Rate is the interest rate at which depository institutions lend reserve balances to other depository institutions overnight. It is set by the Federal Reserve and is used as a tool to regulate the money supply in the economy.

7. BBK_Index: The BBKI are maintained and produced by the Indiana Business Research Center at the Kelley School of Business at Indiana University. The BBK Coincident and Leading Indexes and Monthly GDP Growth for the U.S. are constructed from a collapsed dynamic factor analysis of a panel of 490 monthly measures of real economic activity and quarterly real GDP growth. The BBK Leading Index is the leading subcomponent of the cycle measured in standard deviation units from trend real GDP growth.

8. Housing Index: This variable represents the value of the housing market in the US. It is calculated based on the prices of homes sold in the market and provides an indication of the overall health of the housing market.

9. Recession binary column: This variable is a binary indicator that takes a value of 1 when the US economy is in a recession and 0 otherwise. It is based on the official business cycle dates provided by the National Bureau of Economic Research.

Context

Gross Public debt in the United States by State from 1957 till 2020

debt

Debt is an obligation that requires one party, the debtor, to pay money or other agreed-upon value to another party, the creditor. Debt is a deferred payment, or series of payments, which differentiates it from an immediate purchase

https://www.usgovernmentspending.com/compare_state_spending_2020bH0an

Data

The data contains 50+ CSV files, Merge them together into one through the year and state and they will provide meaningful and helpful insights.

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore the World Bank using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using the World Bank's APIs and Kaggle's API.

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